{"year":"2024","title":"$\\textit {Read-ME} $: Refactorizing LLMs as Router-Decoupled Mixture of Experts with System Co-Design","authors":["R Cai, Y Ro, GW Kim, P Wang, BE Bejnordi, A Akella… - The Thirty-eighth Annual …"],"snippet":"The proliferation of large language models (LLMs) has led to the adoption of Mixture-of-Experts (MoE) architectures that dynamically leverage specialized subnetworks for improved efficiency and performance. Despite their benefits, MoE models face significant …","url":["https://openreview.net/pdf?id=i8JaxY7tDI"]}
{"year":"2024","title":"1-Diffractor: Efficient and Utility-Preserving Text Obfuscation Leveraging Word-Level Metric Differential Privacy","authors":["S Meisenbacher, M Chevli, F Matthes - arXiv preprint arXiv:2405.01678, 2024"],"snippet":"The study of privacy-preserving Natural Language Processing (NLP) has gained rising attention in recent years. One promising avenue studies the integration of Differential Privacy in NLP, which has brought about innovative methods in a variety …","url":["https://arxiv.org/pdf/2405.01678"]}
{"year":"2024","title":"101 Billion Arabic Tokens Dataset","authors":["M Aloui, H Chouikhi, G Chaabane, H Kchaou…"],"snippet":"… , we heavily depend on Common Crawl (1) as our primary source of web-scraped content. Common Crawl provides an accessible web archive … a Dataset Pipeline expressed in the following figure (1) aimed at cleaning up the web-extracted text …","url":["https://www.researchgate.net/profile/Hasna-Chouikhi/publication/380396476_101_Billion_Arabic_Words_Dataset/links/663a610306ea3d0b742f3141/101-Billion-Arabic-Words-Dataset.pdf"]}
{"year":"2024","title":"101 Billion Arabic Words Dataset","authors":["M Aloui, H Chouikhi, G Chaabane, H Kchaou… - arXiv preprint arXiv …, 2024"],"snippet":"… We undertook a large-scale data mining project, extracting a substantial volume of text from the Common Crawl WET files, specifically targeting Arabic content. The extracted data underwent a rigorous cleaning and deduplication process, using …","url":["https://arxiv.org/pdf/2405.01590"]}
{"year":"2024","title":"14 Deep Field of Learning Artificial Impacts Intelligence in the","authors":["R Gulwani, M Aggarwal - Deep Learning Concepts in Operations Research, 2024"],"snippet":"… These datasets, such as ImageNet for computer vision or the Common Crawl for natural language processing, have played a crucial role in training deep learning models and pushing the boundaries of AI performance. …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=qlYXEQAAQBAJ&oi=fnd&pg=PA153&dq=commoncrawl&ots=E_-QAqwqMa&sig=P2vY6z3r_LqzYZg0D8_Douwj95E"]}
{"year":"2024","title":"15 OpenAl ChatGPT and Biased","authors":["MJ O'Brien, I Alsmadi, RA Bentley - … Digital Education with ChatGPT: From Theoretical …, 2024"],"snippet":"According to its website (https://openai. com/blog/introducing-openai), San Francisco-based OpenAI was founded in 2015 as a “non-profit artificial intelligence research company. Our goal is to advance digital intelligence in the way that is most likely to benefit …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=GlorEQAAQBAJ&oi=fnd&pg=PA223&dq=commoncrawl&ots=M7QpPTZKLB&sig=NqASDNRDU40KmGxOxIwRqZndY-s"]}
{"year":"2024","title":"2 Text Preprocessing Method","authors":["J Peng, S Huo"],"snippet":"This paper uses easy data augmentation (EDA) and back translation for text enhancement. After text enhancement, the number of samples in the dataset can be significantly increased, which is helpful for model parameters through training and …","url":["https://journals.riverpublishers.com/index.php/JWE/article/download/25003/19983?inline=1"]}
{"year":"2024","title":"4 CHATGPT IN ACADEMIA: AN IN-DEPTH EXPLORATION OF STUDENT VIEWS–PROS AND CONS","authors":["D Rajkumar, P Murugeswari, M Karthigaieswari - TRANSDISCIPLINARY THREADS"],"snippet":"… GPT-3’s training data came from five existing datasets: • Common Crawl: A collection of text pulled from billions of web pages containing trillions of words. OpenAI filtered it for high-quality reference material only. • WebText2: OpenAI …","url":["https://www.researchgate.net/profile/Namrata-Shrivastava/publication/378011746_TRANSDISCIPLINARY_THREADS_CRAFTING_THE_FUTURE_THROUGH_MULTIDISCIPLINARY_RESEARCH_VOLUME_-2_httpswwwamazonindp9392917295ref_cm_sw_r_apan_dp_DF7WRSTHCX72MEDVWPB2languageen-IN/links/65c33ae71e1ec12eff78f577/TRANSDISCIPLINARY-THREADS-CRAFTING-THE-FUTURE-THROUGH-MULTIDISCIPLINARY-RESEARCH-VOLUME-2-https-wwwamazonin-dp-9392917295ref-cm-sw-r-apan-dp-DF7WRSTHCX72MEDVWPB2-languageen-IN.pdf#page=34"]}
{"year":"2024","title":"5 LLM Pretraining Methods","authors":["A Velu, R Ramamoorthy, SM Manasa, A Prasanth - Generative AI and LLMs"],"snippet":"… – Websites: This feature provides a vast array of information from the internet offering a variety of linguistic expertise, eg, Common Crawl. The major drawback of such data is that the text on the web can be of two different quality levels: spam and high-quality …","url":["https://www.degruyter.com/document/doi/10.1515/9783111425078/pdf?licenseType=restricted#page=107"]}
{"year":"2024","title":"5G INSTRUCT Forge: An Advanced Data Engineering Pipeline for Making LLMs Learn 5G","authors":["AIA Said, A Mekrache, K Boutiba, K Ramantas… - IEEE Transactions on …, 2024"],"snippet":"Large Language Models (LLMs) have transformed various fields with their remarkable ability to comprehend and generate human-like text. Despite these advancements, their effectiveness in specialized domains such as finance, law …","url":["https://ieeexplore.ieee.org/abstract/document/10794684/"]}
{"year":"2024","title":"6 Performance Analysis","authors":["A Safi, S Singh, G Kaur, T Kaur - Intelligent Security Solutions for Cyber-Physical …, 2024"],"snippet":"… The dataset used in this research was gathered from Alexa and the Common Crawl archive. … from a variety of sources, including Common Crawl, Alexa, and PhishTank for the phishing … They used three datasets, including real URLs …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=1VUIEQAAQBAJ&oi=fnd&pg=PA89&dq=commoncrawl&ots=EsWoOABs6N&sig=ot4zCN0ozxE0H1-OW-AyC-mvYJA"]}
{"year":"2024","title":"\" Confrontation or Acceptance\": Understanding Novice Visual Artists' Perception towards AI-assisted Art Creation","authors":["S Zhang, S Li - arXiv preprint arXiv:2410.14925, 2024"],"snippet":"The rise of Generative Artificial Intelligence (G-AI) has transformed the creative arts landscape by producing novel artwork, whereas in the same time raising ethical concerns. While previous studies have addressed these concerns from technical …","url":["https://arxiv.org/pdf/2410.14925"]}
{"year":"2024","title":"\" Deep Learning for de-identification of clinical documents","authors":["N Huberty, S Jodogne"],"snippet":"The amount of unstructured medical documents increases each year, presenting an opportunity to extract valuable insights that could significantly improve healthcare. However, to take advantage of this potential, it is crucial to de-identify these …","url":["https://dial.uclouvain.be/downloader/downloader.php?pid=thesis%3A45971&datastream=PDF_01&cover=cover-mem"]}
{"year":"2024","title":"\" I, for One, Welcome Our New\" AI Jurors: ChatGPT and the Future of the Jury System in American Law","authors":["MJ O'Hara - Int'l JL Ethics Tech., 2024"],"snippet":"This article explores the potential for advanced generative text Al systems like ChatGPT to serve as a replacement for human juries in the modern legal system. It argues that the vast knowledge base and perspective-aggregation capabilities of …","url":["https://heinonline.org/hol-cgi-bin/get_pdf.cgi?handle=hein.journals/ijlet2024&section=21"]}
{"year":"2024","title":"\" Previously on...\" From Recaps to Story Summarization","authors":["AK Singh, D Srivastava, M Tapaswi - arXiv preprint arXiv:2405.11487, 2024"],"snippet":"We introduce multimodal story summarization by leveraging TV episode recaps - short video sequences interweaving key story moments from previous episodes to bring viewers up to speed. We propose PlotSnap, a dataset featuring two crime …","url":["https://arxiv.org/pdf/2405.11487"]}
{"year":"2024","title":"\" Transfer Learning in Natural Language Processing: Overcoming Low-Resource Challenges","authors":["T Adimulam, S Chinta, SK Pattanayak"],"snippet":"… XLM-R (XLM-RoBERTa) [20] scales up the multilingual pre-training approach, using 2.5 TB of filtered CommonCrawl data in 100 languages. XLM-R achieves stateof-the-art performance on cross-lingual classification, sequence labeling, and question …","url":["https://www.researchgate.net/profile/Suprit-Kumar-Pattanayak/publication/385818284_Transfer_Learning_in_Natural_Language_Processing_Overcoming_Low-Resource_Challenges/links/67367c7737496239b2bfead0/Transfer-Learning-in-Natural-Language-Processing-Overcoming-Low-Resource-Challenges.pdf"]}
{"year":"2024","title":"“More than Words”: A Legal Approach to the Risks of Commercial Chatbots Powered by Generative Artificial Intelligence","authors":["S Migliorini - European Journal of Risk Regulation, 2024"],"snippet":"… In the training of ChatGPT, this “clean”19 version of the Common Crawl has been complemented and filtered with the addition of a few … also that the training gave more prominence to the “clean” Common Crawl.Although this explanation may be …","url":["https://www.cambridge.org/core/services/aop-cambridge-core/content/view/4EB4DD9997211B81283EF7B34299E254/S1867299X24000047a.pdf/div-class-title-more-than-words-a-legal-approach-to-the-risks-of-commercial-chatbots-powered-by-generative-artificial-intelligence-div.pdf"]}
{"year":"2024","title":"A Balancing Act: Data Protection Compliance of Artificial Intelligence","authors":["M Bartels - GRUR International, 2024"],"snippet":"Neural network based generative artificial intelligence (GenAI) systems, in particular large language models (LLMs), hold huge potential for economic, scientific, and artistic progress. However, they are also the subject of ongoing fierce data protection …","url":["https://academic.oup.com/grurint/advance-article/doi/10.1093/grurint/ikae060/7671464"]}
{"year":"2024","title":"A Beginner's Guide to Large Language Models","authors":["E Haque - 2024"],"snippet":"Page 1 Page 2 Page 3 “LLMs are like Swiss Army knives for digital communication. Their versatility and adaptability enable them to perform many tasks, each with precision and finesse. Whether you're a writer seeking creative inspiration, a developer …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=-jEWEQAAQBAJ&oi=fnd&pg=PA11&dq=commoncrawl&ots=yx43yLb_vg&sig=TB-dnY6_qqmiTSUgTImvYTEpO5g"]}
{"year":"2024","title":"A Benchmark for Relevance-based Headline Classification and Generation","authors":["G Kanumolu - 2024"],"snippet":"The task of news headline generation deals with generating a concise summary for a given news article. It is a crucial task in increasing productivity for both the readers and producers of news. Significant progress has been made in automatically …","url":["https://web2py.iiit.ac.in/research_centres/publications/download/mastersthesis.pdf.8ae26a615845ea1f.476f70696368616e645f4d535f5468657369732e706466.pdf"]}
{"year":"2024","title":"A Big Data-empowered System for Real-time Detection of Regional Discriminatory Comments on Vietnamese Social Media","authors":["AN Huynh, TD Do, TH Do - arXiv preprint arXiv:2411.02587, 2024"],"snippet":"Regional discrimination is a persistent social issue in Vietnam. While existing research has explored hate speech in the Vietnamese language, the specific issue of regional discrimination remains under-addressed. Previous studies primarily …","url":["https://arxiv.org/pdf/2411.02587"]}
{"year":"2024","title":"A bilingual benchmark for evaluating large language models","authors":["M Alkaoud - PeerJ Computer Science, 2024"],"snippet":"This work introduces a new benchmark for the bilingual evaluation of large language models (LLMs) in English and Arabic. While LLMs have transformed various fields, their evaluation in Arabic remains limited. This work addresses this …","url":["https://peerj.com/articles/cs-1893/"]}
{"year":"2024","title":"A Blinded Comparison of Three Generative Artificial Intelligence Chatbots for Orthopaedic Surgery Therapeutic Questions","authors":["V Arora, J Silburt, M Phillips, M Khan, B Petrisor… - Cureus, 2024"],"snippet":"… Current generative large-language models (LLMs) have been trained on massive corpora of text such as common crawl - a dataset of 250 billion webpages - and thus have both a general knowledge of the world and the capacity to recapitulate human …","url":["https://www.cureus.com/articles/264839-a-blinded-comparison-of-three-generative-artificial-intelligence-chatbots-for-orthopaedic-surgery-therapeutic-questions.pdf"]}
{"year":"2024","title":"A Canary in the AI Coal Mine: American Jews May Be Disproportionately Harmed by Intellectual Property Dispossession in Large Language Model Training","authors":["H Precel, A McDonald, B Hecht, N Vincent - arXiv preprint arXiv:2403.13073, 2024"],"snippet":"Systemic property dispossession from minority groups has often been carried out in the name of technological progress. In this paper, we identify evidence that the current paradigm of large language models (LLMs) likely continues this long history …","url":["https://arxiv.org/pdf/2403.13073"]}
{"year":"2024","title":"A Closer Look at the Triad in Data-Driven Vision and Language: Curation, Representation, and Learning","authors":["J Kil - 2024"],"snippet":"Building advanced Vision and Language (V&L) systems can offer significant societal benefits. For instance, V&L systems with visual question answering capabilities enable visually impaired individuals to perform daily tasks more independently; …","url":["https://etd.ohiolink.edu/acprod/odb_etd/ws/send_file/send?accession=osu1721217385422572&disposition=inline"]}
{"year":"2024","title":"A Collocation-based Method for Addressing Challenges in Word-level Metric Differential Privacy","authors":["S Meisenbacher, M Chevli, F Matthes - arXiv preprint arXiv:2407.00638, 2024"],"snippet":"Applications of Differential Privacy (DP) in NLP must distinguish between the syntactic level on which a proposed mechanism operates, often taking the form of $\\textit{word-level}$ or $\\textit{document-level}$ privatization. Recently, several word-level $\\textit{Metric} …","url":["https://arxiv.org/pdf/2407.00638"]}
{"year":"2024","title":"A Comparative Analysis of Text Embedding Models for Bug Report Semantic Similarity","authors":["A Patil, K Han, A Jadon - 2024 11th International Conference on Signal …, 2024"],"snippet":"… For Fasttext, the ”crawl-300d-2M-subword” model was employed, which consisted of 2 million word vectors trained with subword information on the Common Crawl dataset, encompassing 600 billion tokens. In the case of Doc2Vec, the ”GoogleNews-vectors-negative300” …","url":["https://ieeexplore.ieee.org/abstract/document/10512000/"]}
{"year":"2024","title":"A Comparative Analysis of Word Embeddings Techniques for Italian News Categorization","authors":["F Rollo, G Bonisoli, L Po - IEEE Access, 2024"],"snippet":"Text categorization remains a formidable challenge in information retrieval, requiring effective strategies, especially when applied to low-resource languages such as Italian. This paper delves into the intricacies of categorizing Italian news articles …","url":["https://ieeexplore.ieee.org/iel7/6287639/10380310/10439164.pdf"]}
{"year":"2024","title":"A Comparative Study of ChatGPT and Seq2Seq Chatbot for Effective Students Advising","authors":["SK Assayed, M Alkhatib, K Shaalan - ChatGPT and Global Higher Education: Using …, 2024"],"snippet":"Artificial Intelligence (AI) chatbots are increasingly becoming a part of students’ lives, from school learning to university admissions and orientations. AI chatbots are finding ways to facilitate and improve learning experiences. Moreover, AI chatbots …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=Xy4KEQAAQBAJ&oi=fnd&pg=PA148&dq=commoncrawl&ots=xiIl7ODrch&sig=SjnxTdqq-f8-Iy1AhxxUa2Nt0lA"]}
{"year":"2024","title":"A comparative study of cross-lingual sentiment analysis","authors":["P Přibáň, J Šmíd, J Steinberger, A Mištera - Expert Systems with Applications, 2024"],"snippet":"This paper presents a detailed comparative study of the zero-shot cross-lingual sentiment analysis. Namely, we use modern multilingual Transformer-based models and linear transformations combined with CNN and LSTM neural networks. We …","url":["https://www.sciencedirect.com/science/article/pii/S095741742400112X"]}
{"year":"2024","title":"A Comparison of Pretrained Models for Classifying Issue Reports","authors":["J Heo, G Kwon, C Kwak, S Lee - IEEE Access, 2024"],"snippet":"Issues are evolving requirements which are the main factor that increase the cost of software evolution. To help developers manage issues, GitHub provides issue labeling mechanisms in issue management systems. However, manually labeling …","url":["https://ieeexplore.ieee.org/iel8/6287639/6514899/10546475.pdf"]}
{"year":"2024","title":"A Complete Survey on LLM-based AI Chatbots","authors":["SK Dam, CS Hong, Y Qiao, C Zhang - arXiv preprint arXiv:2406.16937, 2024"],"snippet":"The past few decades have witnessed an upsurge in data, forming the foundation for data-hungry, learning-based AI technology. Conversational agents, often referred to as AI chatbots, rely heavily on such data to train large language models (LLMs) and …","url":["https://arxiv.org/pdf/2406.16937"]}
{"year":"2024","title":"A comprehensive evaluation of large language models in mining gene relations and pathway knowledge","authors":["M Azam, Y Chen, MO Arowolo, H Liu, M Popescu, D Xu - Quantitative Biology, 2024"],"snippet":"… As LLMs typically used the Common Crawl dataset [17], any web materials open to the public, such as PubMed abstracts [18] and publications at the PMC Open Access [19], may be included in the training text of LLMs. The result in Figure 3 may …","url":["https://onlinelibrary.wiley.com/doi/pdf/10.1002/qub2.57"]}
{"year":"2024","title":"A Comprehensive Examination of ChatGPT's Contribution to the Healthcare Sector and Hepatology","authors":["K Kumari, SK Pahuja, S Kumar - Digestive Diseases and Sciences, 2024"],"snippet":"… The model underwent training using a more extensive and varied dataset, which involved the amalgamation of Common Crawl and WebText [5]. One notable attribute of GPT-2 was its proficiency in producing logically connected and plausible …","url":["https://link.springer.com/article/10.1007/s10620-024-08659-4"]}
{"year":"2024","title":"A comprehensive literature review on phishing URL detection using deep learning techniques","authors":["E Kritika - Journal of Cyber Security Technology, 2024"],"snippet":"… The selected papers conducted research based on the data curated from open sources common to most such as Phishtank, Openphish, ISCX 2016, Kaggle, github and phishstorm for collecting malicious urls and Alexa, domcop, common crawl, and …","url":["https://www.tandfonline.com/doi/abs/10.1080/23742917.2024.2378552"]}
{"year":"2024","title":"A Comprehensive Review on Large Language Models","authors":["A Yadav - … Software Engineering Through AI, Federated Learning …, 2024"],"snippet":"In the realm of computer science and language, large language models (LLMs) stand out as remarkable tools of artificial intelligence (AI). Proficient in deciphering intricate language nuances, LLMs offer sensible responses and find applications in …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=sd0FEQAAQBAJ&oi=fnd&pg=PA17&dq=commoncrawl&ots=Mfcu5iTaq4&sig=eYkY6zLRcF4QgfOXXfp_HUxZO_4"]}
{"year":"2024","title":"A Comprehensive Survey and Guide to Multimodal Large Language Models in Vision-Language Tasks","authors":["CX Liang, P Tian, CH Yin, Y Yua, W An-Hou, L Ming… - arXiv preprint arXiv …, 2024"],"snippet":"This survey and application guide to multimodal large language models(MLLMs) explores the rapidly developing field of MLLMs, examining their architectures, applications, and impact on AI and Generative Models. Starting with foundational …","url":["https://arxiv.org/pdf/2411.06284"]}
{"year":"2024","title":"A Comprehensive Survey of Small Language Models in the Era of Large Language Models: Techniques, Enhancements, Applications, Collaboration with LLMs, and …","authors":["F Wang, Z Zhang, X Zhang, Z Wu, T Mo, Q Lu, W Wang… - arXiv preprint arXiv …, 2024"],"snippet":"Large language models (LLM) have demonstrated emergent abilities in text generation, question answering, and reasoning, facilitating various tasks and domains. Despite their proficiency in various tasks, LLMs like LaPM 540B and Llama-3.1 …","url":["https://arxiv.org/pdf/2411.03350"]}
{"year":"2024","title":"A Computational Analysis of Transcribed Speech of People Living with Dementia: The Anchise 2022 Corpus","authors":["F Sigona, DP Radicioni, BG Fivela, D Colla… - Computer Speech & …, 2024"],"snippet":"Introduction Automatic linguistic analysis can provide cost-effective, valuable clues to the diagnosis of cognitive difficulties and to therapeutic practice, and hence impact positively on wellbeing. In this work, we analyzed transcribed conversations …","url":["https://www.sciencedirect.com/science/article/pii/S0885230824000743"]}
{"year":"2024","title":"A contemporary review on chatbots, AI-powered virtual conversational agents, ChatGPT: Applications, open challenges and future research directions","authors":["A Casheekar, A Lahiri, K Rath, KS Prabhakar… - Computer Science Review, 2024"],"snippet":"This review paper offers an in-depth analysis of AI-powered virtual conversational agents, specifically focusing on OpenAI’s ChatGPT. The main contributions of this paper are threefold: (i) an exhaustive review of prior literature on chatbots, (ii) a …","url":["https://www.sciencedirect.com/science/article/pii/S1574013724000169"]}
{"year":"2024","title":"A Controlled Study on Long Context Extension and Generalization in LLMs","authors":["Y Lu, JN Yan, S Yang, JT Chiu, S Ren, F Yuan, W Zhao… - arXiv preprint arXiv …, 2024"],"snippet":"Broad textual understanding and in-context learning require language models that utilize full document contexts. Due to the implementation challenges associated with directly training long-context models, many methods have been proposed for …","url":["https://arxiv.org/pdf/2409.12181"]}
{"year":"2024","title":"A Copious Void: Rhetoric as Artificial Intelligence 1.0","authors":["A Hallsby - Rhetoric Society Quarterly, 2024"],"snippet":"Rhetoric is a trace retained in and by artificial intelligence (AI) technologies. This concept illuminates how rhetoric and AI have faced issues related to information abundance, entrenched social inequalities, discriminatory biases, and the …","url":["https://www.tandfonline.com/doi/pdf/10.1080/02773945.2024.2343265"]}
{"year":"2024","title":"A Critical Analysis of the Largest Source for Generative AI Training Data: Common Crawl","authors":["S Baack - The 2024 ACM Conference on Fairness, Accountability …, 2024"],"snippet":"… among LLM builders about the implications of using Common Crawl’s data. This paper discusses what Common Crawl’s popularity for LLM development means … Our qualitative analysis is based on indepth interviews with Common Crawl staffers …","url":["https://dl.acm.org/doi/abs/10.1145/3630106.3659033"]}
{"year":"2024","title":"A critical examination of document-level machine translation systems","authors":["P Nayak - 2024"],"snippet":"The need for accurate and effective translation cannot be overstated in an increasingly globalised world where communication is paramount. Bridging language barriers is important for promoting understanding and cooperation among …","url":["https://doras.dcu.ie/29345/1/19213962_final_thesis_upload.pdf"]}
{"year":"2024","title":"A Cross-Domain Benchmark for Active Learning","authors":["T Werner, J Burchert, M Stubbemann… - arXiv preprint arXiv …, 2024"],"snippet":"Active Learning (AL) deals with identifying the most informative samples for labeling to reduce data annotation costs for supervised learning tasks. AL research suffers from the fact that lifts from literature generalize poorly and that only a small number …","url":["https://arxiv.org/pdf/2408.00426"]}
{"year":"2024","title":"A CURATEd CATalog: Rethinking the Extraction of Pretraining Corpora for Mid-Resourced Languages","authors":["J Palomar-Giner, JJ Saiz, F Espuña, M Mina, S Da Dalt… - Proceedings of the 2024 …, 2024"],"snippet":"We present and describe two language resources in this paper: CATalog 1.0, the largest text corpus in Catalan to date, and CURATE (Corpus Utility for RAting TExt), a modular, parallelizable pipeline used for processing and scoring documents …","url":["https://aclanthology.org/2024.lrec-main.31.pdf"]}
{"year":"2024","title":"A Dataset for Pharmacovigilance in German, French, and Japanese: Annotating Adverse Drug Reactions across Languages","authors":["L Raithel, HS Yeh, S Yada, C Grouin, T Lavergne… - arXiv preprint arXiv …, 2024"],"snippet":"User-generated data sources have gained significance in uncovering Adverse Drug Reactions (ADRs), with an increasing number of discussions occurring in the digital world. However, the existing clinical corpora predominantly revolve around scientific …","url":["https://arxiv.org/pdf/2403.18336"]}
{"year":"2024","title":"A Dataset for the Detection of Dehumanizing Language","authors":["P Engelmann, PB Trolle, C Hardmeier - arXiv preprint arXiv:2402.08764, 2024"],"snippet":"… The Common Crawl is an open repository of web crawled data, which features crawls from all … As the Common Crawl includes several petabytes of data in total, we have selectively ex… As we limit ourselves to English, the Common Crawl data …","url":["https://arxiv.org/pdf/2402.08764"]}
{"year":"2024","title":"A Decade's Battle on Dataset Bias: Are We There Yet?","authors":["Z Liu, K He - arXiv preprint arXiv:2403.08632, 2024"],"snippet":"We revisit the \"dataset classification\" experiment suggested by Torralba and Efros a decade ago, in the new era with large-scale, diverse, and hopefully less biased datasets as well as more capable neural network architectures. Surprisingly, we …","url":["https://arxiv.org/pdf/2403.08632"]}
{"year":"2024","title":"A Deep Learning Approach to Fine-Grained Political Ideology Classification on Social Media Texts","authors":["ER Kovacs, LA Cotfas, C Delcea - International Conference on Computational …, 2024"],"snippet":"Starting with the mid-2010s, the growing impact of social media on politics has been felt worldwide. This impact became even more decisive in instances such as the 2020 US Presidential Election, where a bitter division between the two main US …","url":["https://link.springer.com/chapter/10.1007/978-3-031-70819-0_1"]}
{"year":"2024","title":"A Deep Neural Network Model for Classifying Pharmacy Practice Publications into Research Domains","authors":["SO Adeosun, AB Faibille, AN Qadir, JT Mutwol… - Research in Social and …, 2024"],"snippet":"Background Pharmacy practice faculty research profiles extend beyond the clinical and social domains, which are core elements of pharmacy practice. But as highlighted by journal editors in the Granada Statements, there is no consensus on …","url":["https://www.sciencedirect.com/science/article/pii/S1551741124003875"]}
{"year":"2024","title":"A Digital Tool for Scaffolding Innovation Learning in Engineering Education with Local Industry Needs","authors":["K KUNRATH, S LEKA, LS VESTERGAARD…"],"snippet":"… We used a pre-trained English model trained on data from the websites Common Crawl and Wikipedia using a continuous bag of words (CBOW) in 300 dimensions [38]. Using cosine metric, we then utilized t-distributed stochastic neighbor embedding (t-SNE) …","url":["https://www.researchgate.net/profile/Devarajan-Ramanujan/publication/384767424_A_Digital_Tool_for_Scaffolding_Innovation_Learning_in_Engineering_Education_with_Local_Industry_Needs/links/6706eb68ffe5b728123df84f/A-Digital-Tool-for-Scaffolding-Innovation-Learning-in-Engineering-Education-with-Local-Industry-Needs.pdf"]}
{"year":"2024","title":"A Federated Approach to Few-Shot Hate Speech Detection for Marginalized Communities","authors":["H Ye, A Wisiorek, A Maronikolakis, Ö Alaçam… - arXiv preprint arXiv …, 2024"],"snippet":"Hate speech online remains an understudied issue for marginalized communities, and has seen rising relevance, especially in the Global South, which includes developing societies with increasing internet penetration. In this paper, we aim to …","url":["https://arxiv.org/pdf/2412.04942"]}
{"year":"2024","title":"A field guide to using LLMs for online conflict analysis","authors":["E Borra, P Bollini, L Caroleo, B Cerigo, R Dubèl, F Gaw…"],"snippet":"… Two ways in which we studied LLMs was by looking at some of their open-source datasets, which one can sift through in WebText2, CommonCrawl and Wikipedia. Another is by studying autocompletions as perpetuations of standardized knowledge …","url":["https://www.digitalmethods.net/Dmi/FieldGuideToUsingLLMs"]}
{"year":"2024","title":"A fine-tuned multimodal large model for power defect image-text question-answering","authors":["Q Wang, J Zhang, J Du, K Zhang, R Li, F Zhao, L Zou… - Signal, Image and Video …, 2024"],"snippet":"In power defect detection, the complexity of scenes and the diversity of defects pose challenges for manual defect identification. Considering these issues, this paper proposes utilizing a multimodal large model to assist power professionals in …","url":["https://link.springer.com/article/10.1007/s11760-024-03539-w"]}
{"year":"2024","title":"A Framework for Applying Copyright Law to the Training of Textual Generative Artificial Intelligence.","authors":["A Neill, J Thomas, E Lee - Texas Intellectual Property Law Journal, 2024"],"snippet":"… Websites are not notified when Common Crawl scrapes their data, but they can opt out by configuring a specific site to block the crawler.46 The second corpora used, WebText2, is an expanded version of WebText and utilizes a similar parameter for …","url":["https://search.ebscohost.com/login.aspx?direct=true&profile=ehost&scope=site&authtype=crawler&jrnl=10681000&AN=178668895&h=ONPvqRBoIa4oizVtMtYHrrGGTVrBJPiftDIO344Y1f0BqgqX%2F06mvi1jEeu8Mlj5Em6%2FD0%2B0o3L%2BUmSqi2hu0A%3D%3D&crl=c"]}
{"year":"2024","title":"A Framework for Embedding Entities in a Textual Narrative: a Case Study on Les Misérables","authors":["G Guex - 2023"],"snippet":"In this article, we propose a general and flexible framework in order to study narrative entities found in a literary work. This framework is exposed starting from a broad perspective, consisting in how to segment the work into textual units and …","url":["https://ceur-ws.org/Vol-3602/paper4.pdf"]}
{"year":"2024","title":"A Framework for Preparing a Balanced and Comprehensive Phishing Dataset","authors":["I Skula, M Kvet - IEEE Access, 2024"],"snippet":"… • Choon Lin Tan (2018) [19] - dataset contains 5000 legitimate records sourced from Alexa and Common Crawl and 5000 phishing records from PhishTank and … Common Crawl (commoncrawl.org)- is a humongous web archive collected by …","url":["https://ieeexplore.ieee.org/iel7/6287639/6514899/10497090.pdf"]}
{"year":"2024","title":"A Framework to Construct Financial Causality Knowledge Graph from Text","authors":["Z Xu, H Takamura, R Ichise - 2024 IEEE 18th International Conference on Semantic …, 2024"],"snippet":"Causality analysis holds a prominent role in finance, and the presentation of causality could offer valuable insights for risk mitigation, investment decisions, and portfolio optimization. Recent research has extensively investigated the identification …","url":["https://www.computer.org/csdl/proceedings-article/icsc/2024/853500a057/1Vwkcfe9osw"]}
{"year":"2024","title":"A Galician Corpus for Misogyny Detection Online","authors":["LM Álvarez-Crespo, LM Castro - Proceedings of the 16th International Conference on …, 2024"],"snippet":"Social networks are virtual spaces where millions of people share ideas, opinions, and experiences. However, this broad social interaction also exposes negative and harmful behaviors, such as harassment and misogyny. Misogyny, particularly, is a …","url":["https://aclanthology.org/2024.propor-1.3.pdf"]}
{"year":"2024","title":"A Generalize Hardware Debugging Approach for Large Language Models Semi-Syntectic Datasets","authors":["W Fu, S Li, Y Zhao, K Yang, X Zhang, Y Jin, X Guo"],"snippet":"… C4 specifically employs the Common Crawl [44] dataset, focusing on deduplication, removing non-English content, and filtering out offensive language. Redpajama combines sources from Wikipedia and StackExchange, similar to C4 …","url":["https://www.techrxiv.org/doi/pdf/10.36227/techrxiv.171527592.25632661"]}
{"year":"2024","title":"A Generative Transformer-Based Approach to Automated Essay Scoring: Evaluating GPT-2's Performance with Pre-and Post-Data Augmentation","authors":["A Gunduz - 2024"],"snippet":"Recent advancements in artificial intelligence and language modeling have revolutionized the domain of educational technology, with a special focus on the utility of automated essay scoring (AES) systems. The potential of GPT-based model …","url":["https://era.library.ualberta.ca/items/9a992075-916c-4c66-983b-3836642ff9dc/download/e1334151-bf7c-4e09-8242-ad012ff0e556"]}
{"year":"2024","title":"A global matching model of choice and response times in the Deese-Roediger-McDermott semantic and perceptual false recognition paradigms","authors":["AF Osth, L Zhang, S Williams, A Osth"],"snippet":"… We used the pre-trained vectors from the fasttext library that were trained on the Common Crawl corpus (Grave, Bojanowski, Gupta, Joulin, & Mikolov, 2018)3. The word2vec model is considered the state-of-the-art semantic space model in its ability …","url":["https://osf.io/6mrux/download"]}
{"year":"2024","title":"A Graph-Based Synthetic Data Pipeline for Scaling High-Quality Reasoning Instructions","authors":["J Wang, J Xu, X Wang, Y Wang, M Xing, S Fang… - arXiv preprint arXiv …, 2024"],"snippet":"Synthesizing high-quality reasoning data for continual training has been proven to be effective in enhancing the performance of Large Language Models (LLMs). However, previous synthetic approaches struggle to easily scale up data and incur …","url":["https://arxiv.org/pdf/2412.08864"]}
{"year":"2024","title":"A Hierarchical Context Augmentation Method to Improve Retrieval-Augmented LLMs on Scientific Papers","authors":["TY Che, XL Mao, T Lan, H Huang - Proceedings of the 30th ACM SIGKDD Conference …, 2024"],"snippet":"… C𝑝𝑟𝑒𝑡𝑟𝑎𝑖𝑛 = C𝑠𝑐𝑖 ∪ C𝑎𝑢𝑔 ∪ C𝑔𝑒𝑛𝑒𝑟𝑎𝑙 (2) where C𝑠𝑐𝑖 is the previous scientific papers and C𝑔𝑒𝑛𝑒𝑟𝑎𝑙 is the general corpus such as CommonCrawl. The mixed dataset will be used to continue pretraining the language …","url":["https://dl.acm.org/doi/abs/10.1145/3637528.3671847"]}
{"year":"2024","title":"A Holistic Review on Detection of Malicious Browser Extensions and Links using Deep Learning","authors":["T Zonta, M Sathiyanarayanan - 2024 IEEE 3rd International Conference on AI in …, 2024"],"snippet":"… Common Crawl [36] is a website which crawls over the web and suggest many datasets of legitimate website and their metadata namely … Available: https://commoncrawl.or g/2021/10/september-2021-crawlarchive-now-available/ [37] AC Bahnsen, EC …","url":["https://ieeexplore.ieee.org/abstract/document/10433842/"]}
{"year":"2024","title":"A Hybrid Deep BiLSTM-CNN for Hate Speech Detection in Multi-social media","authors":["A Kumar, S Kumar, K Passi, A Mahanti - ACM Transactions on Asian and Low …, 2024"],"snippet":"Nowadays, ways of communication among people have changed due to advancements in information technology and the rise of online multi-social media. Many people express their feelings, ideas, and emotions on social media sites such …","url":["https://dl.acm.org/doi/pdf/10.1145/3657635"]}
{"year":"2024","title":"A Hybrid DGA DefenseNet for Detecting DGA Domain Names based on FastText and Deep Learning Techniques","authors":["JL Chen, JF Qiu, YH Chen - Computers & Security, 2024"],"snippet":"As technology rapidly advances, the Internet has become an essential part of modern life. However, public awareness of cybersecurity has not kept pace with the growing threat landscape. Cyber incidents have become more frequent, caused by …","url":["https://www.sciencedirect.com/science/article/pii/S0167404824005388"]}
{"year":"2024","title":"A Hybrid Framework for Improved Weighted Quantum Particle Swarm Optimization and Fast Mask Recurrent CNN to Enhance Phishing-URL Prediction Performance","authors":["SS Kumar, P Muthusamy, MPA Jerald - International Journal of Computational …, 2024"],"snippet":"Phishing websites are cybercrimes that aim to collect confidential data, including bank card numbers, bank accounts, and credentials. To detect phishing sites, specialists must extract the elements of the websites and utilize third-party resources …","url":["https://link.springer.com/article/10.1007/s44196-024-00663-w"]}
{"year":"2024","title":"A Japanese-Chinese Parallel Corpus Using Crowdsourcing for Web Mining","authors":["M Nagata, M Morishita, K Chousa, N Yasuda - arXiv preprint arXiv:2405.09017, 2024"],"snippet":"… In ParaCrawl, they determine which websites to crawl by analyzing the Common Crawl … In this study, we analyzed 12 sets of Common Crawl archives (104TB in total) published from … and bilingual website URLs obtained from Common Crawl …","url":["https://arxiv.org/pdf/2405.09017"]}
{"year":"2024","title":"A Language Model Trained on Uruguayan Spanish News Text","authors":["JP Filevich, G Marco, S Castro, L Chiruzzo, A Rosá - LREC-COLING 2024, 2024"],"snippet":"This paper presents a language model trained from scratch exclusively on a brand new corpus consisting of about 6 GiB of Uruguayan newspaper text. We trained the model for 30 days on a single Nvidia P100 using the RoBERTa-base architecture …","url":["https://www.iris.unina.it/retrieve/684d559a-e9e4-4eb1-8a80-4a3d654fc7f2/book.v3%20LATEST.pdf#page=63"]}
{"year":"2024","title":"A Large-Scale Exploration of $\\mu $-Transfer","authors":["L Lingle - arXiv preprint arXiv:2404.05728, 2024"],"snippet":"Large neural network models have become a mainstay of natural language processing and computer vision, yet their initialization and learning rates are set in a largely heuristic fashion, potentially varying from paper to paper and one model size …","url":["https://arxiv.org/html/2404.05728v1"]}
{"year":"2024","title":"A Lean Dataset for International Math Olympiad: Small Steps towards Writing Math Proofs for Hard Problems","authors":["R Yousefzadeh, X Cao - arXiv preprint arXiv:2411.18872, 2024"],"snippet":"… trained on Common Crawl or fine tuned from a model that was previously trained on Common Crawl. Although the GPT-4 training set is kept as a secret, we know that previous iterations of this model, such as the GPT-f model, were trained on the …","url":["https://arxiv.org/pdf/2411.18872"]}
{"year":"2024","title":"A Legal Framework for Natural Language Model Training in Portugal","authors":["R Almeida, E Amorim - Proceedings of the Workshop on Legal and Ethical …, 2024"],"snippet":"Recent advances in deep learning have promoted the advent of many computational systems capable of performing intelligent actions that, until then, were restricted to the human intellect. In the particular case of human languages, these …","url":["https://aclanthology.org/2024.legal-1.2.pdf"]}
{"year":"2024","title":"A Legal Framework for Natural Language Processing Model Training in Portugal","authors":["R Almeida, E Amorim - arXiv preprint arXiv:2405.00536, 2024"],"snippet":"Recent advances in deep learning have promoted the advent of many computational systems capable of performing intelligent actions that, until then, were restricted to the human intellect. In the particular case of human languages, these …","url":["https://arxiv.org/pdf/2405.00536"]}
{"year":"2024","title":"A Little Leak Will Sink a Great Ship: Survey of Transparency for Large Language Models from Start to Finish","authors":["M Kaneko, T Baldwin - arXiv preprint arXiv:2403.16139, 2024"],"snippet":"… The most common sources included in all LLMs are web page sources such as C4, CommonCrawl, and the Pile. Because they are collected from various web pages, there is a risk that they may contain personal information, copyrighted texts …","url":["https://arxiv.org/pdf/2403.16139"]}
{"year":"2024","title":"A Longitudinal Study of Content Control Mechanisms","authors":["M Dinzinger, M Granitzer - Companion Proceedings of the ACM on Web …, 2024"],"snippet":"… Both resources, robots.txt and regular pages, were collected from the Common Crawl web archive 7 and processed through a customized … As Common Crawl is furhtermore not focused on particular web domains, but randomly samples the …","url":["https://dl.acm.org/doi/abs/10.1145/3589335.3651893"]}
{"year":"2024","title":"A Method for Building Large Language Models with Predefined KV Cache Capacity","authors":["Z Yi, G Niu, L Wang, W Tang, L Zhang - arXiv preprint arXiv:2411.15785, 2024"],"snippet":"This paper proposes a method for building large language models with predefined Key-Value (KV) cache capacity, particularly suitable for the attention layers in Transformer decode-only architectures. This method introduces fixed-length KV …","url":["https://arxiv.org/pdf/2411.15785"]}
{"year":"2024","title":"A methodology for using players' chat content for dynamic difficulty adjustment in metaverse multiplayer games","authors":["MM Rezapour, A Fatemi, MA Nematbakhsh - Applied Soft Computing, 2024"],"snippet":"… RoBERTa, on the other hand, was trained on a much larger corpus of text that includes not only Wikipedia and BookCorpus but also Common Crawl, a dataset that contains billions of web pages. This larger and more diverse corpus of text allows …","url":["https://www.sciencedirect.com/science/article/pii/S1568494624002710"]}
{"year":"2024","title":"A multi-level multi-label text classification dataset of 19th century Ottoman and Russian literary and critical texts","authors":["G Gokceoglu, D Cavusoglu, E Akbas, ÖN Dolcerocca - arXiv preprint arXiv …, 2024"],"snippet":"This paper introduces a multi-level, multi-label text classification dataset comprising over 3000 documents. The dataset features literary and critical texts from 19th-century Ottoman Turkish and Russian. It is the first study to apply large language models (LLMs) …","url":["https://arxiv.org/pdf/2407.15136"]}
{"year":"2024","title":"A Multilingual Dataset for Investigating Stereotypes and Negative Attitudes Towards Migrant Groups in Large Language Models","authors":["D Sorato, CC Ventura, D Zavala-Rojas - … of the 16th International Conference on …, 2024"],"snippet":"… 2020), which is a cleaned version of the CommonCrawl corpus. … where stereotypes are presented in more subtle and/or strategic ways (when compared to social media/CommonCrawl texts) and the explicit discrimination of migrant groups …","url":["https://aclanthology.org/2024.propor-1.1.pdf"]}
{"year":"2024","title":"A Multilingual Perspective on Probing Gender Bias","authors":["K Stańczak - arXiv preprint arXiv:2403.10699, 2024"],"snippet":"Gender bias represents a form of systematic negative treatment that targets individuals based on their gender. This discrimination can range from subtle sexist remarks and gendered stereotypes to outright hate speech. Prior research has …","url":["https://arxiv.org/pdf/2403.10699"]}
{"year":"2024","title":"A Natural Language Processing Approach to Support Biomedical Data Harmonization: Leveraging Large Language Models","authors":["Z Li, SP Prabhu, ZT Popp, SS Jain, V Balakundi… - arXiv preprint arXiv …, 2024"],"snippet":"Biomedical research requires large, diverse samples to produce unbiased results. Automated methods for matching variables across datasets can accelerate this process. Research in this area has been limited, primarily focusing on lexical …","url":["https://arxiv.org/pdf/2411.02730"]}
{"year":"2024","title":"A Neurodynamic-diversity-based Spiking Network model for Text Classification","authors":["Y Liu, W Chen, H Liu, Y Zhang, M Zhang, H Qu - IEEE Transactions on Cognitive and …, 2024"],"snippet":"… In our experiment, we use the pretrained GloVe5(”Common Crawl” version with 2.2M vocabulary) for English words, and a Chinese-version Word2Vec6(trained from Baidu Encyclopedia with 634k vocabulary) for Chinese words. Chinese text is …","url":["https://ieeexplore.ieee.org/abstract/document/10817539/"]}
{"year":"2024","title":"A New Massive Multilingual Dataset for High-Performance Language Technologies","authors":["O de Gibert, G Nail, N Arefyev, M Bañón… - arXiv preprint arXiv …, 2024"],"snippet":"We present the HPLT (High Performance Language Technologies) language resources, a new massive multilingual dataset including both monolingual and bilingual corpora extracted from CommonCrawl and previously unused web crawls …","url":["https://arxiv.org/pdf/2403.14009"]}
{"year":"2024","title":"A New Method for Cross-Lingual-based Semantic Role Labeling","authors":["M Ebrahimi, BM Bidgoli, N Khozouei - arXiv preprint arXiv:2408.15896, 2024"],"snippet":"… It has received specialized training using 2.5 terabytes of meticulously processed CommonCrawl data, which includes text from 100 different languages. RoBERTa itself is a transformer-based model that has been pre-trained in a self-supervised …","url":["https://arxiv.org/pdf/2408.15896"]}
{"year":"2024","title":"A New Type of Foundation Model Based on Recordings of People's Emotions and Physiology","authors":["D Gamez, D Barcari, A Grig - arXiv preprint arXiv:2408.00030, 2024"],"snippet":"… These models are trained on large amounts of text and image data scraped from the Internet - often accessed through the Common Crawl repository. Researchers and technology companies are starting to realize that this data source could become …","url":["https://arxiv.org/pdf/2408.00030"]}
{"year":"2024","title":"A News Media Bias and Factuality Profiling Framework Assisted by Modeling Correlation","authors":["Q Wang, C Li, C Lin, W Fan, S Feng, Y Wang - 2024"],"snippet":"… They constructed a larger dataset based on news published by Common Crawl and merged ground-truth labels from different sources. Hounsel et al. [28] explored techniques for detecting disinformation websites by analyzing various infrastructure …","url":["https://cdn.techscience.cn/files/cmc/2024/online/CMC1031/TSP_CMC_57191/TSP_CMC_57191.pdf"]}
{"year":"2024","title":"A Novel Approach in Financial Fraud Detection: Addressing Data Imbalance With Prompt Engineering, Leveraging Large Language Model Embeddings for Fraud …","authors":["J Lin - 2025"],"snippet":"This research examines novel methodologies that leverage large language models (LLMs) for synthetic data generation and embedding tasks to enhance the effectiveness of financial fraud detection. The study also introduces an optimized approach for …","url":["https://search.proquest.com/openview/a19456f894a6db95b8b0f1da24d07c04/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
{"year":"2024","title":"A Novel Hashcode-based Duplication Reduction via Thresholding Approach for Large-scale Web Documents","authors":["S Ejaz, A Naseer, S Naz - 2024"],"snippet":"Modern search engines encounter a significant challenge when it comes to handling duplicate and nearly identical web pages, particularly during the indexing process for vast amounts of web content. This issue can lead to slow search results and …","url":["https://www.preprints.org/manuscript/202408.0443/download/final_file"]}
{"year":"2024","title":"A Permutaion Importance Based feature selection method and Deep Learning Model to Detect Phishing Websites","authors":["R Zaimi, M Hafidi, L Mahnane - 2024"],"snippet":"Phishing attacks pose a significant and escalating threat to cybersecurity in recent times. This deceptive scam aims to trick naive users, luring them into visiting harmful websites and sharing sensitive information, including credentials, credit card …","url":["https://www.researchsquare.com/article/rs-3943049/latest.pdf"]}
{"year":"2024","title":"A phenomenology and epistemology of large language models: Transparency, trust, and trustworthiness","authors":["R Heersmink, B de Rooij, MJC Vázquez, M Colombo"],"snippet":"… We know that its dataset includes the Common Crawl, which is a publicly available corpus of Webpages, including billions of Webpages … whether sources in the Common Crawl or Wikipedia are prioritised. This is again a serious issue to do …","url":["https://philpapers.org/archive/HEEAPA.pdf"]}
{"year":"2024","title":"A Pointer Network-based Approach for Joint Extraction and Detection of Multi-Label Multi-Class Intents","authors":["A Mullick, S Bose, A Nandy, GS Chaitanya, P Goyal - arXiv preprint arXiv:2410.22476, 2024"],"snippet":"In task-oriented dialogue systems, intent detection is crucial for interpreting user queries and providing appropriate responses. Existing research primarily addresses simple queries with a single intent, lacking effective systems for handling complex …","url":["https://arxiv.org/pdf/2410.22476"]}
{"year":"2024","title":"A Practical and Privacy-Preserving Framework for Real-World Large Language Model Services","authors":["Y Mao, X Liao, W Liu, A Yang - arXiv preprint arXiv:2411.01471, 2024"],"snippet":"… For example, the August 2024 CommonCrawl dataset comprises 2.30 billion web pages 3. GPT-3 was pre-trained on a mix of datasets, including filtered CommonCrawl data and Wikipedia, comprising approximately 300 billion tokens [18] …","url":["https://arxiv.org/pdf/2411.01471"]}
{"year":"2024","title":"A Quantitative Investigation of Graduate Student Perceptions of Human-Generated and AI-Generated Reviews in a Cyber-Social Learning Platform","authors":["C Hughes, AO Tzirides, AK Saini - Trust and Inclusion in AI-Mediated Education …, 2024"],"snippet":"… Text is obtained from the non-profit Common Crawl (which scrapes text from webpages and provides datasets free of charge), WebText2 (which draws on text found on the popular community forum hosting site Reddit), Books 1 & 2 (Internet-based …","url":["https://link.springer.com/chapter/10.1007/978-3-031-64487-0_10"]}
{"year":"2024","title":"A Quantitative Investigation of Graduate Student Perceptions of Human-Generated","authors":["C Hughes, D Anastasia-Olga Olnancy Tzirides - Trust and Inclusion in AI-Mediated …"],"snippet":"This paper is presented in the context of increasing fervent discussions around the influence of Artificial Intelligence (AI) on society at large. A prominent catalyst for these discussions is Open AI's Chat Generative Pre-Trained Transformer (OpenAI …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=oAElEQAAQBAJ&oi=fnd&pg=PA213&dq=commoncrawl&ots=6PR5GrIvOY&sig=g8BqoiU_zPwM00pLtudr9bw93Yc"]}
{"year":"2024","title":"A Review of Current Trends, Techniques, and Challenges in Large Language Models (LLMs)","authors":["R Patil, V Gudivada - 2024"],"snippet":"… For low-resource languages, XLM models trained on CommonCrawl-100 did better than the ones trained using Wikipedia. Another example is mT5 [32], which uses multilingual corpus mC4 to pretrain the model. When dealing with multilingual …","url":["https://www.preprints.org/manuscript/202402.0357/download/final_file"]}
{"year":"2024","title":"A Review of Multi-Modal Large Language and Vision Models","authors":["K Carolan, L Fennelly, AF Smeaton - arXiv preprint arXiv:2404.01322, 2024"],"snippet":"… The Falcon LLM team created the RefinedWed dataset, which is a massive web dataset based on CommonCrawl. TII focused on scaling and improving the quality of web data by employing large-scale de-duplication and strict filtering, resulting in …","url":["https://arxiv.org/pdf/2404.01322"]}
{"year":"2024","title":"A review of multimodal-based emotion recognition techniques for cyberbullying detection in online social media platforms","authors":["S Wang, AS Shibghatullah, TJ Iqbal, KH Keoy - Neural Computing and Applications, 2024"],"snippet":"Cyberbullying is a serious issue in online social media platforms (OSMP), which requires effective detection and intervention systems. Multimodal emotion recognition (MER) technology can help prevent cyberbullying by analyzing emotions …","url":["https://link.springer.com/article/10.1007/s00521-024-10371-3"]}
{"year":"2024","title":"A Review of the Challenges with Massive Web-mined Corpora Used in Large Language Models Pre-Training","authors":["M Perełkiewicz, R Poświata - arXiv preprint arXiv:2407.07630, 2024"],"snippet":"… Common Crawl is an open repository of web crawl data collected over years. The Common Crawl repository provides around 20TB of scraped … Due to the wide coverage of diverse domains and languages, as well as the size of the collected data …","url":["https://arxiv.org/pdf/2407.07630"]}
{"year":"2024","title":"A Review of the Marathi Natural Language Processing","authors":["A Dani, SR Sathe - arXiv preprint arXiv:2412.15471, 2024"],"snippet":"… 2019) are large-scale multilingual text corpora extracted from Common Crawl web data5. They are designed to support natural language processing (NLP) and linguistic research for a wide range of languages. The OSCAR project aims to …","url":["https://arxiv.org/pdf/2412.15471"]}
{"year":"2024","title":"A review on emotion detection by using deep learning techniques","authors":["T Chutia, N Baruah - Artificial Intelligence Review, 2024"],"snippet":"Along with the growth of Internet with its numerous potential applications and diverse fields, artificial intelligence (AI) and sentiment analysis (SA) have become significant and popular research areas. Additionally, it was a key technology that …","url":["https://link.springer.com/article/10.1007/s10462-024-10831-1"]}
{"year":"2024","title":"A Robust Approach to E-Banking Phishing Detection using Ensemble Methods and LSTM","authors":["NVS Reddy, ARR Saai, TV Ramanujan, NRK Reddy… - … International Conference on …, 2024"],"snippet":"… range of datasets from reputable community platforms like VirusTotal, Common Crawl, and PhishTank. This extensive dataset, spanning … Integration of Common Crawl further enriched the dataset, ensuring a diverse set of websites for effective …","url":["https://ieeexplore.ieee.org/abstract/document/10533883/"]}
{"year":"2024","title":"A robust hybrid approach with product context-aware learning and explainable AI for sentiment analysis in Amazon user reviews","authors":["E Hashmi, SY Yayilgan - Electronic Commerce Research, 2024"],"snippet":"… FastText, Footnote 5 a word representation library developed by the Facebook research team, encompasses a repository of 2 million common crawl words with 300 dimensions, resulting in a vast collection of 600 billion word vectors. Distinguished …","url":["https://link.springer.com/article/10.1007/s10660-024-09896-5"]}
{"year":"2024","title":"A Semantic Framework for Modular Knowledge Integration in Large Language Models","authors":["K Etlune, S Richardson, M Howard, B Foster, R Russell… - 2024"],"snippet":"… General language understanding was addressed through datasets such as the Common Crawl corpus, providing extensive textual data across multiple topics. Domain-specific knowledge was incorporated using specialized datasets, including …","url":["https://www.authorea.com/doi/pdf/10.22541/au.173222145.59075557"]}
{"year":"2024","title":"A Shocking Amount of the Web is Machine Translated: Insights from Multi-Way Parallelism","authors":["B Thompson, MP Dhaliwal, P Frisch, T Domhan… - arXiv preprint arXiv …, 2024"],"snippet":"… 2021), which is in turn based on Common CrawlCommon Crawl is a long running web-scraping project which maintains a free, open source repository of web-scraped data. ccMatrix is created by embedding Common Crawl sentences into a …","url":["https://arxiv.org/pdf/2401.05749"]}
{"year":"2024","title":"A Short Commentary on Trinh & Le (2018)","authors":["WS SABA"],"snippet":"… corpus (trained on the language model LM-1-Billion, CommonCrawl, and SQuAD), the probabilities of s1 and s2 appearing in a large corpus. The substitution that turns out to be more probable, is considered to be the more probable referent of “it”. There …","url":["https://www.academia.edu/download/108648524/1810.00521.pdf"]}
{"year":"2024","title":"A State-of-the-art Review on Phishing Website Detection Techniques","authors":["W Li, S Manickam, YW Chong, W Leng, P Nanda - IEEE Access, 2024"],"snippet":"Phishing attacks remain a significant cybersecurity threat, with phishing websites serving as a primary tool for attackers to deceive users and steal sensitive information. The rapid evolution of phishing tactics has spurred the development of …","url":["https://ieeexplore.ieee.org/iel8/6287639/6514899/10788671.pdf"]}
{"year":"2024","title":"A Study of Aging Through Speech and Language Analysis","authors":["Y Yin - 2024"],"snippet":"Speech is a promising biomarker for cognitive impairment and dementing illness. Compared to traditional biomarkers, digital biomarkers are often less invasive, cheaper to measure, and require less instruction. They also allow continuous and …","url":["https://search.proquest.com/openview/720752c5465b608e7046053724743ad6/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
{"year":"2024","title":"A support system for the detection of abusive clauses in B2C contracts","authors":["S Dadas, M Kozłowski, R Poświata, M Perełkiewicz… - Artificial Intelligence and …, 2024"],"snippet":"… To better balance our dataset, we retrieved an additional 7547 safe clauses from Polish CommonCrawl Footnote 15 dumps using weak supervision techniques. Our approach involved scanning approximately 100 GB of Polish web pages and …","url":["https://link.springer.com/article/10.1007/s10506-024-09408-8"]}
{"year":"2024","title":"A Survey of AI-Generated Content (AIGC)","authors":["Y Cao, S Li, Y Liu, Z Yan, Y Dai, P Yu, L Sun - ACM Computing Surveys, 2024"],"snippet":"Recently, Artificial Intelligence Generated Content (AIGC) has gained significant attention from society, especially with the rise of Generative AI (GAI) techniques such as ChatGPT, GPT-4 [165], DALL-E-3 [184], and Sora [137]. AIGC involves using AI …","url":["https://dl.acm.org/doi/pdf/10.1145/3704262"]}
{"year":"2024","title":"A Survey of AI-generated Text Forensic Systems: Detection, Attribution, and Characterization","authors":["T Kumarage, G Agrawal, P Sheth, R Moraffah… - arXiv preprint arXiv …, 2024"],"snippet":"We have witnessed lately a rapid proliferation of advanced Large Language Models (LLMs) capable of generating high-quality text. While these LLMs have revolutionized text generation across various domains, they also pose significant …","url":["https://arxiv.org/pdf/2403.01152"]}
{"year":"2024","title":"A Survey of Conversational Styles and Systems","authors":["R Nagpal, S Fatty, DG Brizan - 2024 16th International Conference on Human …, 2024"],"snippet":"Conversational systems are an emerging area in natural language processing. This survey paper provides a comprehensive overview of architectures, methods, and datasets used to design the development of conversational agents. We have …","url":["https://ieeexplore.ieee.org/abstract/document/10613569/"]}
{"year":"2024","title":"A Survey of Large Language Models for Arabic Language and its Dialects","authors":["M Mashaabi, S Al-Khalifa, H Al-Khalifa - arXiv preprint arXiv:2410.20238, 2024"],"snippet":"This survey offers a comprehensive overview of Large Language Models (LLMs) designed for Arabic language and its dialects. It covers key architectures, including encoder-only, decoder-only, and encoder-decoder models, along with the datasets …","url":["https://arxiv.org/pdf/2410.20238"]}
{"year":"2024","title":"A Survey of Large Language Models for European Languages","authors":["W Ali, S Pyysalo"],"snippet":"… The OSCAR [122] corpus is a large multilingual text dataset extracted from Common Crawl (CC). The German subset of OSCAR is particularly noteworthy, measuring 496.7GB in size and containing approximately 7 billion documents and …","url":["https://www.researchgate.net/profile/Wazir-Ali-6/publication/382143159_A_Survey_of_Large_Language_Models_for_European_Languages/links/668ef7e3af9e615a15dde778/A-Survey-of-Large-Language-Models-for-European-Languages.pdf"]}
{"year":"2024","title":"A Survey of Low-bit Large Language Models: Basics, Systems, and Algorithms","authors":["R Gong, Y Ding, Z Wang, C Lv, X Zheng, J Du, H Qin… - arXiv preprint arXiv …, 2024"],"snippet":"Large language models (LLMs) have achieved remarkable advancements in natural language processing, showcasing exceptional performance across various tasks. However, the expensive memory and computational requirements present …","url":["https://arxiv.org/pdf/2409.16694"]}
{"year":"2024","title":"A Survey of Multimodal Large Language Model from A Data-centric Perspective","authors":["T Bai, H Liang, B Wan, L Yang, B Li, Y Wang, B Cui… - arXiv preprint arXiv …, 2024"],"snippet":"… CommonCrawl project serves as the most commonly … , CommonCrawl’s vast archive of web pages, which includes numerous image-text pairs, has also become a vital resource for constructing multimodal pre-training datasets such as LAION-5B [236] …","url":["https://arxiv.org/pdf/2405.16640"]}
{"year":"2024","title":"A Survey of Neural Machine Translation based on Knowledge Distillation","authors":["MA Chang, T Yonghong, Z Xiaoli, SUN Kangkang - Journal of Frontiers of Computer Science …"],"snippet":"Abstract: Machine Translation (MT) is the process of using a computer to convert a language into another language with the same semantics. With the introduction of neural network, neural machine translation (NMT), as a powerful machine …","url":["http://fcst.ceaj.org/EN/article/downloadArticleFile.do?attachType=PDF&id=3451"]}
{"year":"2024","title":"A survey of neural-network-based methods utilising comparable data for finding translation equivalents","authors":["M Denisová, P Rychlý - arXiv preprint arXiv:2410.15144, 2024"],"snippet":"… On the contrary, mBART is multilingual BART trained on non-aligned multilingual (Common Crawl web corpus)2 and parallel corpus for 24 language pairs (mainly in the public domain), including German, Chinese, Finnish, Estonian, Romanian, etc., all paired …","url":["https://arxiv.org/pdf/2410.15144"]}
{"year":"2024","title":"A Survey of Resource-efficient LLM and Multimodal Foundation Models","authors":["M Xu, W Yin, D Cai, R Yi, D Xu, Q Wang, B Wu, Y Zhao… - arXiv preprint arXiv …, 2024"],"snippet":"Large foundation models, including large language models (LLMs), vision transformers (ViTs), diffusion, and LLM-based multimodal models, are revolutionizing the entire machine learning lifecycle, from training to deployment …","url":["https://arxiv.org/pdf/2401.08092"]}
{"year":"2024","title":"A Survey of Web Content Control for Generative AI","authors":["M Dinzinger, F Heß, M Granitzer - arXiv preprint arXiv:2404.02309, 2024"],"snippet":"… The documents were sourced from the web archive of Common Crawl,16 offering a broad and randomly selected cross-section of the internet. These files were all collected in November and December 2023. Further details on the experimental …","url":["https://arxiv.org/pdf/2404.02309"]}
{"year":"2024","title":"A Survey on Automatic Online Hate Speech Detection in Low-Resource Languages","authors":["S Das, A Dutta, K Roy, A Mondal, A Mukhopadhyay - arXiv preprint arXiv:2411.19017, 2024"],"snippet":"The expanding influence of social media platforms over the past decade has impacted the way people communicate. The level of obscurity provided by social media and easy accessibility of the internet has facilitated the spread of hate speech …","url":["https://arxiv.org/pdf/2411.19017"]}
{"year":"2024","title":"A Survey on Data Selection for Language Models","authors":["A Albalak, Y Elazar, SM Xie, S Longpre, N Lambert… - arXiv preprint arXiv …, 2024"],"snippet":"… They train a classifier using the “high-quality” reference corpora as the positive class and unfiltered Common Crawl documents as the negative class. This classifier then defines the utility metric for selecting data that follows the desired distribution …","url":["https://arxiv.org/pdf/2402.16827"]}
{"year":"2024","title":"A Survey on Large Language Models with Multilingualism: Recent Advances and New Frontiers","authors":["K Huang, F Mo, H Li, Y Li, Y Zhang, W Yi, Y Mao, J Liu… - arXiv preprint arXiv …, 2024"],"snippet":"The rapid development of Large Language Models (LLMs) demonstrates remarkable multilingual capabilities in natural language processing, attracting global attention in both academia and industry. To mitigate potential discrimination …","url":["https://arxiv.org/pdf/2405.10936"]}
{"year":"2024","title":"A Survey on LLMs: Evolution, Applications, and Future Frontiers","authors":["K Harsha, KT Kumar, D Sumathi, EA Jubilson - Generative AI: Current Trends and …"],"snippet":"… The T5 model’s multilingual counterpart, mT5, expands upon its capabilities by being pre-trained on a new and extensive Common Crawl-… It was trained on a sizable Common Crawl corpus that included texts in 101 different languages in …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=eec2EQAAQBAJ&oi=fnd&pg=PA289&dq=commoncrawl&ots=lZ4Ux7keh3&sig=gP3FcOLgDb3ktIOjQ2ujW1EG-_U"]}
{"year":"2024","title":"A Survey on Multilingual Large Language Models: Corpora, Alignment, and Bias","authors":["Y Xu, L Hu, J Zhao, Z Qiu, Y Ye, H Gu - arXiv preprint arXiv:2404.00929, 2024"],"snippet":"… A significant portion of these training data originates from multilingual repositories like Common Crawl, WikiPedia and Web documents, encompassing a broad range of languages. These multilingual repositories are crucial for enhancing the cross-lingual …","url":["https://arxiv.org/pdf/2404.00929"]}
{"year":"2024","title":"A survey on recent advances in named entity recognition","authors":["I Keraghel, S Morbieu, M Nadif - arXiv preprint arXiv:2401.10825, 2024"],"snippet":"Named Entity Recognition seeks to extract substrings within a text that name real-world objects and to determine their type (for example, whether they refer to persons or organizations). In this survey, we first present an overview of recent popular …","url":["https://arxiv.org/pdf/2401.10825"]}
{"year":"2024","title":"A Survey on the Use of Large Language Models (LLMs) in Fake News","authors":["E Papageorgiou, C Chronis, I Varlamis, Y Himeur - Future Internet, 2024"],"snippet":"… It was trained on the Colossal Clean Crawled Corpus (C4) dataset, a 750 GB dataset created from Common Crawl’s web-extracted text. The model architecture is similar to the original … It was trained on the RealNews dataset, created from …","url":["https://www.mdpi.com/1999-5903/16/8/298"]}
{"year":"2024","title":"A systematic review of multidimensional relevance estimation in information retrieval","authors":["G Peikos, G Pasi - Wiley Interdisciplinary Reviews: Data Mining and …"],"snippet":"In information retrieval, relevance is perceived as a multidimensional and dynamic concept influenced by user, task, and domain factors. Relying on this perspective, researchers have introduced multidimensional relevance models addressing …","url":["https://wires.onlinelibrary.wiley.com/doi/abs/10.1002/widm.1541"]}
{"year":"2024","title":"A Systematic Study of the Role of Data Quality and Alignment for Fine-tuning LLMs for Enhanced Autoformalization","authors":["K Chawla, A Sahai, M DePavia, B Miranda - The Second Tiny Papers Track at ICLR 2024"],"snippet":"This study explores the role of data quality, particularly alignment, in fine-tuning Large Language Models (LLMs) for the task of autoformalization. Contrary to the conventional emphasis on dataset size, our research highlights the importance of …","url":["https://openreview.net/pdf?id=9LkPbnRwXu"]}
{"year":"2024","title":"A Systematic Survey of Text Summarization: From Statistical Methods to Large Language Models","authors":["H Zhang, PS Yu, J Zhang - arXiv preprint arXiv:2406.11289, 2024"],"snippet":"… WCEP [66] is built based on news events from Wikipedia Current Events Portal (WCEP) and similar articles in the CommonCrawl News dataset. It features high alignment with several realworld industrial use cases and has 235 articles per cluster on …","url":["https://arxiv.org/pdf/2406.11289"]}
{"year":"2024","title":"A Taxonomy of Stereotype Content in Large Language Models","authors":["G Nicolas, A Caliskan - arXiv preprint arXiv:2408.00162, 2024"],"snippet":"This study introduces a taxonomy of stereotype content in contemporary large language models (LLMs). We prompt ChatGPT 3.5, Llama 3, and Mixtral 8x7B, three powerful and widely used LLMs, for the characteristics associated with 87 social …","url":["https://arxiv.org/pdf/2408.00162"]}
{"year":"2024","title":"A Toolkit for Virtual Reality Data Collection","authors":["T Rolff, N Hypki, M Lappe, F Steinicke - arXiv preprint arXiv:2412.17490, 2024"],"snippet":"Due to the still relatively low number of users, acquiring large-scale and multidimensional virtual reality datasets remains a significant challenge. Consequently, VR datasets comparable in size to state-of-the-art collections in …","url":["https://arxiv.org/pdf/2412.17490"]}
{"year":"2024","title":"A Trustworthy Automated Short-Answer Scoring System Using a New Dataset and Hybrid Transfer Learning Method","authors":["M Maslim, HC Wang, CD Putra, YD Prabowo - 2024"],"snippet":"To measure the quality of student learning, teachers must conduct evaluations. One of the most efficient modes of evaluation is the short answer question. However, there can be inconsistencies in teacher-performed manual evaluations due to an …","url":["https://reunir.unir.net/bitstream/handle/123456789/16203/A%20Trustworthy%20Automated%20Short-Answer%20Scoring%20System%20Using%20a%20New%20Dataset%20and%20Hybrid%20Transfer%20Learning%20Method.pdf?sequence=1"]}
{"year":"2024","title":"ABCF: An Adaptive Balanced Multimodal Website Classification Framework","authors":["Z Liu, W Liu, X Tong, Q Shen, Q Zheng, H Hu, H Liu… - 2024 27th International …, 2024"],"snippet":"Websites are a crucial medium for conveying multimedia information. However, malicious websites can lurk among them, posing a threat to the security of users’ sensitive data and personal privacy. Hence, it is significant to identify and categorize …","url":["https://ieeexplore.ieee.org/abstract/document/10580593/"]}
{"year":"2024","title":"AbdomenAtlas: A Large-Scale, Detailed-Annotated, & Multi-Center Dataset for Efficient Transfer Learning and Open Algorithmic Benchmarking","authors":["W Li, C Qu, X Chen, PRAS Bassi, Y Shi, Y Lai, Q Yu… - arXiv preprint arXiv …, 2024"],"snippet":"We introduce the largest abdominal CT dataset (termed AbdomenAtlas) of 20,460 three-dimensional CT volumes sourced from 112 hospitals across diverse populations, geographies, and facilities. AbdomenAtlas provides 673K high-quality …","url":["https://arxiv.org/pdf/2407.16697"]}
{"year":"2024","title":"AboutMe: Using Self-Descriptions in Webpages to Document the Effects of English Pretraining Data Filters","authors":["L Lucy, S Gururangan, L Soldaini, E Strubell… - arXiv preprint arXiv …, 2024"],"snippet":"… From this Common Crawl data, we identify website hostnames that include an ABOUT page, which we define as URL paths containing about, aboutme, about-us, or bio (Appendix A). We then pair each ABOUT page with a random page on the …","url":["https://arxiv.org/pdf/2401.06408"]}
{"year":"2024","title":"Abusive Language Detection in Khasi Social Media Comments","authors":["A Baruah, L Wahlang, F Jyrwa, F Shadap, F Barbhuiya… - ACM Transactions on Asian …, 2024"],"snippet":"This paper describes the work performed for automated abusive language detection in the Khasi language, a low-resource language spoken primarily in the state of Meghalaya, India. A dataset named Khasi Abusive Language Dataset (KALD) was …","url":["https://dl.acm.org/doi/pdf/10.1145/3664285"]}
{"year":"2024","title":"Accelerating Large Language Model Pretraining via LFR Pedagogy: Learn, Focus, and Review","authors":["N Prakriya, JN Yen, CJ Hsieh, J Cong - arXiv preprint arXiv:2409.06131, 2024"],"snippet":"Large Language Model (LLM) pretraining traditionally relies on autoregressive language modeling on randomly sampled data blocks from web-scale datasets. We take inspiration from human learning techniques like spaced repetition to …","url":["https://arxiv.org/pdf/2409.06131"]}
{"year":"2024","title":"Accelerating Spiking Neural Networks with Parallelizable Leaky Integrate-and-Fire Neurons","authors":["SYA Yarga, SUN Wood - 2024"],"snippet":"… To achieve this, these models undergo training on massive datasets, such as the Common Crawl corpus1, which contains petabytes of textual data. Training on such extensive datasets necessitates the use of fast machine learning models like the …","url":["https://www.techrxiv.org/doi/pdf/10.36227/techrxiv.170905886.62702188"]}
{"year":"2024","title":"ACCEPTANCE OF GENERATIVE AI IN KNOWLEDGE WORK","authors":["K Koponen - 2023"],"snippet":"… The GPT-3 was trained with Corpus, a large and structured collection of texts or language data, called Common Crawl including nearly a trillion words. (Brown et al., 2020) In addition, the training set was also expanded with known high-quality …","url":["https://trepo.tuni.fi/bitstream/handle/10024/154287/KoponenKati.pdf?sequence=2"]}
{"year":"2024","title":"Accessible Foundation Models: Systems, Algorithms, and Science","authors":["T Dettmers - 2024"],"snippet":"… [Raffel et al., 2019] which is a subset of the Common Crawl corpus.We use NVIDIA A40 GPUs for this evaluation. To measure degradation in … -shot experiments, the Pearson correlation coefficient between The Pile Common Crawl …","url":["https://search.proquest.com/openview/6c8dd68b06a47574c371e521806504a7/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
{"year":"2024","title":"ACCSAMS: Automatic Conversion of Exam Documents to Accessible Learning Material for Blind and Visually Impaired","authors":["D Wilkening, O Moured, T Schwarz, K Muller… - arXiv preprint arXiv …, 2024"],"snippet":"… We collected exam materials from the Common Crawl project4, a public archive of web data. We analyzed eight datasets, released between mid 2022 and the end of 2023, extracting PDFs, which include “exam” or “klausur” as a keyword in the URL …","url":["https://arxiv.org/pdf/2405.19124"]}
{"year":"2024","title":"Accuracy of ChatGPT in Neurolocalization","authors":["WF Dabbas, YM Odeibat, M Alhazaimeh, MY Hiasat… - Cureus, 2024"],"snippet":"… The datasets used for pre-training included Common Crawl dataset, an expanded version of the WebText dataset, two internet-based books corpora (Books1 and Books2), and English-language Wikipedia [13]. …","url":["https://www.cureus.com/articles/249830-accuracy-of-chatgpt-in-neurolocalization.pdf"]}
{"year":"2024","title":"Accuracy of Large Language Models in Answering Ophthalmology Board-Style Questions: A Meta-Analysis","authors":["JH Wu, T Nishida, TYA Liu - Asia-Pacific Journal of Ophthalmology, 2024"],"snippet":"Purpose To evaluate the accuracy of large language models (LLMs) in answering ophthalmology board-style questions. Design Meta-analysis. Methods Literature search was conducted using PubMed and Embase in March 2024. We included full-length …","url":["https://www.sciencedirect.com/science/article/pii/S2162098924001178"]}
{"year":"2024","title":"AceMath: Advancing Frontier Math Reasoning with Post-Training and Reward Modeling","authors":["Z Liu, Y Chen, M Shoeybi, B Catanzaro, W Ping - arXiv preprint arXiv:2412.15084, 2024"],"snippet":"In this paper, we introduce AceMath, a suite of frontier math models that excel in solving complex math problems, along with highly effective reward models capable of evaluating generated solutions and reliably identifying the correct ones. To …","url":["https://arxiv.org/pdf/2412.15084"]}
{"year":"2024","title":"Across the Spectrum In-Depth Review AI-Based Models for Phishing Detection","authors":["S Ahmad, M Zaman, AS AL-Shamayleh, T Kehkashan… - IEEE Open Journal of the …, 2024"],"snippet":"Advancement of the Internet has increased security risks associated with data protection and online shopping. Several techniques compromise Internet security, including hacking, SQL injection, phishing attacks, and DNS tunneling. Phishing …","url":["https://ieeexplore.ieee.org/iel8/8782661/8901158/10681500.pdf"]}
{"year":"2024","title":"Active Learning for Identifying Disaster-Related Tweets: A Comparison with Keyword Filtering and Generic Fine-Tuning","authors":["D Hanny, S Schmidt, B Resch - Intelligent Systems Conference, 2024"],"snippet":"… [4] was utilised as it is pre-trained on approximately 198 million Tweets and has been shown to outperform the similar XLM-RoBERTa model trained using the more general CommonCrawl corpus [11] for the multilingual classification of Tweets. The …","url":["https://link.springer.com/chapter/10.1007/978-3-031-66428-1_8"]}
{"year":"2024","title":"Adam-mini: Use Fewer Learning Rates To Gain More","authors":["Y Zhang, C Chen, Z Li, T Ding, C Wu, Y Ye, ZQ Luo… - arXiv preprint arXiv …, 2024"],"snippet":"We propose Adam-mini, an optimizer that achieves on-par or better performance than AdamW with 45% to 50% less memory footprint. Adam-mini reduces memory by cutting down the number of learning rates in Adam: Instead of assigning an …","url":["https://arxiv.org/pdf/2406.16793"]}
{"year":"2024","title":"Adaptation of Large Language Models for Streaming Machine Translation","authors":["DK Vicente Hungerbuhler - 2024"],"snippet":"[EN] Machine translation (MT) stands as a pivotal domain within machine learning, where the rise of neural networks has sparked significant advancements, propelling MT into a highly researched field. This has been further fostered by the proliferation …","url":["https://riunet.upv.es/bitstream/handle/10251/207986/Vicente%20-%20Adaptation%20of%20Large%20Language%20Models%20for%20Streaming%20Machine%20Translation.pdf?sequence=1"]}
{"year":"2024","title":"Adapter-based Approaches to Knowledge-enhanced Language Models--A Survey","authors":["A Fichtl, J Vladika, G Groh - arXiv preprint arXiv:2411.16403, 2024"],"snippet":"Knowledge-enhanced language models (KELMs) have emerged as promising tools to bridge the gap between large-scale language models and domain-specific knowledge. KELMs can achieve higher factual accuracy and mitigate hallucinations …","url":["https://arxiv.org/pdf/2411.16403"]}
{"year":"2024","title":"Adapting LLMs to Downstream Applications","authors":["A Kucharavy - Large, 2024"],"snippet":"… The model was fed with text that generally precedes private information in a dataset used to train GPT-2—specifically the “Common Crawl” dataset to achieve a better recall. 2 With this approach, authors were not only able to extract extensive …","url":["https://link.springer.com/content/pdf/10.1007/978-3-031-54827-7.pdf#page=36"]}
{"year":"2024","title":"Adaptive Data Optimization: Dynamic Sample Selection with Scaling Laws","authors":["Y Jiang, A Zhou, Z Feng, S Malladi, JZ Kolter - arXiv preprint arXiv:2410.11820, 2024"],"snippet":"… Data with high diversity (eg, CommonCrawl) would naturally have a higher irreducible loss and data that are more predictable (eg, code and … We observe that CommonCrawl (Pile-CC) receives the most probability mass in both 124M and 1.3B …","url":["https://arxiv.org/pdf/2410.11820"]}
{"year":"2024","title":"Adaptive Ensembles of Fine-Tuned Transformers for LLM-Generated Text Detection","authors":["Z Lai, X Zhang, S Chen - arXiv preprint arXiv:2403.13335, 2024"],"snippet":"… 5) XLMRoberta: XLMRoberta is a large-scale multilingual transformer-based LM pretrained on a diverse set of one hundred languages using extensive CommonCrawl data [68]. We use the “xlm roberta base multi” as pretrained backbone weight. …","url":["https://arxiv.org/pdf/2403.13335"]}
{"year":"2024","title":"Adaptive Gradient Enhancement for Optimizing Large Language Models: An Empirical Study on Open Source Architectures","authors":["R Kingston, W Johnson, G Murphy, M Williams…"],"snippet":"… Training datasets consisted of large-scale corpora, such as Common Crawl and Wikipedia, which provided a wealth of information across various domains, enabling the model to learn from a rich tapestry of linguistic examples. Validation datasets …","url":["https://files.osf.io/v1/resources/e6bjz/providers/osfstorage/67137ed3907eeafcd52ec242?action=download&direct&version=2"]}
{"year":"2024","title":"AdaRankGrad: Adaptive Gradient-Rank and Moments for Memory-Efficient LLMs Training and Fine-Tuning","authors":["Y Refael, J Svirsky, B Shustin, W Huleihel… - arXiv preprint arXiv …, 2024"],"snippet":"Training and fine-tuning large language models (LLMs) come with challenges related to memory and computational requirements due to the increasing size of the model weights and the optimizer states. Various techniques have been developed to …","url":["https://arxiv.org/pdf/2410.17881"]}
{"year":"2024","title":"Addressing Both Statistical and Causal Gender Fairness in NLP Models","authors":["H Chen, Y Ji, D Evans - arXiv preprint arXiv:2404.00463, 2024"],"snippet":"… 2019) comprising nearly 400,000 online biographies of 28 unique occupations scraped from the CommonCrawl. The task is to predict the occupation given in the biography with the occupation title removed. Each biography includes the name and …","url":["https://arxiv.org/pdf/2404.00463"]}
{"year":"2024","title":"Addressing the Challenge of Online Health Misinformation: Detection, Retrieval, and Explainability","authors":["R Upadhyay - 2024"],"snippet":"Nell’odierna epoca digitale, le piattaforme online costituiscono uno dei mezzi principali utilizzati dalle persone per cercare informazioni relative alla propria salute. Nonostante il web sia un vasto repository di conoscenze in tale ambito, è affetto dal …","url":["https://boa.unimib.it/bitstream/10281/465160/2/phd_unimib_865291.pdf"]}
{"year":"2024","title":"Adjusting Interpretable Dimensions in Embedding Space with Human Judgments","authors":["K Erk, M Apidianaki - arXiv preprint arXiv:2404.02619, 2024"],"snippet":"… The GLoVe embeddings used were trained on Common Crawl (42B tokens, 1.9M vocab, uncased, 300d vectors), downloaded from https: //nlp.stanford.edu/projects/glove/. In order to generate embeddings for contextualized instances of words in our …","url":["https://arxiv.org/html/2404.02619v1"]}
{"year":"2024","title":"AdTEC: A Unified Benchmark for Evaluating Text Quality in Search Engine Advertising","authors":["P Zhang, Y Sakai, M Mita, H Ouchi, T Watanabe - arXiv preprint arXiv:2408.05906, 2024"],"snippet":"With the increase in the more fluent ad texts automatically created by natural language generation technology, it is in the high demand to verify the quality of these creatives in a real-world setting. We propose AdTEC, the first public …","url":["https://arxiv.org/pdf/2408.05906"]}
{"year":"2024","title":"Adult Content Detection on Indonesian Tweets by Fine-tuning Transformer-based Models","authors":["AF Hidayatullah, RA Apong, DTC Lai, A Qazi - 2023 6th International Conference on …, 2023"],"snippet":"The prevalence of adult content on social media has harmful effects on the moral values of young individuals. Therefore, effectively filtering inappropriate content on social media like Twitter is essential. Researchers have utilized machine learning …","url":["https://ieeexplore.ieee.org/abstract/document/10367283/"]}
{"year":"2024","title":"Advancements In Deep Learning Architectures: A Comparative Study Of Performance Metrics And Applications In Real-World Scenarios","authors":["S Chinta"],"snippet":"The rapid advancements in deep learning architectures have transformed various fields, enabling significant improvements in performance and efficiency. This study presents a comparative analysis of several state-of-the-art deep learning …","url":["https://www.researchgate.net/profile/Swetha-Chinta-2/publication/387218808_Advancements_In_Deep_Learning_Architectures_A_Comparative_Study_Of_Performance_Metrics_And_Applications_In_Real-World_Scenarios/links/6764376872316e5855fe26e9/Advancements-In-Deep-Learning-Architectures-A-Comparative-Study-Of-Performance-Metrics-And-Applications-In-Real-World-Scenarios.pdf"]}
{"year":"2024","title":"Advancements in Natural Language Understanding-Driven Machine Translation: Focus on English and the Low Resource Dialectal Lusoga","authors":["A Wasike, I Kamukama, YA Aleshinloye, AR Ajiboye…"],"snippet":"… These datasets include Common Crawl, a largescale web corpus with raw web page data [40]; The Pile, a diverse collection of English … Reference [40] notes that web-crawled datasets like Common Crawl often contain noise, such as duplicate …","url":["https://www.researchgate.net/profile/Azizi-Wasike/publication/385074545_Advancements_in_Natural_Language_Understanding-_Driven_Machine_Translation_Focus_on_English_and_the_Low_Resource_Dialectal_Lusoga/links/6713ddb4d796f96b8ebf5eab/Advancements-in-Natural-Language-Understanding-Driven-Machine-Translation-Focus-on-English-and-the-Low-Resource-Dialectal-Lusoga.pdf"]}
{"year":"2024","title":"Advances in AI-Generated Images and Videos.","authors":["H Bougueffa, M Keita, W Hamidouche, A Taleb-Ahmed… - International Journal of …, 2024"],"snippet":"In recent years generative AI models and tools have experienced a significant increase, especially techniques to generate synthetic multimedia content, such as images or videos. These methodologies present a wide range of possibilities; …","url":["https://search.ebscohost.com/login.aspx?direct=true&profile=ehost&scope=site&authtype=crawler&jrnl=19891660&AN=181559476&h=Ls%2B2VCYfNeJYtRChws%2FJ%2F8E4tbwQ%2BAV%2FqelO2h5NTrT0YLrXVVu2YwElvADGIyBnQIH8kMPjP9TIUxHWUWViRQ%3D%3D&crl=c"]}
{"year":"2024","title":"Advances in Multimodal Information Retrieval and Generation","authors":["M Luo"],"snippet":"Writing systems emerged simultaneously and independently in many ancient civilizations across the globe, including Mesopotamia, Egypt, China, India, and Mesoamerica. The invention of writing and scripts has had a tremendous impact on …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=jWkQEQAAQBAJ&oi=fnd&pg=PR5&dq=commoncrawl&ots=gHrlIlrmoN&sig=llOHcRl0LQw0w-1-dS4zoNhdz6A"]}
{"year":"2024","title":"Advancing fairness and differential privacy in machine learning for socially relevant applications","authors":["MW Pereira - 2024"],"snippet":"This thesis investigates privacy-preserving machine learning techniques for socially relevant applications. Specifically, this work tackles three important problems: the detection and identification of medias with abuse content, with a special focus on …","url":["https://repositorio.unb.br/jspui/bitstream/10482/50927/1/2024_MayanaWanderleyPereira_TESE.pdf"]}
{"year":"2024","title":"Advancing Fake News Detection: Hybrid Deep Learning with FastText and Explainable AI","authors":["E Hashmi, SY Yayilgan, MM Yamin, S Ali, M Abomhara - IEEE Access, 2024"],"snippet":"… FastText, a word representation tool developed by Facebook’s research division, provides both unsupervised and supervised modes, featuring an extensive lexicon of 2 million words sourced from Common Crawl. Each word is represented in a 300-dimensional …","url":["https://ieeexplore.ieee.org/iel7/6287639/6514899/10477989.pdf"]}
{"year":"2024","title":"Advancing Internet Viewpoint Diversity: A Novel Algorithm and a Corpus Creation Tool","authors":["J Harwell - 2023"],"snippet":"… To achieve this, we first develop a big data processing architecture for creating indexed corpora from the Common Crawl web archives. The … Utilizing this tool, we processed approximately 1.2 billion web pages from the Common Crawl dataset …","url":["https://scholarship.claremont.edu/cgi/viewcontent.cgi?article=1768&context=cgu_etd"]}
{"year":"2024","title":"Advancing language models through domain knowledge integration: a comprehensive approach to training, evaluation, and optimization of social scientific neural …","authors":["F Stöhr - Journal of Computational Social Science, 2024"],"snippet":"This article proposes a comprehensive strategy for training, evaluating, and optimizing domain-specific word2vec-based word embeddings, using social science literature as an example. Our primary objectives are:(1) to train the embeddings …","url":["https://link.springer.com/article/10.1007/s42001-024-00286-3"]}
{"year":"2024","title":"Advancing Large Multi-modal Models with Explicit Chain-of-Reasoning and Visual Question Generation","authors":["K Uehara, N Goswami, H Wang, T Baba, K Tanaka… - arXiv preprint arXiv …, 2024"],"snippet":"The increasing demand for intelligent systems capable of interpreting and reasoning about visual content requires the development of Large Multi-Modal Models (LMMs) that are not only accurate but also have explicit reasoning capabilities. This paper …","url":["https://arxiv.org/pdf/2401.10005"]}
{"year":"2024","title":"Advancing medical imaging with language models: featuring a spotlight on ChatGPT","authors":["M Hu, JY Qian, S Pan, Y Li, RLJ Qiu, X Yang - Physics in Medicine and Biology, 2024"],"snippet":"This review paper aims to serve as a comprehensive guide and instructional resource for researchers seeking to effectively implement language models in medical imaging research. First, we presented the fundamental principles and …","url":["https://iopscience.iop.org/article/10.1088/1361-6560/ad387d/pdf"]}
{"year":"2024","title":"Advancing Real-time Pandemic Forecasting Using Large Language Models: A COVID-19 Case Study","authors":["H Du, J Zhao, Y Zhao, S Xu, X Lin, Y Chen, LM Gardner - arXiv preprint arXiv …, 2024","HF Yang, H Du, J Zhao, Y Zhao, S Xu, X Lin, Y Chen… - 2024"],"snippet":"Forecasting the short-term spread of an ongoing disease outbreak is a formidable challenge due to the complexity of contributing factors, some of which can be characterized through interlinked, multi-modality variables such as epidemiological …","url":["https://arxiv.org/pdf/2404.06962","https://www.researchsquare.com/article/rs-4244182/latest.pdf"]}
{"year":"2024","title":"Advancing scientific writing with artificial intelligence: expanding the research toolkit","authors":["AG Atkinson, H Lia, SM Navarro - Global Surgical Education-Journal of the …, 2024"],"snippet":"Generative artificial intelligence (AI) is revolutionizing scientific writing by offering novel tools that integrate into various stages of the research process. This paper explores the application of AI tools in scientific writing, focusing on literature review …","url":["https://link.springer.com/article/10.1007/s44186-024-00271-4"]}
{"year":"2024","title":"Afrikaans Literary Genre Recognition using Embeddings and Pre-Trained Multilingual Language Models","authors":["E Kotzé, BA Senekal - 2024 International Conference on Artificial Intelligence …, 2024"],"snippet":"… XLM-R (or XLM-RoBERTa) is a multilingual version of RoBERTa with 279M parameters and was trained on a 2.5TB of CommonCrawl data containing 100 languages. Afrikaans is included in all three of these multilingual models. …","url":["https://ieeexplore.ieee.org/abstract/document/10467838/"]}
{"year":"2024","title":"AgentGen: Enhancing Planning Abilities for Large Language Model based Agent via Environment and Task Generation","authors":["M Hu, P Zhao, C Xu, Q Sun, J Lou, Q Lin, P Luo… - arXiv preprint arXiv …, 2024"],"snippet":"… The inspiration corpus can be implemented in various ways, such as using a large-scale pre-trained corpus like Common Crawl. Alternatively, a domain-specific corpus, such as a code generation dataset [25, 7], can be used to generate environments for a …","url":["https://arxiv.org/pdf/2408.00764"]}
{"year":"2024","title":"Aggression and Misogyny in Hindi and Bangla: A Study of YouTube Comments","authors":["R Kumar, B Lahiri - Studies in Pragmatics, 2024"],"snippet":"… The pre-trained models are typically trained on web-scale data, ie text collected from all over the web such as the whole of Wikipedia and a common crawl of the websites currently on the internet amounting to billions (or trillions) of tokens and …","url":["https://brill.com/downloadpdf/display/title/69958.pdf#page=130"]}
{"year":"2024","title":"AgXQA: A benchmark for advanced Agricultural Extension question answering","authors":["J Kpodo, P Kordjamshidi, AP Nejadhashemi - Computers and Electronics in …, 2024"],"snippet":"Large language models (LLMs) have revolutionized various scientific fields in the past few years, thanks to their generative and extractive abilities. However, their applications in the Agricultural Extension (AE) domain remain sparse and limited …","url":["https://www.sciencedirect.com/science/article/pii/S0168169924007403"]}
{"year":"2024","title":"AI and The European Union's Approach to Data Protection: The Case of Chat GPT","authors":["A AHKAMI"],"snippet":"Artificial Intelligence (AI) is advancing rapidly, with generative models like ChatGPT revolutionizing numerous industries. However, these advancements present significant challenges in adhering to data protection regulations such as the General …","url":["https://thesis.unipd.it/bitstream/20.500.12608/68193/1/AI%20and%20The%20European%20Union%27s%20Approach%20to%20Data%20Protection%20The%20Case%20of%20ChatGPT.pdf"]}
{"year":"2024","title":"AI as a Teachers Assistant","authors":["D Castelberg, L Flury - 2024"],"snippet":"… As GPT-3 is partially trained on data scraped off the internet using Common Crawl29 English was the most prevalent language it was trained on. English was kept for system prompts to avoid possible misunderstandings. User prompts were kept in …","url":["https://eprints.ost.ch/id/eprint/1230/1/FS%202024-BA-EP-Castelberg-Flury-AI%20as%20a%20Teacher%E2%80%99s%20Assistant.pdf"]}
{"year":"2024","title":"AI chatbots show promise but limitations on UK medical exam questions: a comparative performance study","authors":["MA Sadeq, RMF Ghorab, MH Ashry, AM Abozaid… - Scientific Reports, 2024"],"snippet":"… All chatbots scored higher on questions leaked to the C4 database except for ClaudeInstant which performed worse on the seven questions leaked to the common crawl database (0.571 ± 0.535) than other questions (0.631 ± 0.483). Bard …","url":["https://www.nature.com/articles/s41598-024-68996-2"]}
{"year":"2024","title":"AI Ethics in Enterprise HR Systems: Mitigating Bias and Ensuring Equity in LLM-Powered Employee Engagement Models","authors":["E Oluwagbade - 2024"],"snippet":"… Large Language Models in review were developed on the backbone of publicly available datasets, including Common Crawl, Wikipedia, and OpenWebText. Proprietary HR datasets provided by industry collaborators added depth to the …","url":["https://www.researchgate.net/profile/Elizabeth-Oluwagbade/publication/387190491_AI_Ethics_in_Enterprise_HR_Systems_Mitigating_Bias_and_Ensuring_Equity_in_LLM-Powered_Employee_Engagement_Models/links/6763d4158465b54be4e8474e/AI-Ethics-in-Enterprise-HR-Systems-Mitigating-Bias-and-Ensuring-Equity-in-LLM-Powered-Employee-Engagement-Models.pdf"]}
{"year":"2024","title":"AI Fanfare & Fanfiction: Do Fanfiction Writers Have Protections Against Artificial Intelligence?","authors":["S Tan - Brooklyn Law Review, 2024"],"snippet":"… CommonCrawl, an organization using bots to scrape data, has scraped so much information that it describes itself as “providing a copy of the Internet” to users.According to kafetheresu, CommonCrawl … Although AO3 took coding measures to exclude …","url":["https://brooklynworks.brooklaw.edu/cgi/viewcontent.cgi?article=2397&context=blr"]}
{"year":"2024","title":"AI for GovTech","authors":["C Snoeij"],"snippet":"You are about to read a thesis report that explores the use of Artificial Intelligence (AI), specifically Large Language Models (LLMs), for operationalizing Government Technology (GovTech) benchmarks. This thesis was written as part of the course …","url":["https://repository.tudelft.nl/file/File_d5797dce-88f3-48c5-b131-4579db09309b"]}
{"year":"2024","title":"AI for Science Advice: An Evaluation for the Government Office for Science","authors":["B Ai, C Chanwanpen, K Kramer, Y Hisamatsu, Z Jin"],"snippet":"The rapid development of artificial intelligence (AI), in particular large language models (LLMs), has sparked interest in its potential to improve the efficiency and effectiveness of science advisory processes. This study explores the application of …","url":["https://www.ucl.ac.uk/steapp/sites/steapp/files/9_final_report_-_ai_for_science_advice.pdf"]}
{"year":"2024","title":"AI Literacy for the Common Good","authors":["S Ullrich, R Messerschmidt - Weizenbaum Journal of the Digital Society, 2024"],"snippet":"… A large part of the training data (almost two-thirds) is the Common Crawl dataset, which comprises web pages collected between 2017 and 2020 provided for free by a non-profit organization. Wikipedia articles from the summer of 2022 still flow in at …","url":["https://ojs.weizenbaum-institut.de/index.php/wjds/article/view/4_1_5/149"]}
{"year":"2024","title":"AI unveiled personalities: Profiling optimistic and pessimistic attitudes in Hindi dataset using transformer‐based models","authors":["D Jain, A Kumar - Expert Systems"],"snippet":"Both optimism and pessimism are intricately intertwined with an individual's inherent personality traits and people of all personality types can exhibit a wide range of attitudes and behaviours, including levels of optimism and pessimism. This paper …","url":["https://onlinelibrary.wiley.com/doi/abs/10.1111/exsy.13572"]}
{"year":"2024","title":"AI vs. AI: Exploring Synthetic Text Detection of Large Language Models in a Low-Resource Language","authors":["J Gundersen - 2024"],"snippet":"This thesis will explore the effectiveness of Large Language Models ability to de- tect Norwegian Artificial Intelligence-generated texts in the context of their usage in Cognitive warfare and in the CogWar perspective. The explosion in usage and …","url":["https://ntnuopen.ntnu.no/ntnu-xmlui/bitstream/handle/11250/3167299/no.ntnu:inspera:187437008:71549801.pdf?sequence=1"]}
{"year":"2024","title":"AI vs. Human: Decoding Text Authenticity with Transformers","authors":["D Gifu, C Silviu-Vasile - 2024"],"snippet":"In an era where the proliferation of large language models blurs the lines between human and machine-generated content, discerning text authenticity is paramount. This study investigates transformer-based language models—BERT, RoBERTa, and …","url":["https://www.preprints.org/manuscript/202407.2014/download/final_file"]}
{"year":"2024","title":"AI's Secret Weapon in Education. ChatGPT–The Future of Personalized Learning","authors":["A Popescu - Bulletin of the Transilvania University of Brasov. Series …, 2023"],"snippet":"This article delves into the fascinating intersection of AI and education, with a focus on ChatGPT, a conversational AI developed by OpenAI. Noted for its human-like responses, ChatGPT is positioned as a game-changer in personalized learning. The …","url":["https://webbut.unitbv.ro/index.php/Series_V/article/download/6816/5216"]}
{"year":"2024","title":"AI, Robots. txt","authors":["J Jiménez, J Arkko - 2024"],"snippet":"… A significant portion of the training data for LLMs comes from large datasets like \"The Pile\" and \"Common Crawl,\" which are aggregates of smaller datasets [5, 17]. These datasets, often hundreds of GBs in size, are filtered and processed into plaintext …","url":["https://www.arkko.com/ietf/iab/arkko-jimenez.pdf"]}
{"year":"2024","title":"Ai-enabled automated common vulnerability scoring from common vulnerabilities and exposures descriptions","authors":["Z Zhang, V Kumar, B Pfahringer, A Bifet - International Journal of Information Security, 2025"],"snippet":"With the sheer amount of vulnerabilities, manually evaluating the impact of them is challenging. This paper proposes employing artificial intelligence models as substitutes for humans or as aides to human experts in estimating vulnerabilities. We …","url":["https://link.springer.com/article/10.1007/s10207-024-00922-z"]}
{"year":"2024","title":"AI-Generated Text Detector for Arabic Language","authors":["H Alshammari - 2024"],"snippet":"The rise of AI-generated texts (AIGTs), particularly with the arrival of advanced language models like ChatGPT, has spurred a growing need for effective detection methods. While these models offer various beneficial applications, their potential for …","url":["https://search.proquest.com/openview/193bae341b2c0624ffc194ceabf2c986/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
{"year":"2024","title":"AI-Powered Code Review Assistant for Streamlining Pull Request Merging","authors":["C Adapa, SS Avulamanda, ARK Anjana, A Victor - 2024 IEEE International …, 2024"],"snippet":"… The model's reliance on Refined Web, primarily sourced from Common Crawl, underscores its commitment to exceptional quality through advanced data augmentation techniques, notably largescale deduplication and rigorous filtering. Unlike conventional …","url":["https://ieeexplore.ieee.org/abstract/document/10503540/"]}
{"year":"2024","title":"AI-Proof Your Assignments","authors":["S Vital - 2024"],"snippet":"ChatGPT and other AI tools are powerful, free, and seemingly everywhere. Faculty love it, fear it, and everything in between. Students also love it, fear it, and everything in between; All the while, they are using it. In this session, we’ll cover a bit about how …","url":["https://digitalcommons.stmarys-ca.edu/cgi/viewcontent.cgi?article=1159&context=staff-works"]}
{"year":"2024","title":"AI-Replicas as Ethical Practice: Introducing an Alternative to Traditional Anonymization Techniques in Image-Based Research","authors":["T Kamelski, F Olivos - 2024"],"snippet":"This paper introduces the use of AI-replicas as an alternative to traditional anonymization methods in image-based qualitative research. It emphasizes the ethical and practical dilemmas posed by current anonymization methods, such as …","url":["https://osf.io/8frst/download"]}
{"year":"2024","title":"AIC CTU system at AVeriTeC: Re-framing automated fact-checking as a simple RAG task","authors":["H Ullrich, T Mlynář, J Drchal - arXiv preprint arXiv:2410.11446, 2024"],"snippet":"This paper describes our $3^{rd}$ place submission in the AVeriTeC shared task in which we attempted to address the challenge of fact-checking with evidence retrieved in the wild using a simple scheme of Retrieval-Augmented Generation (RAG) …","url":["https://arxiv.org/pdf/2410.11446"]}
{"year":"2024","title":"Ain't no party like a GPT party: assessing OpenAI's GPT political alignment classification capabilities","authors":["LO M. Foisy, J Drouin, C Pelletier, J Rivest, H Cadieux… - Journal of Information …, 2024"],"snippet":"… Common Crawl and WebText2 account for 80% of the weight in the training mix. Based on the information available on the Common Crawl website, these datasets are created through web scrapping and are composed of between 97% and 98% of …","url":["https://www.tandfonline.com/doi/abs/10.1080/19331681.2024.2444587"]}
{"year":"2024","title":"Aioli: A Unified Optimization Framework for Language Model Data Mixing","authors":["MF Chen, MY Hu, N Lourie, K Cho, C Ré - arXiv preprint arXiv:2411.05735, 2024"],"snippet":"… For example, C4 is a subset of CommonCrawl, so repartitioning these datasets into more disjoint groups could result in better data mixing performance. Furthermore, it is unclear if linear mixing laws results from some specific property of the data …","url":["https://arxiv.org/pdf/2411.05735"]}
{"year":"2024","title":"Algorithmic amplification of biases on Google Search","authors":["H Habib, R Stoldt, A High, B Ekdale, A Peterson… - arXiv preprint arXiv …, 2024"],"snippet":"The evolution of information-seeking processes, driven by search engines like Google, has transformed the access to information people have. This paper investigates how individuals' preexisting attitudes influence the modern information-seeking …","url":["https://arxiv.org/pdf/2401.09044"]}
{"year":"2024","title":"Algorithms and Systems for Scalable Machine Learning over Graphs","authors":["R Waleffe - 2024"],"snippet":"… for large-scale graphs: We use MariusGNN to train a GNN over the entire hyperlink graph from the Common Crawl 2012 web corpus, a graph with 3.5B nodes (web pages) and 128B edges (hyperlinks between pages) (Table 1.1). MariusGNN …","url":["https://search.proquest.com/openview/4463dadd65fc7d321f045f079db135f7/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
{"year":"2024","title":"Alpaca against Vicuna: Using LLMs to Uncover Memorization of LLMs","authors":["AM Kassem, O Mahmoud, N Mireshghallah, H Kim… - arXiv preprint arXiv …, 2024"],"snippet":"In this paper, we introduce a black-box prompt optimization method that uses an attacker LLM agent to uncover higher levels of memorization in a victim agent, compared to what is revealed by prompting the target model with the training data …","url":["https://arxiv.org/pdf/2403.04801"]}
{"year":"2024","title":"ALT-GEN: Benchmarking Table Union Search using Large Language Models","authors":["K Pal, A Khatiwada, R Shraga, RJ Miller - Proceedings of the VLDB Endowment. ISSN"],"snippet":"David Paterson states that when a eld has good benchmarks, we settle debates and the eld makes rapid progress [33]. Traditionally, benchmark generation is done using synthetic data generators that precisely control parameters such as data size …","url":["https://tabular-data-analysis.github.io/tada2024/papers/TaDA.3.pdf"]}
{"year":"2024","title":"Amharic LLaMA and LLaVA: Multimodal LLMs for Low Resource Languages","authors":["M Andersland - arXiv preprint arXiv:2403.06354, 2024"],"snippet":"… Less than 0.1% of CommonCrawl2 is Amharic, and even when combining open source datasets without deduplication, we find that less than 500 million tokens of Amharic are available. In addition, the content of this data tends to be biased …","url":["https://arxiv.org/pdf/2403.06354"]}
{"year":"2024","title":"An AI-driven social media recommender system leveraging smartphone and IoT data","authors":["D Yu, X Zhou, A Noorian, M Hazratifard - The Journal of Supercomputing, 2025"],"snippet":"Our research presents “RoBERTaRecIOT,” an innovative model that stands out for its superiority. It utilizes the pre-trained Robustly Optimized Bidirectional Encoder Representations from Transformers (RoBERTa) framework to deliver personalized …","url":["https://link.springer.com/article/10.1007/s11227-024-06722-5"]}
{"year":"2024","title":"An Ambiguous Technique for Nonvisual Text Entry","authors":["DC Gaines - 2023"],"snippet":"Text entry is a common daily task for many people, but it can be a challenge for people with visual impairments when using virtual touchscreen keyboards that lack physical key boundaries. In this thesis, we investigate using a small number of …","url":["https://digitalcommons.mtu.edu/cgi/viewcontent.cgi?article=2800&context=etdr"]}
{"year":"2024","title":"An Analysis of Langauge Frequency and Error Correction for Esperanto","authors":["J Liang - arXiv preprint arXiv:2402.09696, 2024"],"snippet":"… Goyal builds Commoncrawl Corpus in 100 languages and then uses a language identification model to select Esperanto contexts[8], which … OSCAR [11] provides a collection of unannotated raw data and devises a method to improve the quality of …","url":["https://arxiv.org/pdf/2402.09696"]}
{"year":"2024","title":"An Analysis of Multilingual FActScore","authors":["KT Vu, M Krumdick, V Reddy, F Dernoncourt, VD Lai - arXiv preprint arXiv …, 2024"],"snippet":"FActScore has gained popularity as a metric to estimate the factuality of long-form texts generated by Large Language Models (LLMs) in English. However, there has not been any work in studying the behavior of FActScore in other languages. This …","url":["https://arxiv.org/pdf/2406.19415"]}
{"year":"2024","title":"AN ANALYSIS ON SHORT-FORM TEXT AND DERIVED ENGAGEMENT","authors":["RJ Schwarz - 2024"],"snippet":"Short text has historically proven challenging to work with in many Natural LanguageProcessing (NLP) applications. Traditional tasks such as authorship attribution benefitfrom having longer samples of work to derive features from. Even …","url":["https://hammer.purdue.edu/articles/thesis/AN_ANALYSIS_ON_SHORT-FORM_TEXT_AND_DERIVED_ENGAGEMENT/26335663/1/files/47829367.pdf"]}
{"year":"2024","title":"An Assessment on Comprehending Mental Health through Large Language Models","authors":["M Arcan, PD Niland, F Delahunty - arXiv preprint arXiv:2401.04592, 2024"],"snippet":"… The training data for GPT-3 is primarily sourced from a filtered version of Common Crawl, contributing to 60% of the weighted pre-training dataset, comprising 410 billion bytepair-encoded tokens. Other data sources include 19 billion tokens from …","url":["https://arxiv.org/pdf/2401.04592"]}
{"year":"2024","title":"An efficient parallel optimization method for large model based on cloud computing","authors":["Z Xu - … Conference on Electronic Information Engineering and …, 2024"],"snippet":"… Subsequently, we employ a similar methodology to create Pile-CC, involving the download and refinement of two complete Common Crawl (CC) snapshots. The overall process for handling CC data entails extracting text from the raw HTML …","url":["https://www.spiedigitallibrary.org/conference-proceedings-of-spie/13184/131842T/An-efficient-parallel-optimization-method-for-large-model-based-on/10.1117/12.3033037.short"]}
{"year":"2024","title":"An ensemble learning approach for detecting phishing URLs in encrypted TLS traffic","authors":["C Kondaiah, AR Pais, RS Rao - Telecommunication Systems, 2024"],"snippet":"… The model was trained and tested on a dataset comprising one million URLs sourced from PhishTank and Common Crawl and over 10,000 images collected from various e-commerce and e-banking websites. The proposed model achieved …","url":["https://link.springer.com/article/10.1007/s11235-024-01229-z"]}
{"year":"2024","title":"An Extensive Survey on Investigation Methodologies for Text Summarization","authors":["A Saklecha, P Uplavdiya, MPS Chawla - Indian Journal of Signal Processing (IJSP), 2023"],"snippet":"Natural language processing (NLP) is a fastexpanding field, and text summarization has recently gained a lot of research interest. The necessity for automatic summarizing approaches to effectively digest massive amounts of textual data has …","url":["https://www.ijsp.latticescipub.com/wp-content/uploads/papers/v3i4/D1016113423.pdf"]}
{"year":"2024","title":"An In-Depth Analysis of the Adoption of Large Language Models in Clinical Settings: A Fuzzy Multi-Criteria Decision-Making Approach","authors":["AM Aldwean - 2024"],"snippet":"The growing capabilities of large language models (LLMs) in the medical field hold promising transformational change. The evolution of LLMs, such as BioBERT and MedGPT, has created new opportunities for enhancing the quality of healthcare …","url":["https://search.proquest.com/openview/afe33dbe92c45414a67a4e7b377f2716/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
{"year":"2024","title":"An Initial Review of the Copyright Concerns of Generative Artificial Intelligence","authors":["G Billiris, AQ Gill - 2024"],"snippet":"Generative Artificial Intelligence (GAI) heralds a new era of creativity and technological advancement. Despite its promising benefits, GAI raises concerns about its trustworthiness and associated challenges. This study employs a digital …","url":["https://aisel.aisnet.org/acis2024/17/"]}
{"year":"2024","title":"An Integrated Data Processing Framework for Pretraining Foundation Models","authors":["Y Sun, F Wang, Y Zhu, WX Zhao, J Mao - arXiv preprint arXiv:2402.16358, 2024"],"snippet":"… In the end-to-end evaluation, we train two GPT-2 models using CommonCrawl before and after processing, respectively. The model trained on the refined data demonstrates remarkable performance enhancement across downstream tasks of …","url":["https://arxiv.org/pdf/2402.16358"]}
{"year":"2024","title":"An integrated model based on deep learning classifiers and pre-trained transformer for phishing URL detection","authors":["NQ Do, A Selamat, H Fujita, O Krejcar - Future Generation Computer Systems, 2024"],"snippet":"The unique nature of website URLs has made phishing detection a challenging task. Unlike natural language, URLs have an unstructured nature with non-linear and sophisticated correlations. Therefore, they should be handled as both natural …","url":["https://www.sciencedirect.com/science/article/pii/S0167739X24003315"]}
{"year":"2024","title":"An Introduction to Vision-Language Modeling","authors":["F Bordes, RY Pang, A Ajay, AC Li, A Bardes, S Petryk… - arXiv preprint arXiv …, 2024"],"snippet":"… Multiple curation steps are used to curate this dataset where English data is collected from common crawl and deduplicated followed by pre-processing HTML document where useful DOM nodes are identified and retained, then for each DOM …","url":["https://arxiv.org/pdf/2405.17247"]}
{"year":"2024","title":"An overview of large AI models and their applications","authors":["X Tu, Z He, Y Huang, ZH Zhang, M Yang, J Zhao - Visual Intelligence, 2024"],"snippet":"In recent years, large-scale artificial intelligence (AI) models have become a focal point in technology, attracting widespread attention and acclaim. Notable examples include Google’s BERT and OpenAI’s GPT, which have scaled their parameter sizes …","url":["https://link.springer.com/article/10.1007/s44267-024-00065-8"]}
{"year":"2024","title":"An Updated Analysis of Learning Resource Metadata Usage on the Web","authors":["R Sebastian, A Hoppe - International Conference on Theory and Practice of …, 2024"],"snippet":"… The Web Data Commons(WDC) [8] extracts embedded linked open data from HTML resources scraped by the Common Crawl [3]. This is the starting point for our analysis. While the Common Crawl is only a subset of the publicly available web, it …","url":["https://link.springer.com/chapter/10.1007/978-3-031-72440-4_8"]}
{"year":"2024","title":"Analysing Slow Thinking Capabilities in Large Language Model Agent-Agent Dialogue","authors":["J Cornelje - 2024"],"snippet":"… LLMs can be given data from books, CommonCrawl, Reddit links and Wikipedia, where CommonCrawl consists of petabytes of web archives [113]. Having large datasets makes it more difficult to curate the data. Documentation of the data can …","url":["https://studenttheses.uu.nl/bitstream/handle/20.500.12932/46440/Master%20Thesis%20-%20Joel%20Cornelje.pdf?sequence=1"]}
{"year":"2024","title":"Analysing The Impact of Sequence Composition on Language Model Pre-Training","authors":["Y Zhao, Y Qu, K Staniszewski, S Tworkowski, W Liu… - arXiv preprint arXiv …, 2024"],"snippet":"Most language model pre-training frameworks concatenate multiple documents into fixed-length sequences and use causal masking to compute the likelihood of each token given its context; this strategy is widely adopted due to its simplicity and …","url":["https://arxiv.org/pdf/2402.13991"]}
{"year":"2024","title":"Analysing the landscape of Deep Fake Detection: A Survey","authors":["K Vyas, P Pareek, R Jayaswal, S Patil - … of Intelligent Systems and Applications in …, 2024"],"snippet":"… Grover utilizes a test set created by the free and open-source web crawler and archive Common Crawl [35]. As an example, a team of academics from Harvard and the MIT-IBM Watson laboratory developed the Giant language model test room, a …","url":["https://www.ijisae.org/index.php/IJISAE/article/download/4418/3078"]}
{"year":"2024","title":"ANALYSIS AND MODELING OF STATE-LEVEL POLICY AND LEGISLATIVE TEXT WITH NLP AND ML TECHNIQUES","authors":["M Davoodi - 2024"],"snippet":"State-level policy decisions significantly influence various aspects of our daily lives, such as access to healthcare and education. Despite their importance, there is a limited understanding of how these policies and decisions are formulated within the …","url":["https://hammer.purdue.edu/articles/thesis/ANALYSIS_AND_MODELING_OF_STATE-LEVEL_POLICY_AND_LEGISLATIVE_TEXT_WITH_NLP_AND_ML_TECHNIQUES/27956481/1/files/50976462.pdf"]}
{"year":"2024","title":"ANALYSIS OF CROSS-LINGUAL MODELS FOR ASPECT-BASED SENTIMENT ANALYSIS: A CASE STUDY IN DUTCH AS A LOW-RESOURCE LANGUAGE.","authors":["RA COTFAS"],"snippet":"This study addressed the limited availability of well-labeled data and research resources for end-to-end ABSA in low-resource languages, particularly Dutch. The study aims to tackle this challenge by investigating the performance of state-of-the-art …","url":["http://arno.uvt.nl/show.cgi?fid=172664"]}
{"year":"2024","title":"AnchorAL: Computationally Efficient Active Learning for Large and Imbalanced Datasets","authors":["P Lesci, A Vlachos - arXiv preprint arXiv:2404.05623, 2024"],"snippet":"Active learning for imbalanced classification tasks is challenging as the minority classes naturally occur rarely. Gathering a large pool of unlabelled data is thus essential to capture minority instances. Standard pool-based active learning is …","url":["https://arxiv.org/html/2404.05623v1"]}
{"year":"2024","title":"Ancient Greek's New Technological Muse: Extracting Topoi in the Anacreontea with LLMs","authors":["RO Nunes, JG Zandoná, JV Maia, A Spritzer… - Seminário Integrado de …, 2024"],"snippet":"… The pre-training corpora include texts from Wikipedia, the European Parliament Proceedings Parallel Corpus, and OSCAR, a cleansed version of Common Crawl Researchers have also introduced a pilot study focused on the automatic linguistic …","url":["https://sol.sbc.org.br/index.php/semish/article/download/29353/29158/"]}
{"year":"2024","title":"and S. Abirami","authors":["RS Gulecha, SKNR Subramanian - Speech and Language Technologies for Low …"],"snippet":"In recent years, the Internet and social media have sparked a revolution in the way information is exchanged. The growth of social media and micro-blogging sites not only provides platforms for empowering freedom of expression and individual voices …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=Rs0DEQAAQBAJ&oi=fnd&pg=PA225&dq=commoncrawl&ots=l6SKt6PjDk&sig=xgAK9FCRDZ55-F9mtury-zU49yk"]}
{"year":"2024","title":"Answer Agnostic Question Generation in Bangla Language","authors":["AR Fahad, N Al Nahian, MA Islam, RM Rahman - International Journal of Networked …, 2024"],"snippet":"… mT5 is a massively multilingual model pre-trained using fresh Common Crawl-based data that includes 101 languages [14]. Another model, BanglaT5, a Transformer model for the Bangla language, was trained using a 27.5 GB clean corpus of Bangla …","url":["https://link.springer.com/article/10.1007/s44227-023-00018-5"]}
{"year":"2024","title":"AntiPhishStack: LSTM-based Stacked Generalization Model for Optimized Phishing URLs Detection","authors":["S Aslam, H Aslam, A Manzoor, C Hui, A Rasool - 2024"],"snippet":"The escalating reliance on revolutionary online web services has introduced heightened security risks, with persistent challenges posed by phishing despite extensive security measures. Traditional phishing systems, reliant on machine …","url":["https://www.preprints.org/manuscript/202401.1142/download/final_file"]}
{"year":"2024","title":"AnyGPT: Unified Multimodal LLM with Discrete Sequence Modeling","authors":["J Zhan, J Dai, J Ye, Y Zhou, D Zhang, Z Liu, X Zhang… - arXiv preprint arXiv …, 2024"],"snippet":"We introduce AnyGPT, an any-to-any multimodal language model that utilizes discrete representations for the unified processing of various modalities, including speech, text, images, and music. AnyGPT can be trained stably without any …","url":["https://arxiv.org/pdf/2402.12226"]}
{"year":"2024","title":"APLIKASI CHATGPT DALAM BAHASA MELAYU: ISU DAN CADANGAN PENYELESAIAN: OPERATING CHATGPT IN MALAY: ISSUES AND PROPOSED …","authors":["H Nomoto, D Moeljadi, FAA Razak - RENTAS: Jurnal Bahasa, Sastera dan Budaya, 2024"],"snippet":"… bekerjasama dengan kerajaan Brunei dan Singapura, meminta OpenAI dan Common Crawl, iaitu sumber utama set data latihan ChatGPT, … .my yang disenaraikan dalam 500 laman web teratas yang berdaftar di Common Crawl.Untuk …","url":["https://e-journal.uum.edu.my/index.php/jbsb/article/download/22165/4330"]}
{"year":"2024","title":"APOLLO: SGD-like Memory, AdamW-level Performance","authors":["H Zhu, Z Zhang, W Cong, X Liu, S Park, V Chandra… - arXiv preprint arXiv …, 2024"],"snippet":"Large language models (LLMs) are notoriously memory-intensive during training, particularly with the popular AdamW optimizer. This memory burden necessitates using more or higher-end GPUs or reducing batch sizes, limiting training scalability …","url":["https://arxiv.org/pdf/2412.05270"]}
{"year":"2024","title":"Application of an Improved Convolutional Neural Network Algorithm in Text Classification","authors":["J Peng, S Huo - Journal of Web Engineering, 2024"],"snippet":"This paper proposes a text classification model based on a combination of a convolutional neural network (CNN) and a support vector machine (SVM) using Amazon review polarity, TREC, and Kaggle as experimental data. By adding an …","url":["https://journals.riverpublishers.com/index.php/JWE/article/download/25003/19981"]}
{"year":"2024","title":"Application of Open-source Large Language Model (LLM) for Simulation of a Vulnerable IoT System and Cybersecurity Best Practices Assistance","authors":["V Yosifova - 2024"],"snippet":"This paper explores the role of open-source large language models in IoT cybersecurity world. The threats of malicious activity on the Internet and the loss of private information are very real and lead to serious consequences. The purpose of …","url":["https://www.preprints.org/manuscript/202405.1169/download/final_file"]}
{"year":"2024","title":"Applications and Concerns of ChatGPT and Other Conversational Large Language Models in Health Care: Systematic Review","authors":["L Wang, Z Wan, C Ni, Q Song, Y Li, E Clayton, B Malin… - Journal of Medical Internet …, 2024"],"snippet":"Background The launch of ChatGPT (OpenAI) in November 2022 attracted public attention and academic interest to large language models (LLMs), facilitating the emergence of many other innovative LLMs. These LLMs have been applied in …","url":["https://www.jmir.org/2024/1/e22769/"]}
{"year":"2024","title":"Applications of AI in Computer Vision and NLP","authors":["SB Rajasekaran - Journal of Artificial Intelligence & Cloud Computing …, 2023"],"snippet":"… In language AI, there are several commonly used datasets such as Common Crawl, Wikipedia, and OpenWebText. However, creating and maintaining these datasets can also be a challenging task, as it needs a big amount of work and it can …","url":["https://www.onlinescientificresearch.com/articles/applications-of-ai-in-computer-vision-and-nlp.pdf"]}
{"year":"2024","title":"Applying German word vectors to assess flexibility performance in the associative fluency task.","authors":["M Camenzind, M Single, SM Gerber, T Nef, CL Bassetti… - Psychology of Aesthetics …, 2024"],"snippet":"… One model was trained on common crawl, a nonprofit organization crawling the web and making resulting data publicly available, and the other was trained on Wikipedia. The vectors were trained using the CBOW algorithm with a special focus …","url":["https://psycnet.apa.org/record/2024-67165-001"]}
{"year":"2024","title":"Applying Named Entity Recognition and Graph Networks to Extract Common Interests from Thematic Subfora on Reddit","authors":["J Sawicki, M Ganzha, M Paprzycki, Y Watanobe - Applied Sciences, 2024"],"snippet":"… , accessed on 13 February 2024) (pre-trained BERT large models fine-tuned on the CoNLL-2003 dataset) and flair/ner-english-large (https://huggingface.co/flair/ner-english-large, accessed on 13 February 2024) (an XLM-RoBERTa [89] pre-trained on a cleaned …","url":["https://www.mdpi.com/2076-3417/14/5/1696"]}
{"year":"2024","title":"Applying Transfer Learning to German Metaphor Prediction","authors":["M Berger, SM Reimann, NM Kiwitt - Proceedings of the 2024 Joint International …, 2024"],"snippet":"… -scores using CommonCrawl embeddings (F1 60%) and News Commentary embeddings (F1 58%) while CommonCrawl contains over 2 m… 4), we can see that the bilingual embeddings approach, especially using Europarl and CommonCrawl …","url":["https://aclanthology.org/2024.lrec-main.123.pdf"]}
{"year":"2024","title":"Arabic sarcasm detection: An enhanced fine-tuned language model approach","authors":["MA Galal, AH Yousef, HH Zayed, W Medhat - Ain Shams Engineering Journal, 2024"],"snippet":"Sarcasm is a complex linguistic phenomenon involving humor, criticism, or phrases that convey the opposite meaning, mask true feelings, and play pivotal roles in various aspects of communication. Therefore, identifying sarcasm is essential for …","url":["https://www.sciencedirect.com/science/article/pii/S2090447924001114"]}
{"year":"2024","title":"Arctic-Embed: Scalable, Efficient, and Accurate Text Embedding Models","authors":["L Merrick, D Xu, G Nuti, D Campos - arXiv preprint arXiv:2405.05374, 2024"],"snippet":"This report describes the training dataset creation and recipe behind the family of \\texttt{arctic-embed} text embedding models (a set of five models ranging from 22 to 334 million parameters with weights open-sourced under an Apache-2 license). At the time of …","url":["https://arxiv.org/pdf/2405.05374"]}
{"year":"2024","title":"Are Human Conversations Special? A Large Language Model Perspective","authors":["T Jawale, C Animesh, S Vallath, K Talamadupula… - arXiv preprint arXiv …, 2024"],"snippet":"… We analyze the web data from CommonCrawl[21] dumps for human conversation data and the types of conversations in Table 1. We randomly sample a subset of the dump and deduplicate it so that it can be used to approximate the data distribution …","url":["https://arxiv.org/html/2403.05045v1"]}
{"year":"2024","title":"Are LLMs Good for Low-resource Vietnamese and Other Translations?","authors":["VV Nguyen, H Nguyen-Tien, P Nguyen-Ngoc… - 2024"],"snippet":"… mT5 is a large multilingual model [6] that was pre-trained on a new Common Crawl-based dataset, which includes 101 languages. In this work, they detail the design and modified training of mT5 and demonstrate its state-of-the-art …","url":["https://www.researchsquare.com/article/rs-5355866/latest.pdf"]}
{"year":"2024","title":"Are LLMs Prescient? A Continuous Evaluation using Daily News as the Oracle","authors":["H Dai, R Teehan, M Ren - arXiv preprint arXiv:2411.08324, 2024"],"snippet":"Many existing evaluation benchmarks for Large Language Models (LLMs) quickly become outdated due to the emergence of new models and training data. These benchmarks also fall short in assessing how LLM performance changes over time …","url":["https://arxiv.org/pdf/2411.08324"]}
{"year":"2024","title":"Are LLMs Robust for Spoken Dialogues?","authors":["SM Mousavi, G Roccabruna, S Alghisi, M Rizzoli… - arXiv preprint arXiv …, 2024"],"snippet":"… The LLM finetuned for this task is T5 Small [21], (12 layers, 60M parameters), a transformer-based encoder-decoder model, pre-trained on the Common Crawl dataset with 750GB of web page text. The fine-tuning was performed following the …","url":["https://arxiv.org/pdf/2401.02297"]}
{"year":"2024","title":"Are We All Musicians Now? Authenticity, Musicianship, and AI Music Generator Suno","authors":["S Tan - 2024"],"snippet":"This paper analyzes the authenticity of the music and the musicianship behind Suno, an artificial intelligence (AI) music generator. The developers launched Suno’s initial release on December 20, 2023, and the latest version, v4, on November 19, 2024 …","url":["https://osf.io/4nt8z/download"]}
{"year":"2024","title":"Aria-UI: Visual Grounding for GUI Instructions","authors":["Y Yang, Y Wang, D Li, Z Luo, B Chen, C Huang, J Li - arXiv preprint arXiv:2412.16256, 2024"],"snippet":"… diverse data synthesis pipeline from our Common Crawl collection and public available data. … caption, instruction) samples from Common Crawl and publicly available data, enabling Aria-… We leverage the latest collection of Common Crawl …","url":["https://arxiv.org/pdf/2412.16256"]}
{"year":"2024","title":"Aria: An Open Multimodal Native Mixture-of-Experts Model","authors":["D Li, Y Liu, H Wu, Y Wang, Z Shen, B Qu, X Niu… - arXiv preprint arXiv …, 2024"],"snippet":"… We extract and filter web pages from Common Crawl. The filtering process first removes web pages with low image or text quality. Then, it deduplicate images, and removes web pages where the images and the text have low overall CLIP score [Radford …","url":["https://arxiv.org/pdf/2410.05993"]}
{"year":"2024","title":"Artificial Divides: Global AI Access Disparities and Constructions of New Digital Realities","authors":["L Peng - 2024"],"snippet":"Following the wake of ChatGPT’s release in late 2022, we have witnessed the launch of an “arms race” of generative AI technology as large language models (LLMs) entered a phase of rapid development and advancement, with promises of …","url":["https://search.proquest.com/openview/f1715dc8510957e376b032206084aa4f/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
{"year":"2024","title":"ARTIFICIAL INTELLIGENCE (AI) AND ETHICS OF EDUCATIONAL RESEARCH","authors":["KA YOHANNA, I MATTHEW, H DANASABE - Sokoto Educational Review, 2024"],"snippet":"Integrating Artificial Intelligence (AI) into educational research is rapidly advancing, offering innovative opportunities for personalized learning and data-driven insights. However, the ethical implications of AI use in education, including concerns about …","url":["http://www.sokedureview.org/index.php/SER/article/download/515/488"]}
{"year":"2024","title":"Artificial Intelligence and the Law of Machine-Readability: A Review of Human-to-Machine Communication Protocols and their (In) Compatibility with Article 4 (3) of the …","authors":["H Hamann - JIPITEC–Journal of Intellectual Property, Information …, 2024"],"snippet":"Many legal scholars critique the supposed ineffectiveness of European copyright regulation regarding commercial text and data mining. At the same time, tech-savvy entrepreneurs keep proposing new standards to effectuate them at a rate that has …","url":["https://www.jipitec.eu/jipitec/article/download/407/404"]}
{"year":"2024","title":"Artificial Intelligence as the Next Front in the Class War","authors":["C Hill - 2024"],"snippet":"For many years, artificial intelligence has been confined to the realm of science fiction, and while the technology has been in development, predicting the effects AI will have on our society has been a challenging endeavor. The release of ChatGPT …","url":["https://search.proquest.com/openview/5443943478391e6a128ff58e5cb6a081/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
{"year":"2024","title":"Artificial Intelligence for Anesthesiology Board-style Examination Questions: Role of Large Language Models","authors":["AA Khan, R Yunus, M Sohail, TA Rehman, S Saeed… - Journal of Cardiothoracic …, 2024"],"snippet":"Background : New artificial intelligence tools have been developed that have implications for medical usage. Large language models such as the widely used ChatGPT, developed by OpenAI, have not been explored in the context of …","url":["https://www.sciencedirect.com/science/article/pii/S1053077024000909"]}
{"year":"2024","title":"Artificial Intelligence in the Media Economy: A Systematic Review of Use Cases, Application Potentials, and Challenges of Generative Language Models","authors":["T Prien, K Goldhammer - 2024"],"snippet":"Springer MRW: [AU:, IDX:] Page 1 Artificial Intelligence in the Media Economy: A Systematic Review of Use Cases, Application Potentials, and Challenges of Generative Language Models Tim Prien and Klaus Goldhammer Contents 1 …","url":["https://link.springer.com/content/pdf/10.1007/978-3-658-34048-3_89-1.pdf"]}
{"year":"2024","title":"Artificial intelligence in the news: how AI retools, rationalizes, and reshapes journalism and the public arena","authors":["F Simon - 2024"],"snippet":"Despite growing interest, the effects of AI on the news industry and our information environment — the public arena — remain poorly understood. Insufficient attention has also been paid to the implications of the news industry’s dependence on …","url":["https://ora.ox.ac.uk/objects/uuid:aeb25013-1d17-40b2-b471-5bdca309db87/files/s4t64gp800"]}
{"year":"2024","title":"Artificial Intelligence Integration, Concerns, Benefits, and the Need for Ethical Policies for Community Foundations and Nonprofit Organizations","authors":["V Balidemaj - 2024"],"snippet":"This study describes the nature and extent of Artificial Intelligence (AI) integration in philanthropic organizations and assesses the capacity and readiness of nonprofits in adopting AI for philanthropic use. Additionally, the study explores the nature and …","url":["https://open.clemson.edu/cgi/viewcontent.cgi?article=4768&context=all_dissertations"]}
{"year":"2024","title":"Artificial Intelligence Supporting Independent Student Learning: An Evaluative Case Study of ChatGPT and Learning to Code","authors":["K Hartley, M Hayak, UH Ko - Education Sciences, 2024"],"snippet":"Artificial intelligence (AI) tools like ChatGPT demonstrate the potential to support personalized and adaptive learning experiences. This study explores how ChatGPT can facilitate self-regulated learning processes and learning computer programming …","url":["https://www.mdpi.com/2227-7102/14/2/120"]}
{"year":"2024","title":"Artificial Intelligence, Large Language Models, and Design Thinking in TPC Classrooms","authors":["C Masters-Wheeler, J Bay, P Sullivan - Programmatic Perspectives, 2023"],"snippet":"… Common Crawl, for instance, is an open repository of web data that is accessible to anyone and can be used to train AI models. Large language models (LLMs) use the textual data from sources like Common Crawl and other freely accessible data …","url":["https://programmaticperspectives.cptsc.org/index.php/jpp/article/download/58/73"]}
{"year":"2024","title":"Artificial Intelligence, Machine Learning, and Deep Learning Applications in the Engineering Fields–A Comprehensive Review","authors":["H Darwish, W Darwish, H Darwish, IW AlHmoud…"],"snippet":"This research paper addresses the critical issue of understanding the diverse applications of Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) across 14 distinct engineering disciplines, a topic of growing …","url":["https://www.researchgate.net/profile/Hiba-Darwish-3/publication/385505148_Artificial_Intelligence_Machine_Learning_and_Deep_Learning_Applications_in_the_Engineering_Fields_-A_Comprehensive_Review/links/6727a96c77b63d1220d760eb/Artificial-Intelligence-Machine-Learning-and-Deep-Learning-Applications-in-the-Engineering-Fields-A-Comprehensive-Review.pdf"]}
{"year":"2024","title":"Asking GPT for the Ordinary Meaning of Statutory Terms","authors":["C Engel, RH McAdams - MPI Collective Goods Discussion Paper, 2024"],"snippet":"We report on our test of the Large Language Model (LLM) ChatGPT (GPT) as a tool for generating evidence of the ordinary meaning of statutory terms. We explain why the most useful evidence for interpretation involves a distribution of replies rather …","url":["https://pure.mpg.de/rest/items/item_3566108/component/file_3566109/content"]}
{"year":"2024","title":"Asking Questions Framework for Oral History Archives","authors":["J Švec, M Bulín, A Frémund, F Polák - European Conference on Information Retrieval, 2024"],"snippet":"… The resulting Wav2Vec 2.0 end-to-end model was combined with a lower-case four-gram language model estimated from CommonCrawl data. To decrease the model’s … The model was pre-trained on a self-supervised text-restoration task …","url":["https://link.springer.com/chapter/10.1007/978-3-031-56063-7_11"]}
{"year":"2024","title":"Assessing and Optimizing Large Language Models on Spondyloarthritis Multi-Choice Question Answering: Protocol for Enhancement and Assessment","authors":["A Wang, Y Wu, X Ji, X Wang, J Hu, F Zhang, Z Zhang… - JMIR Research Protocols, 2024"],"snippet":"Background Spondyloarthritis (SpA), a chronic inflammatory disorder, predominantly impacts the sacroiliac joints and spine, significantly escalating the risk of disability. SpA’s complexity, as evidenced by its diverse clinical presentations and symptoms …","url":["https://www.researchprotocols.org/2024/1/e57001"]}
{"year":"2024","title":"Assessing Task-Specific Performance Gains from Parameter-Efficient Fine-Tuning of Autoregressive Large Language Models","authors":["P Verdonk"],"snippet":"This study investigates the effectiveness and economic feasibility of fine-tuning Large Language Models (LLMs). With a focus on the open-source LLaMA-2 model of Touvron, Martin et al.(2023), Parameter-Efficient Fine-Tuning (PEFT) is used in …","url":["https://thesis.eur.nl/pub/73000/FV_Thesis_477745pv_MSc.pdf"]}
{"year":"2024","title":"ASSESSING THE IMPACT OF PROMPTING TECHNIQUES ON SHORT-TERM CURRICULUM DESIGN: A COMPARATIVE APPROACH","authors":["L Paz, M Berg, S Kreibich, D Werth - ICERI2024 Proceedings, 2024"],"snippet":"Since the public release of Large Language Models (LLMs) such as ChatGPT, the education landscape has witnessed groundbreaking innovations in personalized learning, automated content creation, and improved accessibility. Although previous …","url":["https://library.iated.org/view/PAZ2024ASS"]}
{"year":"2024","title":"Assessing the potential of leveraging LLaMA-2 to create an institute-specific online chatbot assistant.","authors":["L Werkman - 2024"],"snippet":"With the increasing popularity of chatbots such as ChatGPT, when faced with questions, people are getting more and more inclined to opt for a chatbot instead of browsing, calling, or travelling and waiting in line at service points. 8 To address this …","url":["https://www.diva-portal.org/smash/get/diva2:1886049/FULLTEXT01.pdf"]}
{"year":"2024","title":"Assessing the research landscape and clinical utility of large language models: a scoping","authors":["YJ Park, A Pillai, J Deng, E Guo, M Gupta, M Paget… - 2024"],"snippet":"… Introduced in November 2022, ChatGPT was trained using a large corpora of unlabelled text, including CommonCrawl, WebText, and Wikipedia, as well as internet-based book corpora spanning multiple languages [3]. GPT, along with other …","url":["https://bmcmedinformdecismak.biomedcentral.com/counter/pdf/10.1186/s12911-024-02459-6.pdf"]}
{"year":"2024","title":"Assessing the Role of Imagery in Multimodal Machine Translation","authors":["NK Motlagh, J Davis, T Anderson, J Gwinnup…"],"snippet":"… 2023), which comprises 12.8 million image-text pairs harvested from the Common Crawl (Common Crawl). The DataComp dataset serves as a foundation dataset for enhancing the training of CLIP models. We employ a CLIP ViT-B/32 model …","url":["https://www2.statmt.org/wmt24/pdf/2024.wmt-1.130.pdf"]}
{"year":"2024","title":"Assessment of beliefs and attitudes towards benzodiazepines using machine learning based on social media posts: an observational study","authors":["L de Anta, MÁ Alvarez-Mon, V Pereira-Sanchez… - BMC Psychiatry, 2024"],"snippet":"Benzodiazepines are frequently prescribed drugs; however, their prolonged use can lead to tolerance, dependence, and other adverse effects. Despite these risks, long-term use remains common, presenting a public health concern. This study aims to …","url":["https://bmcpsychiatry.biomedcentral.com/articles/10.1186/s12888-024-06111-5"]}
{"year":"2024","title":"ASSESSMENT OF HARMFULNESS OF INSTRUCTION-TUNED LARGE LANGUAGE MODEL LLAMA 2 BY SELF-EVALUATION","authors":["JJ Öberg - 2024"],"snippet":"The relatively recent introduction of public large language models like ChatGPT has raised numerous concerns regarding the ethical issues surrounding their application. Their general proficiency in performing natural language tasks, rivaling that of …","url":["https://www.diva-portal.org/smash/get/diva2:1894765/FULLTEXT01.pdf"]}
{"year":"2024","title":"Assisting Quality Assurance of Examination Tasks: Using a GPT Model and Bayesian Testing for Formative Assessment","authors":["N Willert, PK Würz - Computers and Education: Artificial Intelligence, 2024"],"snippet":"Formative quality assurance in the creation of examination tasks has always been an extremely time-consuming process. Especially due to the changing and short-lived content of computer science, new questions have to be created regularly, which in …","url":["https://www.sciencedirect.com/science/article/pii/S2666920X24001462"]}
{"year":"2024","title":"Association of Celtic Students","authors":["F Smith - 2024"],"snippet":"Technology is a vital part of language revitalisation and conversation. While certain languages have usable speech-to-text (STT; sometimes also called automatic speech recognition or ASR) models, this is not the case for most Celtic languages …","url":["https://www.researchgate.net/profile/Preben-Vangberg/publication/386137301_Speech-to-Text_for_Breton/links/6745efffa7fbc259f190195c/Speech-to-Text-for-Breton.pdf"]}
{"year":"2024","title":"Asymmetric Polysemous Reasoning for Image-Text Matching","authors":["H Zhang, M Yang - 2023 IEEE International Conference on Data Mining …, 2023"],"snippet":"Image-text matching has received growing interest since it bridges vision and language. The key challenge lies in how to learn correspondence between image and text. Upon observation, we find existing works suffer from two limitations. Firstly …","url":["https://ieeexplore.ieee.org/abstract/document/10411666/"]}
{"year":"2024","title":"Asynchronous Local-SGD Training for Language Modeling","authors":["B Liu, R Chhaparia, A Douillard, S Kale, AA Rusu… - arXiv preprint arXiv …, 2024"],"snippet":"Local stochastic gradient descent (Local-SGD), also referred to as federated averaging, is an approach to distributed optimization where each device performs more than one SGD update per communication. This work presents an empirical …","url":["https://arxiv.org/pdf/2401.09135"]}
{"year":"2024","title":"Atmospheric Limitations for High-frequency Ground-based Very Long Baseline Interferometry","authors":["DW Pesce, L Blackburn, R Chaves, SS Doeleman… - The Astrophysical Journal, 2024"],"snippet":"Very long baseline interferometry (VLBI) provides the highest-resolution images in astronomy. The sharpest resolution is nominally achieved at the highest frequencies, but as the observing frequency increases, so too does the atmospheric contribution …","url":["https://iopscience.iop.org/article/10.3847/1538-4357/ad3961"]}
{"year":"2024","title":"AtomGPT: Atomistic Generative Pre-trained Transformer for Forward and Inverse Materials Design","authors":["K Choudhary - arXiv preprint arXiv:2405.03680, 2024"],"snippet":"Large language models (LLMs) such as generative pretrained transformers (GPTs) have shown potential for various commercial applications, but their applicability for materials design remains underexplored. In this article, we introduce AtomGPT, a …","url":["https://arxiv.org/pdf/2405.03680"]}
{"year":"2024","title":"Auditing Large Language Models for Enhanced Text-Based Stereotype Detection and Probing-Based Bias Evaluation","authors":["Z Wu, S Bulathwela, M Perez-Ortiz, AS Koshiyama - arXiv preprint arXiv:2404.01768, 2024"],"snippet":"Recent advancements in Large Language Models (LLMs) have significantly increased their presence in human-facing Artificial Intelligence (AI) applications. However, LLMs could reproduce and even exacerbate stereotypical outputs from …","url":["https://arxiv.org/pdf/2404.01768"]}
{"year":"2024","title":"Augmenting a Spanish clinical dataset for transformer-based linking of negations and their out-of-scope references","authors":["AJ Tamayo-Herrera, DA Burgos, A Gelbukh - Natural Language Processing"],"snippet":"A negated statement consists of three main components: the negation cue, the negation scope, and the negation reference. The negation cue is the indicator of negation, while the negation scope defines the extent of the negation. The negation …","url":["https://www.cambridge.org/core/services/aop-cambridge-core/content/view/AD9F18ADEE45FA58A4041E059E111C52/S2977042424000104a.pdf/augmenting_a_spanish_clinical_dataset_for_transformerbased_linking_of_negations_and_their_outofscope_references.pdf"]}
{"year":"2024","title":"Augmenting Knowledge-Based Conversational Search Systems With Large Language Models","authors":["M Klettner"],"snippet":"Conversational interfaces are increasingly used by websites and apps, including office software as well as creativity tools. This trend reflects a shift towards natural language in human-computer interaction, which is also facilitated by utilizing Large …","url":["https://wwwmatthes.in.tum.de/file/kuo9al9qqe3h/Sebis-Public-Website/Student-Theses-Guided-Research/Current-Theses-Guided-Researches/Master-s-Thesis-Manuel-Klettner/Klettner_Manuel_MastersThesis.pdf"]}
{"year":"2024","title":"Automated Data Analytics: Combining Human Creativity and AI Power Using ChatGPT","authors":["S Sedkaoui - 2024"],"snippet":"The human mind is endowed with a remarkable capacity for creative synthesis between intuition and reason; this mental alchemy is the source of genius. A new synergy is emerging between human ingenuity and the computational capacity of …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=Ec8oEQAAQBAJ&oi=fnd&pg=PP1&dq=commoncrawl&ots=KEk-YTpP96&sig=tyBc_EAYFmXLs9KcLka0WJgHXy4"]}
{"year":"2024","title":"Automated Risk Analysis for Construction Contracts Using Neural Networks","authors":["K Hamdy, I AbdelRasheed, YAS Essawy… - Journal of Legal Affairs and …, 2024"],"snippet":"… for requiring less training time compared to previous recurrent neural architectures, such as long short-term memory (LSTM), and has been prevalently adopted for training large language models on large (language) data sets, such as the …","url":["https://ascelibrary.org/doi/abs/10.1061/JLADAH.LADR-1149"]}
{"year":"2024","title":"Automated Text Identification on Languages of the Iberian Peninsula: LLM and BERT-based Models Aggregation","authors":["G Gritsai, A Grabovoy - 2024"],"snippet":"This paper describes our solution approach for the IberAuTexTification (Automated Text Identification on Languages of the Iberian Peninsula) competition held as part of the IberLEF 2024 conference. Machinegenerated text fragments can be spotted in …","url":["https://ceur-ws.org/Vol-3756/IberAuTexTification2024_paper6.pdf"]}
{"year":"2024","title":"AutoMathText: Autonomous Data Selection with Language Models for Mathematical Texts","authors":["Y Zhang, Y Luo, Y Yuan, ACC Yao - arXiv preprint arXiv:2402.07625, 2024"],"snippet":"To improve language models' proficiency in mathematical reasoning via continual pretraining, we introduce a novel strategy that leverages base language models for autonomous data selection. Departing from conventional supervised fine-tuning or …","url":["https://arxiv.org/pdf/2402.07625"]}
{"year":"2024","title":"Automatic Coding of Contingency in Child-Caregiver Conversations","authors":["A Agrawal, M Nikolaus, B Favre, A Fourtassi - 2024"],"snippet":"One of the most important communicative skills children have to learn is to engage in meaningful conversations with people around them. At the heart of this learning lies the mastery of contingency, ie, the ability to contribute to an ongoing exchange …","url":["https://files.osf.io/v1/resources/hwnms/providers/osfstorage/65fc3931d09d170113eee760?action=download&direct&version=1"]}
{"year":"2024","title":"Automatic Control With Human-Like Reasoning: Exploring Language Model Embodied Air Traffic Agents","authors":["J Andriuškevičius, J Sun - arXiv preprint arXiv:2409.09717, 2024"],"snippet":"… Most of the data used to train leading-edge large language models, such as the latest Common Crawl dataset [5], which comprises over 250 billion web pages, sources information from publicly accessible internet sites. This extensive training …","url":["https://arxiv.org/pdf/2409.09717"]}
{"year":"2024","title":"Automatic Data Curation for Self-Supervised Learning: A Clustering-Based Approach","authors":["HV Vo, V Khalidov, T Darcet, T Moutakanni… - arXiv preprint arXiv …, 2024"],"snippet":"… By filtering Common Crawl data, the authors managed to obtain large datasets to train reliable … To this end, we apply our curation pipeline to two text pools based on Common Crawl. The first … Doing so keeps the original data distribution closer to …","url":["https://arxiv.org/pdf/2405.15613"]}
{"year":"2024","title":"Automatic detection of hate speech in code-mixed Indian languages in twitter social media interaction using DConvBLSTM-MuRIL ensemble method","authors":["P Kakati, D Dandotiya - Social Network Analysis and Mining, 2024"],"snippet":"… During the pre-training process, 2.5 terabytes of Common Crawl data in 100 languages are used. This model gives a much better performance than multilingual BERT when code-switching, especially for languages with little resources, because …","url":["https://link.springer.com/article/10.1007/s13278-024-01264-3"]}
{"year":"2024","title":"Automatic Ellipsis Reconstruction in Coordinated German Sentences Based on Text-to-Text Transfer Transformers","authors":["M Schmidt, K Harbusch, D Memmesheimer - International Conference on Text …, 2024"],"snippet":"Ellipsis reconstruction, ie, revealing omitted syntactically obligatory words in a sentence, is still a challenging task in Natural Language Processing (NLP) technologies, even though this information is essential for advanced human-computer …","url":["https://link.springer.com/chapter/10.1007/978-3-031-70563-2_14"]}
{"year":"2024","title":"Automatic Extraction of User-Centric Aspects for Tourist Spot Recommender Systems Using Reviews in Japanese","authors":["F Uwano, R Kobayashi, M Ohta - International Conference on Human-Computer …, 2024"],"snippet":"In tourist reviews, various pieces of information are described to confirm the characteristics of tourist spots. This paper proposes a method to extract tourist spot aspects using Japanese tourist reviews automatically. The aspects of tourist spots …","url":["https://link.springer.com/chapter/10.1007/978-3-031-60125-5_17"]}
{"year":"2024","title":"Automatic language ability assessment method based on natural language processing","authors":["N Nnamoko, T Karaminis, J Procter, J Barrowclough… - Natural Language …, 2024"],"snippet":"Background and Objectives: The Wechsler Abbreviated Scales of Intelligence second edition (WASI-II) is a standardised assessment tool that is widely used to assess cognitive ability in clinical, research, and educational settings. In one of the …","url":["https://www.sciencedirect.com/science/article/pii/S2949719124000426"]}
{"year":"2024","title":"Automatic Personality Recognition via XLNet with Refined Highway and Switching Module for Chatbot","authors":["OTC Chen, CH Tsai, MH Ha - 2024 IEEE International Symposium on Circuits and …, 2024"],"snippet":"This study introduces an Automatic Personality Recognition (APR) model, named XLNet refined-highway-switch network, comprising XLNet, refined highway units, a switching module, and a fully-connected layer. The pretrained XLNet is employed to …","url":["https://ieeexplore.ieee.org/abstract/document/10558116/"]}
{"year":"2024","title":"Automatic Pull Request Description Generation Using LLMs: A T5 Model Approach","authors":["MN Sakib, MA Islam, MM Arifin - arXiv preprint arXiv:2408.00921, 2024"],"snippet":"… One reason T5 excels at producing high-quality PR descriptions is its training on the diverse ”Colossal Clean Crawled Corpus” (C4), a cleaned and structured version of the Common Crawl web dump. The C4 dataset, which encompasses 250 …","url":["https://arxiv.org/pdf/2408.00921"]}
{"year":"2024","title":"Automatic Simplification of Lithuanian Administrative Texts","authors":["J Mandravickaitė, E Rimkienė, DK Kapkan… - Algorithms, 2024"],"snippet":"… These data were drawn from the public Common Crawl web scrape. Being pre-trained on multilingual data made mT5 model particularly … Multilingual Corpus: The model was pre-trained on CC25, which is a subset of the Common Crawl (CC) corpus that …","url":["https://www.mdpi.com/1999-4893/17/11/533"]}
{"year":"2024","title":"Automatic software product features extraction from software vendor documents","authors":["A Constantinou - 2024"],"snippet":"This project focuses on the automatic software features extraction from vendors' webpages and the consequent creation of a knowledge graph to accommodate these features. The use of LLMs for the classification of features is explored, through …","url":["https://studenttheses.uu.nl/bitstream/handle/20.500.12932/48264/Thesis_Report.pdf?sequence=1&isAllowed=y"]}
{"year":"2024","title":"Automatic Text Classification With Large Language Models: A Review of openai for Zero-and Few-Shot Classification","authors":["KL Anglin, C Ventura - Journal of Educational and Behavioral Statistics, 2024"],"snippet":"While natural language documents, such as intervention transcripts and participant writing samples, can provide highly nuanced insights into educational and psychological constructs, researchers often find these materials difficult and …","url":["https://journals.sagepub.com/doi/abs/10.3102/10769986241279927"]}
{"year":"2024","title":"Automatické vytváření souhrnů historických dokumentů","authors":["V Tran - 2024"],"snippet":"… The dataset is comprised of a large amount of cleaned English text extracted from Common Crawl … The results show that the pre-training has 1https://commoncrawl.org/ … It uses the same pretraining objective as BART and it uses a multilingual Common …","url":["https://dspace5.zcu.cz/bitstream/11025/57103/1/text_thesis.pdf"]}
{"year":"2024","title":"Automating Code Adaptation for MLOps--A Benchmarking Study on LLMs","authors":["H Patel, BA Ramanan, MA Khan, T Williams… - arXiv preprint arXiv …, 2024"],"snippet":"This paper explores the possibilities of the current generation of Large Language Models for incorporating Machine Learning Operations (MLOps) functionalities into ML training code bases. We evaluate the performance of OpenAI (gpt-3.5-turbo) and …","url":["https://arxiv.org/pdf/2405.06835"]}
{"year":"2024","title":"Automating String Encoding in AutoML","authors":["CH Lam"],"snippet":"Automated Machine Learning (AutoML) systems often struggle with data sets with string data. Due to their unstructured nature and dependence on domain knowledge, string data are a frequent cause of errors and coming up with generalized ways of …","url":["https://pure.tue.nl/ws/portalfiles/portal/319777301/Lam_C.pdf"]}
{"year":"2024","title":"Automation and Optimisation of Seo Content Gap Analysis Task with Semantic Clustering of Portuguese Search Keywords","authors":["IRVG Roque - 2024"],"snippet":"In the field of digital marketing, efficient content gap analysis is crucial for developing effective SEO strategies. Traditional approaches to this task are time-consuming, representing a challenge for Organic Performance teams, who must process large …","url":["https://search.proquest.com/openview/f1b7c0d75a5b02ef52133ceed6a94a0a/1?pq-origsite=gscholar&cbl=2026366&diss=y"]}
{"year":"2024","title":"Autonomous Data Selection with Language Models for Mathematical Texts","authors":["Y Zhang, Y Luo, Y Yuan, AC Yao - ICLR 2024 Workshop on Navigating and …, 2024"],"snippet":"To improve language models’ proficiency in mathematical reasoning via continual pretraining, we introduce a novel strategy that leverages base language models for autonomous data selection. Departing from conventional supervised fine-tuning or …","url":["https://openreview.net/pdf?id=bBF077z8LF"]}
{"year":"2024","title":"Autoregressive multimodal transformer for zero-shot sales forecasting of fashion products with exogenous data","authors":["M Rajendran, B Hong - Applied Intelligence, 2025"],"snippet":"Predicting future sales volumes of fashion industry products is challenging due to rapid market changes and limited historical sales data for recent products. As traditional forecasting methods and machine learning models often fail to address …","url":["https://link.springer.com/article/10.1007/s10489-024-05972-3"]}
{"year":"2024","title":"Autoregressive Pre-Training on Pixels and Texts","authors":["Y Chai, Q Liu, J Xiao, S Wang, Y Sun, H Wu - Proceedings of the 2024 Conference on …, 2024"],"snippet":"… a substantial refinement of the Common Crawl corpus. This dataset, derived from the extensive Common Crawl web scrape, undergoes … Common Crawl Common Crawl is a comprehensive web corpus that collects data from a variety of web pages …","url":["https://aclanthology.org/2024.emnlp-main.182.pdf"]}
{"year":"2024","title":"AutoScale: Automatic Prediction of Compute-optimal Data Composition for Training LLMs","authors":["F Kang, Y Sun, B Wen, S Chen, D Song, R Mahmood… - arXiv preprint arXiv …, 2024"],"snippet":"… With more compute, data sources with diverse examples, such as CommonCrawl, demonstrate continued reductions in training loss even at … With more compute, data sources with diverse examples, such as CommonCrawl, continue to reduce …","url":["https://arxiv.org/pdf/2407.20177"]}
{"year":"2024","title":"BA-LORA: BIAS-ALLEVIATING LOW-RANK ADAPTA-TION TO MITIGATE CATASTROPHIC INHERITANCE IN LARGE LANGUAGE MODELS","authors":["TTOMC INHERITANCE"],"snippet":"Large language models (LLMs) have demonstrated remarkable proficiency across various natural language processing (NLP) tasks. However, adapting LLMs to downstream applications requires computationally intensive and …","url":["https://openreview.net/pdf?id=d465apqCqc"]}
{"year":"2024","title":"Bachelor's Thesis","authors":["L Lamberti, C Biemann, HO Hatzel"],"snippet":"… We ran its script dedicated to gather articles from the Common Crawl news archive, limiting the set to only a few major German publishers, ranging in dates from 2020-2023. This should return more search results that might at first glance be …","url":["https://www.inf.uni-hamburg.de/en/inst/ab/lt/teaching/theses/completed-theses/2024-ba-lamberti.pdf"]}
{"year":"2024","title":"BACK TO THE ROOTS: TRACING SOURCE LANGUAGES IN WIKIPEDIA WITH LABSE","authors":["E Cupin, L Galiero, D Ciminari"],"snippet":"Our objective is to try and ascertain the plausible source language of Wikipedia articles on two domains, gastronomy and science, across five languages: Italian, English, Spanish, German, and French. Drawing upon the concept of text similarity …","url":["https://albarron.github.io/uploads/nlp23/dit_nlp23_finalproject_Cupin_Ciminari_Galiero.pdf"]}
{"year":"2024","title":"BadRAG: Identifying Vulnerabilities in Retrieval Augmented Generation of Large Language Models","authors":["J Xue, M Zheng, Y Hu, F Liu, X Chen, Q Lou - arXiv preprint arXiv:2406.00083, 2024"],"snippet":"Large Language Models (LLMs) are constrained by outdated information and a tendency to generate incorrect data, commonly referred to as \"hallucinations.\" Retrieval-Augmented Generation (RAG) addresses these limitations by combining …","url":["https://arxiv.org/pdf/2406.00083"]}
{"year":"2024","title":"BaichuanSEED: Sharing the Potential of ExtensivE Data Collection and Deduplication by Introducing a Competitive Large Language Model Baseline","authors":["G Dong, D Pan, Y Sun, S Zhang, Z Liang, X Wu… - arXiv preprint arXiv …, 2024"],"snippet":"… We collect 94 publicly available batches of CommonCrawl spanning the past decade. We construct our WARC extraction and processing pipeline, considering the effectiveness and cost of the WET and WARC formats. … https://commoncrawl.org …","url":["https://arxiv.org/pdf/2408.15079"]}
{"year":"2024","title":"Bailong: Bilingual Transfer Learning based on QLoRA and Zip-tie Embedding","authors":["LC Chen, ZR Li - arXiv preprint arXiv:2404.00862, 2024"],"snippet":"… Owing to computational constraints, we further conducted additional sampling of the OSCAR dataset and the Common Crawl dataset to mitigate the issue related to dataset size. In the long run, there are around 13 billion tokens left in the corpus. The …","url":["https://arxiv.org/html/2404.00862v1"]}
{"year":"2024","title":"Balanced Data Sampling for Language Model Training with Clustering","authors":["Y Shao, L Li, Z Fei, H Yan, D Lin, X Qiu - arXiv preprint arXiv:2402.14526, 2024"],"snippet":"Data plays a fundamental role in the training of Large Language Models (LLMs). While attention has been paid to the collection and composition of datasets, determining the data sampling strategy in training remains an open question. Most …","url":["https://arxiv.org/pdf/2402.14526"]}
{"year":"2024","title":"Balancing Multilingual Model Training Data Using Exponential Smoothing","authors":["D Kundu - 2023"],"snippet":"… The XLM-R [9] model is pre-trained over a larger common crawl corpus similarly to MBERT, using language sampling according to exponentially-smoothed language probabilities. Again, performance on low-resources tasks seems to benefit …","url":["https://ijsret.com/wp-content/uploads/2023/11/IJSRET_V9_issue6_417.pdf"]}
{"year":"2024","title":"BAM! Just Like That: Simple and Efficient Parameter Upcycling for Mixture of Experts","authors":["Q Zhang, N Gritsch, D Gnaneshwar, S Guo, D Cairuz… - Workshop on Efficient Systems for …"],"snippet":"Training Mixture of Experts (MoEs) from scratch in a large-scale regime is expensive. Previous work addresses this challenge by independently training multiple dense expert models and using them to initialize an MoE. In particular, initializing MoE …","url":["https://openreview.net/pdf?id=IfdVxuAHLr"]}
{"year":"2024","title":"Bangla Emergency Post Classification on Social Media using Transformer Based BERT Models","authors":["AA Nabil, D Das, MS Salim, S Arifeen, HMA Fattah - 2023 6th International …, 2023"],"snippet":"… It is a large multi-lingual language model trained on 2.5TB of filtered Common Crawl data. XLMRoBERTa is a multilingual model trained in 100 different languages. Unlike some XLM multilingual models, it does not require lang tensors to understand …","url":["https://ieeexplore.ieee.org/abstract/document/10427900/"]}
{"year":"2024","title":"Banned Books: Analysis of Censorship on Amazon. com","authors":["J Knockel, J Dałek, N Aljizawi, M Ahmed, L Meletti… - 2024"],"snippet":"… Common Crawl dataset. This sampling of products may be more likely to include hightrafficandlonger-livedproducts.Whilethismayevenbeadesirableproperty, there may also exist other biases introduced by sampling from the Common Crawl dataset …","url":["https://tspace.library.utoronto.ca/bitstream/1807/141434/1/Banned_Books.pdf"]}
{"year":"2024","title":"Basic Overview of the Components of the LLM Architectures","authors":["D Grigorov - Introduction to Python and Large Language Models: A …, 2024"],"snippet":"This chapter delves into the intricate components that constitute large language model (LLM) architectures. Understanding these elements is crucial for appreciating how LLMs transform raw textual data into meaningful, context-aware outputs. The …","url":["https://link.springer.com/chapter/10.1007/979-8-8688-0540-0_5"]}
{"year":"2024","title":"BeanCounter: A low-toxicity, large-scale, and open dataset of business-oriented text","authors":["S Wang, B Levy - arXiv preprint arXiv:2409.17827, 2024"],"snippet":"… We show that this data is indeed novel: less than 0.1% of BeanCounter appears in Common Crawl-based datasets and it is an order of magnitude larger than datasets relying on similar sources. Given the data’s provenance, we hypothesize …","url":["https://arxiv.org/pdf/2409.17827"]}
{"year":"2024","title":"Beauty Contest in Equity-Based Crowdfunding Campaigns","authors":["AA Trzebiński, Ł Kołodziejczyk - Journal of Alternative Finance, 2024"],"snippet":"Purpose This study investigates how investor sentiment influences equity-based crowdfunding campaigns outcomes, with a particular focus on sentiment related to specific industries. The motivation stems from the need to understand the …","url":["https://journals.sagepub.com/doi/abs/10.1177/27533743241303783"]}
{"year":"2024","title":"BeeManc at the PLABA Track of TAC-2023: Investigating LLMs and Controllable Attributes for Improving Biomedical Text Readability","authors":["Z Li, S Belkadi, N Micheletti, L Han, M Shardlow… - arXiv preprint arXiv …, 2024"],"snippet":"In this system report, we describe the models and methods we used for our participation in the PLABA2023 task on biomedical abstract simplification, part of the TAC 2023 tracks. The system outputs we submitted come from the following three …","url":["https://arxiv.org/pdf/2408.03871"]}
{"year":"2024","title":"Bella Turca: A Large-Scale Dataset of Diverse Text Sources for Turkish Language Modeling","authors":["D Altinok - International Conference on Text, Speech, and …, 2024"],"snippet":"… To meet the data requirements for language modeling, earlier large language models (LLMs) heavily relied on the Common Crawl dataset as their primary or sole source of training data [5, 26]. While training on the Common Crawl has proven …","url":["https://link.springer.com/chapter/10.1007/978-3-031-70563-2_16"]}
{"year":"2024","title":"Benchmarking Defeasible Reasoning with Large Language Models--Initial Experiments and Future Directions","authors":["I Tachmazidis, S Batsakis, G Antoniou - arXiv preprint arXiv:2410.12509, 2024"],"snippet":"Large Language Models (LLMs) have gained prominence in the AI landscape due to their exceptional performance. Thus, it is essential to gain a better understanding of their capabilities and limitations, among others in terms of nonmonotonic …","url":["https://arxiv.org/pdf/2410.12509"]}
{"year":"2024","title":"Benchmarking Large Language Models","authors":["D Ellison, C Van Buren, X Jiang, A Dholakia - … TPCTC 2023, Vancouver, BC, Canada, August …"],"snippet":"… It draws from an enormous training dataset including webpages (CommonCrawl), open-source repositories (GitHub), Wikipedia in 20 languages, books (Project Gutenberg), scientific papers (ArXiv), and questions and answers (Stack Exchange)[6] …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=MVojEQAAQBAJ&oi=fnd&pg=PA77&dq=commoncrawl&ots=MRcmnjR-nq&sig=7WmIzJDSkQtxqsJOkz1ZotlU7IE"]}
{"year":"2024","title":"Benchmarking LLM for Zero-day Vulnerabilities","authors":["M Lisha, V Agarwal, S Kamthania, P Vutkur, M Chari - 2024 IEEE International …, 2024"],"snippet":"Large Language Models (LLMs) have emerged as powerful tools for natural language processing tasks. This paper investigates the efficacy of various LLMs in detecting zero-day vulnerabilities, crucial for preemptive cybersecurity measures …","url":["https://ieeexplore.ieee.org/abstract/document/10677338/"]}
{"year":"2024","title":"Benchmarking LLM Guardrails in Handling Multilingual Toxicity","authors":["Y Yang, S Dan, D Roth, I Lee - arXiv preprint arXiv:2410.22153, 2024"],"snippet":"With the ubiquity of Large Language Models (LLMs), guardrails have become crucial to detect and defend against toxic content. However, with the increasing pervasiveness of LLMs in multilingual scenarios, their effectiveness in handling …","url":["https://arxiv.org/pdf/2410.22153"]}
{"year":"2024","title":"Benchmarking PathCLIP for Pathology Image Analysis","authors":["S Zheng, X Cui, Y Sun, J Li, H Li, Y Zhang, P Chen… - arXiv preprint arXiv …, 2024"],"snippet":"… All these versions are trained using masked language modeling and next-word prediction techniques with training data sourced from publicly available repositories like Wikipedia, Common Crawl. The results of LLaMA demonstrate that cuttingedge …","url":["https://arxiv.org/pdf/2401.02651"]}
{"year":"2024","title":"Benchmarking zero-shot stance detection with FlanT5-XXL: Insights from training data, prompting, and decoding strategies into its near-SoTA performance","authors":["R Aiyappa, S Senthilmani, J An, H Kwak, YY Ahn - arXiv preprint arXiv:2403.00236, 2024"],"snippet":"We investigate the performance of LLM-based zero-shot stance detection on tweets. Using FlanT5-XXL, an instruction-tuned open-source LLM, with the SemEval 2016 Tasks 6A, 6B, and P-Stance datasets, we study the performance and its variations …","url":["https://arxiv.org/pdf/2403.00236"]}
{"year":"2024","title":"BengaliLCP: A Dataset for Lexical Complexity Prediction in the Bengali Texts","authors":["N Ayman, MA Hossain, A Aziz, RU Faruqui, AN Chy - Proceedings of the 2024 Joint …, 2024"],"snippet":"Encountering intricate or ambiguous terms within a sentence produces distress for the reader during comprehension. Lexical Complexity Prediction (LCP) deals with predicting the complexity score of a word or a phrase considering its context. This …","url":["https://aclanthology.org/2024.lrec-main.200.pdf"]}
{"year":"2024","title":"BERGEN: A Benchmarking Library for Retrieval-Augmented Generation","authors":["D Rau, H Déjean, N Chirkova, T Formal, S Wang… - arXiv preprint arXiv …, 2024"],"snippet":"Retrieval-Augmented Generation allows to enhance Large Language Models with external knowledge. In response to the recent popularity of generative LLMs, many RAG approaches have been proposed, which involve an intricate number of …","url":["https://arxiv.org/pdf/2407.01102"]}
{"year":"2024","title":"BERT, RoBERTa or DeBERTa? Comparing Performance Across Transformer Models in Political Science Text","authors":["J Carreras Timoneda, S Vallejo Vera"],"snippet":"Transformer models such as BERT, RoBERTa, and DeBERTa have revolutionized the field of Natural Language Processing in recent years with substantial improvements in the contextual understanding of text. While political scientists have …","url":["https://www.journals.uchicago.edu/doi/pdf/10.1086/730737"]}
{"year":"2024","title":"BERT, RoBERTa or DeBERTa? Comparing Performance Across Transformers Models in Political Science Text","authors":["JC Timoneda, SV Vera"],"snippet":"Transformer models such as BERT, RoBERTa, and DeBERTa have revolutionized the field of Natural Language Processing in recent years with substantial improvements in the contextual understanding of text. While political scientists have …","url":["https://svallejovera.github.io/files/bert_roberta_jop.pdf"]}
{"year":"2024","title":"BERTicelli at HaSpeeDe 3: Fine-tuning and Cross-validating Large Language Models for Hate Speech Detection Leonardo Grotti¹², Patrick Quick¹ ¹Universiteit …","authors":["L Grotti¹ - EVALITA Proceedings of the Eighth Evaluation …, 2024"],"snippet":"The present paper describes the results from the experiments carried out for the HaSpeeDe 3 shared task, an Italian-language Hate Speech (HS) detection task, at EVALITA 2023. Two BERT-based language models were selected: UmBERTO (cased) …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=ZLfuEAAAQBAJ&oi=fnd&pg=PA188&dq=commoncrawl&ots=BBnDdqOBAj&sig=H6DFO9BmsqkOJQHbUMkZxiadwmA"]}
{"year":"2024","title":"BERTs are Generative In-Context Learners","authors":["D Samuel - arXiv preprint arXiv:2406.04823, 2024"],"snippet":"This paper explores the in-context learning capabilities of masked language models, challenging the common view that this ability does not 'emerge' in them. We present an embarrassingly simple inference technique that enables DeBERTa to operate as …","url":["https://arxiv.org/pdf/2406.04823"]}
{"year":"2024","title":"BEThiz: Precise and complete BERT model to fill out questions with correct answers, understanding the context for the Spanish language","authors":["I Zoukagh"],"snippet":"This article provides a research viewpoint on the training procedure of a Bidirectional Encoder Representations from Transformers (BERT) model starting from the beginning, employing the Tensor Processing Unit (TPU), with a particular …","url":["https://www.techrxiv.org/doi/pdf/10.36227/techrxiv.173152909.93080264"]}
{"year":"2024","title":"Better Alignment with Instruction Back-and-Forth Translation","authors":["T Nguyen, J Li, S Oh, L Schmidt, J Weston… - arXiv preprint arXiv …, 2024"],"snippet":"We propose a new method, instruction back-and-forth translation, to construct high-quality synthetic data grounded in world knowledge for aligning large language models (LLMs). Given documents from a web corpus, we generate and curate synthetic instructions …","url":["https://arxiv.org/pdf/2408.04614"]}
{"year":"2024","title":"Beware of Calibration Data for Pruning Large Language Models","authors":["Y Ji, Y Xiang, J Li, Q Xia, P Li, X Duan, Z Wang… - arXiv preprint arXiv …, 2024"],"snippet":"… It includes 2.6T tokens extracted from Common Crawl. We sample from a subset5 of the DCLM. … C4 and Slimpajama, which are also extracted from Common Crawl, perform slightly worse. In contrast, the source of Wikipedia differs significantly from …","url":["https://arxiv.org/pdf/2410.17711"]}
{"year":"2024","title":"Beyond Lexical Boundaries: LLM-Generated Text Detection for Romanian Digital Libraries","authors":["M Nitu, M Dascalu - Future Internet, 2024"],"snippet":"Machine-generated content reshapes the landscape of digital information; hence, ensuring the authenticity of texts within digital libraries has become a paramount concern. This work introduces a corpus of approximately 60 k Romanian documents …","url":["https://www.mdpi.com/1999-5903/16/2/41"]}
{"year":"2024","title":"Beyond Metrics: Evaluating LLMs' Effectiveness in Culturally Nuanced, Low-Resource Real-World Scenarios","authors":["M Ochieng, V Gumma, S Sitaram, J Wang, K Ronen… - arXiv preprint arXiv …, 2024"],"snippet":"The deployment of Large Language Models (LLMs) in real-world applications presents both opportunities and challenges, particularly in multilingual and code-mixed communication settings. This research evaluates the performance of seven leading …","url":["https://arxiv.org/pdf/2406.00343"]}
{"year":"2024","title":"Beyond Perplexity: Multi-dimensional Safety Evaluation of LLM Compression","authors":["Z Xu, A Gupta, T Li, O Bentham, V Srikumar - arXiv preprint arXiv:2407.04965, 2024"],"snippet":"Large language models (LLMs) are increasingly deployed in real-world scenarios with the help of recent model compression techniques. Such momentum towards local deployment means the use of compressed LLMs will widely impact a large …","url":["https://arxiv.org/pdf/2407.04965"]}
{"year":"2024","title":"Beyond Scale: The Diversity Coefficient as a Data Quality Metric for Variability in Natural Language Data","authors":["A Lee, B Miranda, S Sundar, A Casasola, S Koyeyo"],"snippet":"… Since many datasets are publicly available (eg Common Crawl, Wikipedia), data used to train new models may be curated from such … We evaluate on Pile-CC (Pile Common Crawl) and OpenWebText2 since those datasets align with intuitively …","url":["https://openreview.net/pdf?id=tgkWxsOapD"]}
{"year":"2024","title":"Beyond Technology. Our New Life with IT","authors":["J Müller - Turning Point, 2024"],"snippet":"… A publicly available data repository measured in many petabytes (1 petabyte = 1 million gigabytes) is Common Crawl. It is provided free of charge by Amazon Web Services to anyone who needs data for training purposes for AI. In the context of very …","url":["https://link.springer.com/chapter/10.1007/978-3-658-46079-2_1"]}
{"year":"2024","title":"Beyond the Black Box: Optimization Within Latent Spaces","authors":["V Kishore - 2024"],"snippet":"… We compute b using Common Crawl monolingual datasets.For each language and contextual embedding model, we create 1M candidate-reference pairs by grouping two random sentences. Because of the random pairing and the corpus …","url":["https://search.proquest.com/openview/493a2e2eef54f228bc2976f8d6e64067/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
{"year":"2024","title":"Beyond Words: Sentiment Analysis of Croatian Language Attitudes","authors":["B Kovacic, A Brnjakovic, G Thakkar"],"snippet":"Sociolinguistic research can benefit heavily from natural language processing (NLP) tools. Especially language attitude research can be facilitated by using sentiment analysis. By using existing tools for Bosnian-Croatian-Montenegrin-Serbian (BCMS) …","url":["https://archive.ceciis.foi.hr/public/conferences/2024/Proceedings/S6/S6P2.pdf"]}
{"year":"2024","title":"BharatBhasaNet-A unified framework to identify Indian code mix Languages","authors":["S Dey, S Thakur, A Kandwal, R Kumar, S Dasgupta… - IEEE Access, 2024"],"snippet":"In the rapidly globalizing digital communication sphere, the imperative for advanced multilingual text recognition and identification is increasingly evident. Contrasting the previous works, which were predominantly constrained to 2-3 languages, this …","url":["https://ieeexplore.ieee.org/iel7/6287639/6514899/10517602.pdf"]}
{"year":"2024","title":"BhashaVerse: Translation Ecosystem for Indian Subcontinent Languages","authors":["V Mujadia, DM Sharma - arXiv preprint arXiv:2412.04351, 2024"],"snippet":"… 2019b) mined from Wikipedia and CommonCrawl offer valuable data for pre-processing pipelines. Other notable resources include the Nepali National Corpus (Yadavaetal. 2008), the Kathmandu University English-Nepali Parallel Corpus (Duwal and Bal …","url":["https://arxiv.org/pdf/2412.04351"]}
{"year":"2024","title":"Bi-directional GRU-Based Approach for Multi-Class Text Error Identification System","authors":["S Reeha, BV Nikith, GMP Reddy, PB Pati - 2024 IEEE 9th International Conference …, 2024"],"snippet":"… The C4 dataset, utilized in this study, is an extensively cleaned and curated version of Common Crawl's web crawl corpus. Common Crawl is a publicly available dataset accessible at commoncrawl.org. and boasting over 700 million …","url":["https://ieeexplore.ieee.org/abstract/document/10543361/"]}
{"year":"2024","title":"BIAS ASSESSMENT IN LARGE LANGUAGE MODELS","authors":["F ASLAN"],"snippet":"The introduction of Large Language Models (LLMs) such as Chat-GPT has transformed the field of natural language processing, providing exceptional capabilities in text generation and comprehension. However, these models have …","url":["http://arno.uvt.nl/show.cgi?fid=170714"]}
{"year":"2024","title":"Bias in LLMs for High-Stakes Recommendations: An Analysis of BERT-Family Architectures with Varied Fine-Tuning Configurations","authors":["N Degelin"],"snippet":"… This chapter explained the mechanisms behind LLMs, including their training with extensive data sources like Common Crawl and the role of tokenization. It covered how fine-tuning improves LLMs for specific tasks using methods such as sequence …","url":["https://www.researchgate.net/profile/Nisse_Degelin/publication/385776127_Bias_in_LLMs_for_High-Stakes_Recommendations_An_Analysis_of_BERT-Family_Architectures_with_Varied_Fine-Tuning_Configurations/links/6734ad60a78ba469f060a5d1/Bias-in-LLMs-for-High-Stakes-Recommendations-An-Analysis-of-BERT-Family-Architectures-with-Varied-Fine-Tuning-Configurations.pdf"]}
{"year":"2024","title":"Bias-Aware Low-Rank Adaptation: Mitigating Catastrophic Inheritance of Large Language Models","authors":["Y Chang, Y Chang, Y Wu - arXiv preprint arXiv:2408.04556, 2024"],"snippet":"Large language models (LLMs) have exhibited remarkable proficiency across a diverse array of natural language processing (NLP) tasks. However, adapting LLMs to downstream applications typically necessitates computationally intensive and …","url":["https://arxiv.org/pdf/2408.04556"]}
{"year":"2024","title":"BiasMirror: Towards Mitigating Implicit Bias","authors":["K Brohman, A Khan, T Fu, R Mukkamala, A Baiyere - 2024"],"snippet":"This research-in-progress study attends to the issue of implicit bias, which underlies discriminatory attitudes and behaviors that people may not be aware that they hold. Specifically in the context of performance evaluations, attending to such bias is …","url":["https://aisel.aisnet.org/icis2024/soc_impactIS/soc_impactIS/21/"]}
{"year":"2024","title":"Big City Bias: Evaluating the Impact of Metropolitan Size on Computational Job Market Abilities of Language Models","authors":["C Campanella, R van der Goot - arXiv preprint arXiv:2403.08046, 2024"],"snippet":"Large language models (LLMs) have emerged as a useful technology for job matching, for both candidates and employers. Job matching is often based on a particular geographic location, such as a city or region. However, LLMs have known …","url":["https://arxiv.org/pdf/2403.08046"]}
{"year":"2024","title":"BigDocs: An Open and Permissively-Licensed Dataset for Training Multimodal Models on Document and Code Tasks","authors":["JA Rodriguez, X Jian, SS Panigrahi, T Zhang, A Feizi… - Workshop on Responsibly …"],"snippet":"Multimodal AI has the potential to significantly enhance document-understanding tasks, such as processing receipts, understanding workflows, extracting data from documents, and summarizing reports. Code generation tasks that require long-structured …","url":["https://openreview.net/pdf?id=UTgNFcpk0j"]}
{"year":"2024","title":"Bilingual Adaptation of Monolingual Foundation Models","authors":["G Gosal, Y Xu, G Ramakrishnan, R Joshi, A Sheinin… - … on Foundation Models in the Wild"],"snippet":"We present an efficient method for adapting a monolingual Large Language Model (LLM) to another language, addressing challenges of catastrophic forgetting and tokenizer limitations. We focus this study on adapting Llama 2 to Arabic. Our two-stage …","url":["https://openreview.net/pdf?id=XfA4HYYGLz"]}
{"year":"2024","title":"Bilingual Propaganda Detection in Diplomats' Tweets Using Language Models and Linguistic Features","authors":["A Modzelewski, P Golik, A Wierzbicki - IberLEF@ SEPLN, 2024"],"snippet":"Our study presents an approach to a shared task of propaganda identification and characterization at the DIPROMATS 2024 hosted by the Iberian Languages Evaluation Forum. As the DSHacker team, we participated in the propaganda …","url":["https://ceur-ws.org/Vol-3756/DIPROMATS2024_paper1.pdf"]}
{"year":"2024","title":"Binary Battle: Leveraging Machine Learning and Transfer Learning Models to Distinguish between Conspiracy Theories and Critical Thinking","authors":["S Mahesh, S Divakaran, K Girish, HL Shashirekha - 2024"],"snippet":"In the context of automatic content moderation Natural Language Processing (NLP) has a complex task when it comes to distinguishing between conspiracy theories and critical thinking. While conspiracy theories present complex narratives …","url":["https://ceur-ws.org/Vol-3740/paper-266.pdf"]}
{"year":"2024","title":"BioBridge: Unified Bio-Embedding with Bridging Modality in Code-Switched EMR.","authors":["J Jeon, S Cho, D Lee, C Lee, J Kim - IEEE Access, 2024"],"snippet":"Pediatric Emergency Department (PED) overcrowding presents a significant global challenge, prompting the need for efficient solutions. This paper introduces the BioBridge framework, a novel approach that applies Natural Language Processing (NLP) …","url":["https://ieeexplore.ieee.org/iel8/6287639/6514899/10693433.pdf"]}
{"year":"2024","title":"Bioeconomy firms and where to find them","authors":["L Kriesch, S Losacker - REGION, 2024"],"snippet":"… This dataset uses the open-source web repository CommonCrawl to identify German company websites and has proven to be a valuable database for spatial research. From this data, we identify bioeconomy firms using a combination of …","url":["https://openjournals.wu-wien.ac.at/ojs/index.php/region/article/view/523/456"]}
{"year":"2024","title":"BioMedLM: A 2.7 B Parameter Language Model Trained On Biomedical Text","authors":["E Bolton, A Venigalla, M Yasunaga, D Hall, B Xiong… - arXiv preprint arXiv …, 2024"],"snippet":"… The Pile contains multiple sub-corpora, including general content from Common Crawl and specialized content like PubMed, Github, and FreeLaw. This model serves as an important baseline for comparison with our domain-specific models; …","url":["https://arxiv.org/pdf/2403.18421"]}
{"year":"2024","title":"BIS Papers","authors":["I Aldasoro, S Doerr, L Gambacorta, S Notra, T Oliviero… - 2024","L Gambacorta, V Shreeti - 2025"],"snippet":"The rapid advancement of artificial intelligence (AI) relies on a complex supply chain comprising five key layers: hardware, cloud infrastructure, training data, foundation models and AI applications. This paper examines the market structure of each layer …","url":["https://www.bis.org/publ/bppdf/bispap145.pdf","https://www.bis.org/publ/bppdf/bispap154.pdf"]}
{"year":"2024","title":"BLEnD: A Benchmark for LLMs on Everyday Knowledge in Diverse Cultures and Languages","authors":["J Myung, N Lee, Y Zhou, J Jin, RA Putri, D Antypas… - arXiv preprint arXiv …, 2024"],"snippet":"… [21] introduce a methodology to extract large-scale cultural commonsense knowledge from the Common Crawl corpus on geography, religion, and occupations. CREHate [16] is a cross-cultural English hate speech dataset covering annotations …","url":["https://arxiv.org/pdf/2406.09948"]}
{"year":"2024","title":"Blind Baselines Beat Membership Inference Attacks for Foundation Models","authors":["D Das, J Zhang, F Tramèr - arXiv preprint arXiv:2406.16201, 2024"],"snippet":"… More precisely, these benchmarks introduce two datasets, CommonPool and DCLM-POOL, which contain respectively 12.8 billion image-text pairs and 240 trillion text tokens sampled from Common Crawl. To enable experiments at …","url":["https://arxiv.org/pdf/2406.16201"]}
{"year":"2024","title":"BlockLLM: Memory-Efficient Adaptation of LLMs by Selecting and Optimizing the Right Coordinate Blocks","authors":["AV Ramesh, V Ganapathiraman, IH Laradji, M Schmidt - arXiv preprint arXiv …, 2024"],"snippet":"… The C4 dataset is a large-scale, cleaned version of the Common Crawl web corpus used for pre-training language models, featuring diverse and high-quality text from the internet. Our experiment setup is similar to [34], following the setup from …","url":["https://arxiv.org/pdf/2406.17296"]}
{"year":"2024","title":"Boost Large Language Model Performance through Self-Training with Reward Guided Tree Search","authors":["J Hargreaves, E Fairweather, O Bellingham - 2024"],"snippet":"Large language models have changed the field of natural language processing by enabling sophisticated language generation tasks, yet there remains a persistent challenge in enhancing their performance through autonomous learning …","url":["https://essopenarchive.org/doi/pdf/10.22541/au.172116715.57325819"]}
{"year":"2024","title":"Botlitica: A generative AI-based tool to assist journalists in navigating political propaganda campaigns","authors":["E Musi, EEG Aguilar, L Federico - Studies in Communication Sciences, 2024"],"snippet":"The hype on generative AI has raised concerns about the spread of disinformation but also opened up new opportunities for hybrid journalism. The proliferation of political propaganda campaigns spread across digital media during election periods …","url":["https://www.hope.uzh.ch/scoms/article/download/4270/4464"]}
{"year":"2024","title":"BOTS-LM: Training Large Language Models for Setswana","authors":["N Brown, V Marivate - arXiv preprint arXiv:2408.02239, 2024"],"snippet":"In this work we present BOTS-LM, a series of bilingual language models proficient in both Setswana and English. Leveraging recent advancements in data availability and efficient fine-tuning, BOTS-LM achieves performance similar to models …","url":["https://arxiv.org/pdf/2408.02239"]}
{"year":"2024","title":"Brain Rush","authors":["P Cohan"],"snippet":"… LLM developers could tap free data libraries – such as the Common Crawl repository of web data – supplemented by licensing foreign-language …","url":["https://link.springer.com/content/pdf/10.1007/979-8-8688-0318-5.pdf"]}
{"year":"2024","title":"Branch-Train-MiX: Mixing Expert LLMs into a Mixture-of-Experts LLM","authors":["S Sukhbaatar, O Golovneva, V Sharma, H Xu, XV Lin… - arXiv preprint arXiv …, 2024"],"snippet":"We investigate efficient methods for training Large Language Models (LLMs) to possess capabilities in multiple specialized domains, such as coding, math reasoning and world knowledge. Our method, named Branch-Train-MiX (BTX), starts …","url":["https://arxiv.org/pdf/2403.07816"]}
{"year":"2024","title":"Breaking the Ceiling of the LLM Community by Treating Token Generation as a Classification for Ensembling","authors":["YC Yu, CC Kuo, Z Ye, YC Chang, YS Li - arXiv preprint arXiv:2406.12585, 2024"],"snippet":"Ensembling multiple models has always been an effective approach to push the limits of existing performance and is widely used in classification tasks by simply averaging the classification probability vectors from multiple classifiers to achieve …","url":["https://arxiv.org/pdf/2406.12585"]}
{"year":"2024","title":"Breaking the Curse of Multilinguality with Cross-lingual Expert Language Models","authors":["T Blevins, T Limisiewicz, S Gururangan, M Li, H Gonen… - arXiv preprint arXiv …, 2024"],"snippet":"Despite their popularity in non-English NLP, multilingual language models often underperform monolingual ones due to inter-language competition for model parameters. We propose Cross-lingual Expert Language Models (X-ELM), which …","url":["https://arxiv.org/pdf/2401.10440"]}
{"year":"2024","title":"Breaking the Programming Language Barrier: Multilingual Prompting to Empower Non-Native English Learners","authors":["J Prather, BN Reeves, P Denny, J Leinonen, S MacNeil… - arXiv preprint arXiv …, 2024"],"snippet":"… than 1% of the language distribution available in Common Crawl2 (an open repository of web crawl data that makes up a significant portion of the training data for many LLMs), whereas Chinese is one of the most common languages in the …","url":["https://arxiv.org/pdf/2412.12800"]}
{"year":"2024","title":"Brevity is the soul of wit: Pruning long files for code generation","authors":["AK Singh, Y Yang, K Tirumala, M Elhoushi, AS Morcos - arXiv preprint arXiv …, 2024"],"snippet":"Data curation is commonly considered a \"secret-sauce\" for LLM training, with higher quality data usually leading to better LLM performance. Given the scale of internet-scraped corpora, data pruning has become a larger and larger focus. Specifically, many have …","url":["https://arxiv.org/pdf/2407.00434"]}
{"year":"2024","title":"Bridging large language model disparities: Skill tagging of multilingual educational content","authors":["Y Kwak, ZA Pardos - British Journal of Educational Technology, 2024"],"snippet":"The adoption of large language models (LLMs) in education holds much promise. However, like many technological innovations before them, adoption and access can often be inequitable from the outset, creating more divides than they bridge. In …","url":["https://bera-journals.onlinelibrary.wiley.com/doi/pdf/10.1111/bjet.13465"]}
{"year":"2024","title":"Bridging the Bosphorus: Advancing Turkish Large Language Models through Strategies for Low-Resource Language Adaptation and Benchmarking","authors":["EC Acikgoz, M Erdogan, D Yuret - arXiv preprint arXiv:2405.04685, 2024"],"snippet":"… This dataset was generated by extracting content from 71 monthly snapshots of the internet via Common Crawl (CC). CulturaX contains version … However, the diversity of these datasets should be sufficient, including common crawl, book …","url":["https://arxiv.org/pdf/2405.04685"]}
{"year":"2024","title":"Bridging the Data Provenance Gap Across Text, Speech and Video","authors":["S Longpre, N Singh, M Cherep, K Tiwary… - arXiv preprint arXiv …, 2024"],"snippet":"Progress in AI is driven largely by the scale and quality of training data. Despite this, there is a deficit of empirical analysis examining the attributes of well-established datasets beyond text. In this work we conduct the largest and first-of-its-kind …","url":["https://arxiv.org/pdf/2412.17847"]}
{"year":"2024","title":"Browsing and Searching Metadata of TREC","authors":["T Breuer, EM Voorhees, I Soboroff - Proceedings of the 47th International ACM SIGIR …, 2024"],"snippet":"Information Retrieval (IR) research is deeply rooted in experimentation and evaluation, and the Text REtrieval Conference (TREC) has been playing a central role in making that possible since its inauguration in 1992. TREC's mission centers …","url":["https://dl.acm.org/doi/abs/10.1145/3626772.3657873"]}
{"year":"2024","title":"Build a Large Language Model (From Scratch)","authors":["S Raschka - 2024"],"snippet":"… For context, consider the size of the CommonCrawl dataset, which alone consists of 410 billion tokens and requires about 570 GB of storage. In comparison, later iterations of models like GPT-3, such as Meta’s LLaMA, have expanded their training scope to …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=uSUmEQAAQBAJ&oi=fnd&pg=PA1&dq=commoncrawl&ots=5B8k6_EtVn&sig=ozDubtqfTPHnCHQ2f-ctPtkU8Mc"]}
{"year":"2024","title":"Building a Large Japanese Web Corpus for Large Language Models","authors":["N Okazaki, K Hattori, H Shota, H Iida, M Ohi, K Fujii… - arXiv preprint arXiv …, 2024"],"snippet":"… The corpus developed in this study is made from 21 snapshots of Common Crawl (from CC-MAIN-2020-40 to CC-MAIN-2023-23), and the size of the corpus after cleaning is 173,350,375 pages and 312,093,428,689 characters. To confirm the …","url":["https://arxiv.org/pdf/2404.17733"]}
{"year":"2024","title":"Building a Specialized ChatGpt-Like System","authors":["MB Riyadh, MKI Eddine, MB Nassim"],"snippet":"… be examined, which was sampled from a mix primarily made up of the Common Crawl dataset [11]. This dataset is large enough to train the … This means that Common Crawl and Books2 datasets are sampled less than once during training …","url":["https://www.researchgate.net/profile/Nassim-Boudjenah/publication/381996102_Building_a_Specialized_ChatGpt-Like_System/links/668716052aa57f3b826eafb4/Building-a-Specialized-ChatGpt-Like-System.pdf"]}
{"year":"2024","title":"Building and AI Chatbot using LLM","authors":["I Goswami, D Gupta - 2024"],"snippet":"In our digital world, where communication is key, the emergence of AI-powered chatbots has revolutionized the way we interact with technology. This project delves into the development of an AI chatbot utilizing Large Language Models (LLM), a …","url":["http://www.ir.juit.ac.in:8080/jspui/bitstream/123456789/11451/1/Building%20and%20AI%20Chatbot%20using%20LLM.pdf"]}
{"year":"2024","title":"Building and better understanding vision-language models: insights and future directions","authors":["H Laurençon, A Marafioti, V Sanh, L Tronchon - arXiv preprint arXiv:2408.12637, 2024"],"snippet":"The field of vision-language models (VLMs), which take images and texts as inputs and output texts, is rapidly evolving and has yet to reach consensus on several key aspects of the development pipeline, including data, architecture, and training …","url":["https://arxiv.org/pdf/2408.12637"]}
{"year":"2024","title":"Building and Running Large-Scale Language Models: The Infrastructure and Techniques Behind GPT-4","authors":["DC Youvan - 2024"],"snippet":"… o Common Crawl: One of the primary sources for large-scale training datasets is Common Crawl, which is an open repository of web data collected by crawling the internet. Common Crawl provides a vast amount of diverse text from websites, blogs …","url":["https://www.researchgate.net/profile/Douglas-Youvan/publication/384398902_Building_and_Running_Large-Scale_Language_Models_The_Infrastructure_and_Techniques_Behind_GPT-4/links/66f6f4d3906bca2ac3d20e68/Building-and-Running-Large-Scale-Language-Models-The-Infrastructure-and-Techniques-Behind-GPT-4.pdf"]}
{"year":"2024","title":"Building Better Datasets: Seven Recommendations for Responsible Design from Dataset Creators","authors":["W Orr, K Crawford - arXiv preprint arXiv:2409.00252, 2024"],"snippet":"The increasing demand for high-quality datasets in machine learning has raised concerns about the ethical and responsible creation of these datasets. Dataset creators play a crucial role in developing responsible practices, yet their …","url":["https://arxiv.org/pdf/2409.00252"]}
{"year":"2024","title":"Building on Efficient Foundations: Effectively Training LLMs with Structured Feedforward Layers","authors":["X Wei, S Moalla, R Pascanu, C Gulcehre - arXiv preprint arXiv:2406.16450, 2024"],"snippet":"… Dataset We use the RefinedWeb dataset [44], a carefully curated subset of CommonCrawl, processed for optimal filtering and deduplication. It provides 600B tokens available for public use. As it is a substantial dataset, we shuffle, extract, and …","url":["https://arxiv.org/pdf/2406.16450"]}
{"year":"2024","title":"Building Question-Answer Data Using Web Register Identification","authors":["A Eskelinen, A Myntti, E Henriksson, S Pyysalo… - Proceedings of the 2024 …, 2024"],"snippet":"… (2015), is a corpus of Finnish collected between 2015 and 2016 from Common Crawl and by crawling .fi domains. As all of these resources are Common Crawl based, in the post-processing stage we make sure that duplicate QA pairs are …","url":["https://aclanthology.org/2024.lrec-main.234.pdf"]}
{"year":"2024","title":"Building Test Collections for Japanese Dense Information Retrieval Technologies and Beyond","authors":["H Joho, A Keyaki, Y Tachioka, S Yamamoto - 2024"],"snippet":"This paper presents the NTCIR Transfer Task, a series of evaluations aimed at advancing dense information retrieval technologies for non-English languages, particularly Japanese. While dense retrieval methods have shown significant …","url":["https://ceur-ws.org/Vol-3854/emtcir-4.pdf"]}
{"year":"2024","title":"By Senior Judge Stephanie Domitrovich and Judge Herbert B. Dixon Jr.","authors":["CJJ Federal Judiciary - Judges Journal, 2024"],"snippet":"… For example, the datasets used to train ChatGPT 3 included text from the following sources: (1) Common Crawl, containing petabytes of data collected from the internet since 2008; (2) WebText2, text from webpages with highly ranked Reddit …","url":["https://heinonline.org/hol-cgi-bin/get_pdf.cgi?handle=hein.journals/judgej63&section=3"]}
{"year":"2024","title":"Bye-bye Bias: What to Consider When Training Generative AI Models on Subjective Marketing Metrics","authors":["C Schamp - 2024"],"snippet":"… However, these models are trained on vast data sets scraped from the Internet, such as Common Crawl or LAION, that contain little information on the types of perceptual measures marketing is often interested in, such as perceived brand …","url":["https://sciendo.com/pdf/10.2478/nimmir-2024-0007"]}
{"year":"2024","title":"Byte Latent Transformer: Patches Scale Better Than Tokens","authors":["A Pagnoni, R Pasunuru, P Rodriguez, J Nguyen… - arXiv preprint arXiv …, 2024"],"snippet":"We introduce the Byte Latent Transformer (BLT), a new byte-level LLM architecture that, for the first time, matches tokenization-based LLM performance at scale with significant improvements in inference efficiency and robustness. BLT encodes bytes …","url":["https://arxiv.org/pdf/2412.09871"]}
{"year":"2024","title":"Cache Me If You Can: The Case For Retrieval Augmentation in Federated Learning","authors":["A Muhamed, P Thaker, MT Diab, V Smith - Privacy Regulation and Protection in Machine …"],"snippet":"We propose retrieval augmentation (RA) as an enhancement to federated learning (FL) that can improve privacy protection and ensure regulatory compliance. FL, primarily designed for data privacy preservation, faces challenges with conventional …","url":["https://openreview.net/pdf?id=MKd1SkDbbz"]}
{"year":"2024","title":"CAM 2.0: End-to-End Open Domain Comparative Question Answering System","authors":["A Shallouf, H Herasimchyk, M Salnikov, RG Veliz…"],"snippet":"… After extracting objects and aspects, we look for their matches in the Common Crawl text. It is also important to mention, that for the final … (lemmatized) corpus containing 14.3 billion English sentences from the Common Crawl. To retrieve …","url":["https://www.inf.uni-hamburg.de/en/inst/ab/lt/publications/2024-nikishina-cam2.pdf"]}
{"year":"2024","title":"CamelEval: Advancing Culturally Aligned Arabic Language Models and Benchmarks","authors":["Z Qian, F Altam, MSS Alqurishi, R Souissi - arXiv preprint arXiv:2409.12623, 2024"],"snippet":"Large Language Models (LLMs) are the cornerstones of modern artificial intelligence systems. This paper introduces Juhaina, a Arabic-English bilingual LLM specifically designed to align with the values and preferences of Arabic speakers …","url":["https://arxiv.org/pdf/2409.12623"]}
{"year":"2024","title":"Can AI Help with Your Personal Finances?","authors":["O Hean, U Saha, B Saha"],"snippet":"In recent years, Large Language Models (LLMs) have emerged as a transformative development in artificial intelligence (AI), drawing significant attention from industry and academia. Trained on vast datasets, these sophisticated AI systems exhibit …","url":["https://www.researchgate.net/profile/Oudom-Hean/publication/387273435_Can_AI_Help_with_Your_Personal_Finances/links/676608bafb9aff6eaae3e232/Can-AI-Help-with-Your-Personal-Finances.pdf"]}
{"year":"2024","title":"Can Bias in LLMs be Used for Good?","authors":["FL Wortzman"],"snippet":"It is a well-known fact that LLMs express harmful biases in their predictions. The main source comes from the training datasets, which are too large and expensive to check thoroughly. In my submission, I explore how we can leverage the bias in LLMs …","url":["https://aiequalitytoolbox.com/wp-content/uploads/2024/10/10-Can-bias-in-LLMs-be-used-for-good.pdf"]}
{"year":"2024","title":"Can ChatGPT learn Chinese or Swahili? Considering how large language models might act differently if trained in different languages.","authors":["N Savage"],"snippet":"… Thien Nguyen, a professor of computer science at the University of Oregon, looked at the CommonCrawl corpus, a selection of text scraped … Then, because only a small percentage of the CommonCrawl corpus is in Korean, the company …","url":["https://dl.acm.org/doi/full/10.1145/3640351"]}
{"year":"2024","title":"Can ChatGPT Plan Your Retirement?: Generative AI andFinancial Advice","authors":["AW Lo, J Ross"],"snippet":"We identify some of the most pressing issues facing the adoption of large language models (LLMs) in practical settings, and propose a research agenda to reach the next technological inflection point in generative AI. We focus on three challenges …","url":["https://assets.pubpub.org/z7x033cz/Lo%20&%20Ross%20(2024)_Just%20Accepted-01717176710726.pdf"]}
{"year":"2024","title":"Can cross-domain term extraction benefit from cross-lingual transfer and nested term labeling?","authors":["HTH Tran, M Martinc, A Repar, N Ljubešić, A Doucet… - Machine Learning, 2024"],"snippet":"Automatic term extraction (ATE) is a natural language processing task that eases the effort of manually identifying terms from domain-specific corpora by providing a list of candidate terms. In this paper, we treat ATE as a sequence-labeling task and …","url":["https://link.springer.com/article/10.1007/s10994-023-06506-7"]}
{"year":"2024","title":"Can Large Language Models Accelerate Digital Transformation by Generating Expert-Like Systems Engineering Artifacts? Insights from an Empirical Exploration","authors":["M Husain, P Wach, TG Topcu - The Proceedings of the 2024 Conference on Systems …"],"snippet":"The old saga of complex system development continues as the vast majority of government and industry programs continue to result in cost and schedule overruns [1–7]. While numerous researchers and government reports attribute this trend to the ever-increasing …","url":["https://link.springer.com/content/pdf/10.1007/978-3-031-62554-1.pdf#page=366"]}
{"year":"2024","title":"Can large language models understand molecules?","authors":["S Sadeghi, A Bui, A Forooghi, J Lu, A Ngom - BMC bioinformatics, 2024"],"snippet":"Purpose Large Language Models (LLMs) like Generative Pre-trained Transformer (GPT) from OpenAI and LLaMA (Large Language Model Meta AI) from Meta AI are increasingly recognized for their potential in the field of cheminformatics, particularly …","url":["https://link.springer.com/article/10.1186/s12859-024-05847-x"]}
{"year":"2024","title":"Can Models Learn Skill Composition from Examples?","authors":["H Zhao, S Kaur, D Yu, A Goyal, S Arora - ICML 2024 Workshop on LLMs and Cognition"],"snippet":"As large language models (LLMs) become increasingly capable, their ability to exhibit *compositional generalization* of skills has garnered significant attention. Yu et al. 2023 recently introduced Skill-Mix evaluation, where models are tasked with …","url":["https://openreview.net/pdf?id=YEEsRgkvnU"]}
{"year":"2024","title":"Cascaded transformer-based networks for wikipedia large-scale image-caption matching","authors":["N Messina, DA Coccomini, A Esuli, F Falchi - Multimedia Tools and Applications, 2024"],"snippet":"… It uses an XLM-RoBERTa masked language model pre-trained on the CommonCrawl dataset and fine-tuned on the image URL-caption match classification task. The CLS token in output from XLM-RoBERTa is attached to a feed-forward …","url":["https://link.springer.com/article/10.1007/s11042-023-17977-0"]}
{"year":"2024","title":"Causality-driven multivariate stock movement forecasting","authors":["A Díaz Berenguer, Y Da, MN Bossa, MC Oveneke… - PloS one, 2024"],"snippet":"Our study aims to investigate the interdependence between international stock markets and sentiments from financial news in stock forecasting. We adopt the Temporal Fusion Transformers (TFT) to incorporate intra and inter-market …","url":["https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0302197"]}
{"year":"2024","title":"CC-GPX: Extracting High-Quality Annotated Geospatial Data from Common Crawl","authors":["I Ilyankou, J Haworth, S Cavazzi - arXiv preprint arXiv:2405.11039, 2024"],"snippet":"The Common Crawl (CC) corpus is the largest open web crawl dataset containing 9.5+ petabytes of data captured since 2008. The dataset is instrumental in training large language models, and as such it has been studied for (un)desirable content …","url":["https://arxiv.org/pdf/2405.11039"]}
{"year":"2024","title":"CCI3. 0-HQ: a large-scale Chinese dataset of high quality designed for pre-training large language models","authors":["L Wang, BW Zhang, C Wu, H Zhao, X Shi, S Gu, J Li… - arXiv preprint arXiv …, 2024"],"snippet":"… Among them, the Open-source datasets, such as The Pile[3] and Common Crawl[4], have been instrumental in propelling LLM … such as FineWeb(15TB)[7], which draw extensively from Common Crawl. Simultaneously, the focus has shifted from rule-based …","url":["https://arxiv.org/pdf/2410.18505"]}
{"year":"2024","title":"CCSUM: A large-scale and high-quality dataset for abstractive news summarization","authors":["X Jiang, M Dreyer - 2024"],"snippet":"… Accordingly, among 35 million CommonCrawl News articles, we identify pairs of articles about the same news story and use one article’s first sentence as the summary for the other article. To ensure high quality, we apply strict filters whose …","url":["https://www.amazon.science/publications/ccsum-a-large-scale-and-high-quality-dataset-for-abstractive-news-summarization"]}
{"year":"2024","title":"CERM: Context-aware Literature-based Discovery via Sentiment Analysis","authors":["JC Young, U Akujuobi - arXiv preprint arXiv:2402.01724, 2024"],"snippet":"Driven by the abundance of biomedical publications, we introduce a sentiment analysis task to understand food-health relationship. Prior attempts to incorporate health into recipe recommendation and analysis systems have primarily focused on …","url":["https://arxiv.org/pdf/2402.01724"]}
{"year":"2024","title":"Challenge design roadmap","authors":["HJE Balderas, I Guyon, A Howard, W Reade, S Treguer - AI Competitions and …, 2023"],"snippet":"Challenges can be seen as a type of game that motivates participants to solve serious tasks. As a result, competition organizers must develop effective game rules. However, these rules have multiple objectives beyond making the game enjoyable …","url":["https://hal.science/hal-04333280/document"]}
{"year":"2024","title":"Challenges and Contributions in Table-to-text Generation: A Survey","authors":["T Dey, P Bhattacharyya"],"snippet":"… The pre-training of T5 involves an unsupervised “span masking” objective applied to Common Crawl data, where spans of text are masked and the model learns to predict them, thus gaining a deep understanding of language patterns and …","url":["https://www.cfilt.iitb.ac.in/resources/surveys/2024/Data_to_text_CFILT_Survey_Tathagata.pdf"]}
{"year":"2024","title":"Changes and challenges of legal education in the era of generative artificial intelligence: Chinese experience","authors":["W Wang, Z Xu, Z Xu - Journal of Infrastructure, Policy and Development, 2024"],"snippet":"Using generative artificial intelligence systems in the classroom for law case analysis teaching can enhance the efficiency and accuracy of knowledge delivery. They can create interactive learning environments that are appropriate, immersive …","url":["https://systems.enpress-publisher.com/index.php/jipd/article/download/5600/3487"]}
{"year":"2024","title":"Chatbots in Airport Customer Service—Exploring Use Cases and Technology Acceptance","authors":["I Auer, S Schlögl, G Glowka - Future Internet, 2024"],"snippet":"… Those pre-trained transformer systems like BERT (Bidirectional Encoder Representations from Transformers) and GPT (Generative Pre-trained Transformer) have been trained on vast language corpora such as Wikipedia and Common Crawl …","url":["https://www.mdpi.com/1999-5903/16/5/175/pdf"]}
{"year":"2024","title":"Chatbots to Cyber Threats: The Evolution of Generative AI in Digital Security","authors":["S Mahato, PK Satan Kumar Yadav"],"snippet":"Generative AI (GenAI) technologies like models such as ChatGPT and Google Bard are racing into an era of rapid incursion of the digital interaction space, especially in the areas of cybersecurity and privacy. I pore on in this paper such duality of the …","url":["https://www.researchgate.net/profile/Sushil-Mahato-5/publication/386340315_Chatbots_to_Cyber_Threats_The_Evolution_of_Generative_AI_in_Digital_Security/links/674df5ce3d17281c7df3330a/Chatbots-to-Cyber-Threats-The-Evolution-of-Generative-AI-in-Digital-Security.pdf"]}
{"year":"2024","title":"Chatgpt & Google Bard AI: A Comparative Study From Student's Perspective.","authors":["SV Vishwakarma, SV Nagar, M West"],"snippet":"The motivation behind choosing this research topic is that rising generation will be based on AI ie Artificial Intelligence. Artificial intelligence is a specialty within computer science that is concerned with creating systems that can replicate human …","url":["https://dalmialionscollege.ac.in/wp-content/uploads/IJCRTAG02031.pdf"]}
{"year":"2024","title":"ChatGPT Alternative Solutions: Large Language Models Survey","authors":["H Alipour, N Pendar, K Roy - arXiv preprint arXiv:2403.14469, 2024"],"snippet":"In recent times, the grandeur of Large Language Models (LLMs) has not only shone in the realm of natural language processing but has also cast its brilliance across a vast array of applications. This remarkable display of LLM capabilities has ignited a …","url":["https://arxiv.org/pdf/2403.14469"]}
{"year":"2024","title":"ChatGPT and GPT-4: utilities in the legal sector","authors":["FJ Dosal Gómez, J Nieto Galende - 2024"],"snippet":"Artificial intelligence systems such as ChatGPT, the OpenAI chatbot, based on the language model family GPT (generative pre-trained transformers), as well as other solutions built on this technology and fine-tuned for specific tasks, have generated …","url":["https://www.tecnologia-ciencia-educacion.com/index.php/TCE/article/download/19081/21543/46195"]}
{"year":"2024","title":"ChatGPT and Language Translation: A Small Case Study Evaluating English–Mandarin Translation","authors":["C Woodrum - International Conference on Human-Computer …, 2024"],"snippet":"… has been informed speculation that it relies heavily on common crawl [13], a compendium of publicly available … common crawl. The \\(15^{th}\\) most common language, Indonesian, makes up less than 1% of the data set [14, 15]. It is important …","url":["https://link.springer.com/chapter/10.1007/978-3-031-60615-1_10"]}
{"year":"2024","title":"ChatGPT as the Marketplace of Ideas: Should Truth-Seeking Be the Goal of AI Content Governance?","authors":["J Zhang - arXiv preprint arXiv:2405.18636, 2024"],"snippet":"As one of the most enduring metaphors within legal discourse, the marketplace of ideas has wielded considerable influence over the jurisprudential landscape for decades. A century after the inception of this theory, ChatGPT emerged as a …","url":["https://arxiv.org/pdf/2405.18636"]}
{"year":"2024","title":"ChatGPT in Cyber Onslaught and Fortification: Past, Present, and Future","authors":["M Gunda, V Manda, P Naradasu, S Mekala… - 2024 IEEE 9th International …, 2024"],"snippet":"… GPT-1 was unveiled in 2018 and trained on a pair of data sets: over 11,000 books from Book Corpus and the enormous Common Crawl … With 1.5 billion features and a much more extensive and diversified training dataset comprising Common Crawl …","url":["https://ieeexplore.ieee.org/abstract/document/10543384/"]}
{"year":"2024","title":"ChatGPT versus NASS clinical guidelines for degenerative spondylolisthesis: a comparative analysis","authors":["W Ahmed, M Saturno, R Rajjoub, AH Duey, B Zaidat… - European Spine Journal, 2024"],"snippet":"… Furthermore, the largest dataset used to train both ChatGPT 3.5 and 4.0 is CommonCrawl, a platform that does not include PubMed and consists predominantly of open access articles, some of which may be of less rigorous if not …","url":["https://link.springer.com/article/10.1007/s00586-024-08198-6"]}
{"year":"2024","title":"ChatGPT vs Gemini vs LLaMA on Multilingual Sentiment Analysis","authors":["A Buscemi, D Proverbio - arXiv preprint arXiv:2402.01715, 2024"],"snippet":"… It relied on a dataset referred to as the Common Crawl [30], a publicly accessible repository that comprises billions of web pages, making it one of the most extensive text databases available. It is important to note that the choice of dataset significantly …","url":["https://arxiv.org/pdf/2402.01715"]}
{"year":"2024","title":"ChatGPT's applications in marketing: a topic modeling approach","authors":["W Tafesse, A Wien - Marketing Intelligence & Planning, 2024"],"snippet":"Purpose ChatGPT is a versatile technology with practical use cases spanning many professional disciplines including marketing. Being a recent innovation, however, there is a lack of academic insight into its tangible applications in the marketing …","url":["https://www.emerald.com/insight/content/doi/10.1108/MIP-10-2023-0526/full/html"]}
{"year":"2024","title":"ChatGPT, the perfect virtual teaching assistant? Ideological bias in learner-chatbot interactions","authors":["M Van Poucke - Computers and Composition, 2024"],"snippet":"This paper examines ChatGPT's use of evaluative language and engagement strategies while addressing information-seeking queries. It assesses the chatbot's role as a virtual teaching assistant (VTA) across various educational settings. By …","url":["https://www.sciencedirect.com/science/article/pii/S8755461524000471"]}
{"year":"2024","title":"ChatGPT-3.5 can create and justify short Afrikaans poems: Implications for practice","authors":["CJ van Staden - Suid-Afrikaanse Tydskrif vir Natuurwetenskap en …, 2024"],"snippet":"ChatGPT-3.5 can create poems but the implications thereof has not yet been sufficiently investigated. The purpose of this explorative case study was to determine to which extent ChatGPT-3.5 can create and justify Afrikaans poems. Because …","url":["https://journals.co.za/doi/abs/10.36303/SATNT.2024.43.1.973"]}
{"year":"2024","title":"ChatQA: Building GPT-4 Level Conversational QA Models","authors":["Z Liu, W Ping, R Roy, P Xu, M Shoeybi, B Catanzaro - arXiv preprint arXiv …, 2024"],"snippet":"… We collect 7k documents (average ∼1k words per document) from common crawl, which cover a wide range of domains. Each document is used for generation of a single conversational QA sample, which leads to a total of 7k multi-turn QA dialogues …","url":["https://arxiv.org/pdf/2401.10225"]}
{"year":"2024","title":"Chatqa: Surpassing gpt-4 on conversational qa and rag","authors":["Z Liu, W Ping, R Roy, P Xu, C Lee, M Shoeybi… - The Thirty-eighth Annual …, 2024"],"snippet":"In this work, we introduce ChatQA, a suite of models that outperform GPT-4 on retrieval-augmented generation (RAG) and conversational question answering (QA). To enhance generation, we propose a two-stage instruction tuning method that …","url":["https://openreview.net/pdf?id=bkUvKPKafQ"]}
{"year":"2024","title":"Chatting Over Course Material: The Role of Retrieval Augmented Generation Systems in Enhancing Academic Chatbots.","authors":["H Monteiro - 2024"],"snippet":"Large Language Models (LLMs) have the potential to enhance learning among students. These tools can be used in chatbot systems allowing students to ask questions about course material, in particular when plugged with the so-called …","url":["https://www.diva-portal.org/smash/get/diva2:1871612/FULLTEXT01.pdf"]}
{"year":"2024","title":"Cheap Learning: Maximising Performance of Language Models for Social Data Science Using Minimal Data","authors":["L Castro-Gonzalez, YL Chung, HR Kirk, J Francis… - arXiv preprint arXiv …, 2024"],"snippet":"The field of machine learning has recently made significant progress in reducing the requirements for labelled training data when building new models. These `cheaper' learning techniques hold significant potential for the social sciences, where …","url":["https://arxiv.org/pdf/2401.12295"]}
{"year":"2024","title":"Check for Extending the Comparative Argumentative Machine: Multilingualism and Stance Detection","authors":["I Nikishina¹, A Bondarenko, S Zaczek¹, OL Haag… - Robust Argumentation Machines …"],"snippet":"The comparative argumentative machine CAM can retrieve arguments that answer comparative questions questions that ask which of several to-be-compared options should be favored in some scenario. In this paper, we describe how we equipped …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=YnMUEQAAQBAJ&oi=fnd&pg=PA317&dq=commoncrawl&ots=o1gact1LH0&sig=q3_HNymYbwpQ5CGcykL5lcksB_s"]}
{"year":"2024","title":"Check for updates A Study of Transductive Graph-Based Regression","authors":["ADB Valejo - Intelligent Systems Design and Applications: Deep …"],"snippet":"Regression methods play an important role in many realworld applications such as econometric, pattern recognition, and prediction of protein chains to cite a few tasks. In the semi-supervised transductive learning problem, some studies present graph-based …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=f9sVEQAAQBAJ&oi=fnd&pg=PA350&dq=commoncrawl&ots=o_7uFjZgt_&sig=K-UYGhdg_mXgrKc-k6v32KIUAJk"]}
{"year":"2024","title":"Check for updates Digilog: Enhancing Website Embedding on Local Governments-A Comparative Analysis","authors":["J Gerber, B Kreiner, J Saxer, A Weiler - Foundations of Intelligent Systems: 27th International …"],"snippet":"The ability to understand and process websites, known as website embedding, is crucial across various domains. It lays the foundation for machine understanding of websites. Specifically, website embedding proves invaluable when monitoring local …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=htIOEQAAQBAJ&oi=fnd&pg=PA126&dq=commoncrawl&ots=o6KyGM_g-B&sig=F3rWIHXdM96ui9ycDvbY9eN_e8o"]}
{"year":"2024","title":"CheckIT!: A Corpus of Expert Fact-checked Claims for Italian Jacopo Gili', Lucia Passaro² and Tommaso Caselli³ ¹Department of Computer Science, University of Turin …","authors":["LP Jacopo Gili, T Caselli - Proceedings of the 9th Italian Conference on …, 2024"],"snippet":"This paper introduces CheckIT!, a resource of expert fact-checked claims, filling a gap for the development of fact-checking pipelines in Italian. We further investigate the use of three state-of-the-art generative text models to create variations of claims …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=OJ0QEQAAQBAJ&oi=fnd&pg=PA228&dq=commoncrawl&ots=2YBOmTCdDf&sig=nCzruIiTWjYUmyU31x156y2AnPk"]}
{"year":"2024","title":"ChemTEB: Chemical Text Embedding Benchmark, an Overview of Embedding Models Performance & Efficiency on a Specific Domain","authors":["AS Kasmaee, M Khodadad, MA Saloot, N Sherck… - arXiv preprint arXiv …, 2024"],"snippet":"… Unlike models that rely on limited labeled data or low-quality synthetic text pairs, E5 is contrastively trained on CCPairs, a curated web-scale dataset that incorporates diverse data sources such as CommunityQA, Common Crawl, and …","url":["https://arxiv.org/pdf/2412.00532"]}
{"year":"2024","title":"Chimera: Improving Generalist Model with Domain-Specific Experts","authors":["T Peng, M Li, H Zhou, R Xia, R Zhang, L Bai, S Mao… - arXiv preprint arXiv …, 2024"],"snippet":"… We constructed our benchmark by systematically sampling from an initial pool of 200, 000 PDF documents obtained from Common Crawl, Google, Baidu search engines, and internal repositories, which is consistent with the approach of …","url":["https://arxiv.org/pdf/2412.05983"]}
{"year":"2024","title":"Chinese Tiny LLM: Pretraining a Chinese-Centric Large Language Model","authors":["X Du, Z Yu, S Gao, D Pan, Y Cheng, Z Ma, R Yuan… - arXiv preprint arXiv …, 2024"],"snippet":"In this study, we introduce CT-LLM, a 2B large language model (LLM) that illustrates a pivotal shift towards prioritizing the Chinese language in developing LLMs. Uniquely initiated from scratch, CT-LLM diverges from the conventional …","url":["https://arxiv.org/pdf/2404.04167"]}
{"year":"2024","title":"ChineseWebText 2.0: Large-Scale High-quality Chinese Web Text with Multi-dimensional and fine-grained information","authors":["W Zhang, Z Li, W Yang, C Leng, Y Bai, Q Du, C Zong… - arXiv preprint arXiv …, 2024"],"snippet":"… Given the relatively high noise levels in Common Crawl data, we directly sample from Common Crawl to construct the negative samples. Figure 2a provides a detailed breakdown of the composition and quantity of the training data …","url":["https://arxiv.org/pdf/2411.19668"]}
{"year":"2024","title":"ChocoLlama: Lessons Learned From Teaching Llamas Dutch","authors":["M Meeus, A Rathé, F Remy, P Delobelle, JJ Decorte… - arXiv preprint arXiv …, 2024"],"snippet":"While Large Language Models (LLMs) have shown remarkable capabilities in natural language understanding and generation, their performance often lags in lower-resource, non-English languages due to biases in the training data. In this …","url":["https://arxiv.org/pdf/2412.07633"]}
{"year":"2024","title":"Choose the Final Translation from NMT and LLM hypotheses Using MBR Decoding: HW-TSC's Submission to the WMT24 General MT Shared Task","authors":["Z Wu, D Wei, Z Li, H Shang, J Guo, S Li, Z Rao, Y Luo… - arXiv preprint arXiv …, 2024"],"snippet":"… and Common Crawl data sources. The amount of data we used for training NMT and LLM-based MT models is shown in Table 1. It should be noted that in order to obtain better translation performance in the general domain, we mix the monolingual …","url":["https://arxiv.org/pdf/2409.14800"]}
{"year":"2024","title":"CHORDONOMICON: A Dataset of 666,000 Songs and their Chord Progressions","authors":["S Kantarelis, K Thomas, V Lyberatos, E Dervakos… - arXiv preprint arXiv …, 2024"],"snippet":"… A relevant search on https://index.commoncrawl.org/ will show all the harvested UG URLs, and the relevant Common Crawl web archive (.warc) files will show the raw scrapped pages, along with the lyrics, song names, bands, and all information …","url":["https://arxiv.org/pdf/2410.22046"]}
{"year":"2024","title":"CLaMP 2: Multimodal Music Information Retrieval Across 101 Languages Using Large Language Models","authors":["S Wu, Y Wang, R Yuan, Z Guo, X Tan, G Zhang… - arXiv preprint arXiv …, 2024"],"snippet":"Challenges in managing linguistic diversity and integrating various musical modalities are faced by current music information retrieval systems. These limitations reduce their effectiveness in a global, multimodal music environment. To …","url":["https://arxiv.org/pdf/2410.13267"]}
{"year":"2024","title":"CLAPNQ: Cohesive Long-form Answers from Passages in Natural Questions for RAG systems","authors":["S Rosenthal, A Sil, R Florian, S Roukos - arXiv preprint arXiv:2404.02103, 2024"],"snippet":"… However, they use sentencelevel matching (by encoding sentences for semantic similarity comparisons) to retrieve up to top 7 documents from Common Crawl while avoiding exact matches as the abstractive dataset. In the extractive version, the …","url":["https://arxiv.org/pdf/2404.02103"]}
{"year":"2024","title":"CLASSLA-web: Comparable Web Corpora of South Slavic Languages Enriched with Linguistic and Genre Annotation","authors":["N Ljubešić, T Kuzman - arXiv preprint arXiv:2403.12721, 2024"],"snippet":"This paper presents a collection of highly comparable web corpora of Slovenian, Croatian, Bosnian, Montenegrin, Serbian, Macedonian, and Bulgarian, covering thereby the whole spectrum of official languages in the South Slavic language space …","url":["https://arxiv.org/pdf/2403.12721"]}
{"year":"2024","title":"Cleaner Pretraining Corpus Curation with Neural Web Scraping","authors":["Z Xu, Z Liu, Y Yan, Z Liu, C Xiong, G Yu - arXiv preprint arXiv:2402.14652, 2024"],"snippet":"… The web-crawled datasets, such as Common Crawl, have been widely used for pretraining, facilitating the development of language … htmlparser serves as the text pre-extraction tool for CommonCrawl6 WET file (containing pre-extracted text), while …","url":["https://arxiv.org/html/2402.14652v1"]}
{"year":"2024","title":"CLEARNESS: Coreference Resolution for Generating and Ranking Arguments Extracted from Debate Portals for Queries","authors":["J Weidmann, L Dumani, R Schenkel - 2023"],"snippet":"… Refining Arg-CTRL with data from Common Crawl leads to a higher quality of generated arguments compared to using user discussions from Reddit comments. In the mentioned studies, new arguments are generated through the use of knowledge …","url":["https://ceur-ws.org/Vol-3630/LWDA2023-paper15.pdf"]}
{"year":"2024","title":"CLIP and the City: Addressing the Artificial Encoding of Cities in Multimodal Foundation Deep Learning Models","authors":["DN del Castillo, I Neri"],"snippet":"In this project, we propose and explore a computational pipeline to examine urban cultural landscapes through the lens of artificial intelligence, and for questioning modes of embedding culture in machine learning models. By employing machine …","url":["https://www.strand.rs/publishing/2023/OA2023_proceedings_p100.pdf"]}
{"year":"2024","title":"CLIP-CID: Efficient CLIP Distillation via Cluster-Instance Discrimination","authors":["K Yang, T Gu, X An, H Jiang, X Dai, Z Feng, W Cai… - arXiv preprint arXiv …, 2024"],"snippet":"Contrastive Language-Image Pre-training (CLIP) has achieved excellent performance over a wide range of tasks. However, the effectiveness of CLIP heavily relies on a substantial corpus of pre-training data, resulting in notable consumption …","url":["https://arxiv.org/pdf/2408.09441"]}
{"year":"2024","title":"Clusters and Copies: An Analysis of Cryptocurrency Investment Scam Websites","authors":["IA Klom - 2024"],"snippet":"Cryptocurrency investment scams have become an increasingly prevalent threat, leveraging sophisticated methods to deceive and exploit victims. The phenomenon of pig butchering has gained prominence, but victims rarely see the perpetrators …","url":["https://repository.tudelft.nl/file/File_c05f5a66-85f2-47d4-8b71-b2ce0baf01cf"]}
{"year":"2024","title":"Co-constructing AI Authoring Using Ethical Theories","authors":["B Jones - 88th Annual International Conference"],"snippet":"We must show ethical humility, historically contextualizing ethical standards, as we implement AI tools in courses. The pace of change requires agile approaches to defining standards for the ethical use of AI. We invited students to co-construct a …","url":["https://researchmap.jp/hiroyuki-london/published_papers/45908700/attachment_file.pdf#page=218"]}
{"year":"2024","title":"CoastTerm: a Corpus for Multidisciplinary Term Extraction in Coastal Scientific Literature","authors":["J Delaunay, HTH Tran, CE González-Gallardo… - arXiv preprint arXiv …, 2024"],"snippet":"… – Multilingual pre-trained model: We opt for XLMR [9], a transformer-based model pre-trained on 2.5TB of filtered CommonCrawl data containing 100 languages. This multilingual version of RoBERTa, achieves benchmark performance in ATE for rich-resourced …","url":["https://arxiv.org/pdf/2406.09128"]}
{"year":"2024","title":"Code LLMs: A Taxonomy-based Survey","authors":["N Raihan, C Newman, M Zampieri - arXiv preprint arXiv:2412.08291, 2024"],"snippet":"Large language models (LLMs) have demonstrated remarkable capabilities across various NLP tasks and have recently expanded their impact to coding tasks, bridging the gap between natural languages (NL) and programming languages (PL). This …","url":["https://arxiv.org/pdf/2412.08291"]}
{"year":"2024","title":"Cognitive Development as a Model for the Effects of Psychedelics: Do Changes in Cognitive Flexibility Underly the Clinical Benefits of Psychedelic Therapy?","authors":["E Hurwitz - 2024"],"snippet":"… A set of pre-trained word vectors was used which contained 840 billion tokens gathered via Common Crawl. The original set of word vectors was filtered to include only a subset of words originally used by Contexto, then further filtered to remove …","url":["https://escholarship.org/content/qt4147574w/qt4147574w_noSplash_1da8993495c397b9243deb22946fb202.pdf"]}
{"year":"2024","title":"Combatting Dimensional Collapse in LLM Pre-Training Data via Submodular File Selection","authors":["T DATA"],"snippet":"Selecting high-quality pre-training data for large language models (LLMs) is crucial for enhancing their overall performance under limited computation budget, improving both training and sample efficiency. Recent advancements in file …","url":["https://openreview.net/pdf?id=f4gF6AIHRy"]}
{"year":"2024","title":"ComiCap: A VLMs pipeline for dense captioning of Comic Panels","authors":["E Vivoli, N Biondi, M Bertini, D Karatzas - arXiv preprint arXiv:2409.16159, 2024"],"snippet":"… It was trained using a unique set of training data that includes CommonCrawl and Code Pretrain datasets, C4, and smaller contributions from sources such as Arxiv and Open Web Math, among others. For handling high-resolution images, the model …","url":["https://arxiv.org/pdf/2409.16159"]}
{"year":"2024","title":"Community OSCAR: A Community Effort for Multilingual Web Data","authors":["M Brack, M Ostendorff, PO Suarez, JJ Saiz, IL Castilla…"],"snippet":"The development of large language models (LLMs) relies heavily on extensive, highquality datasets. Publicly available datasets focus predominantly on English, leaving other language communities behind. To address this issue, we introduce …","url":["https://occiglot.eu/papers/Community_Oscar.pdf"]}
{"year":"2024","title":"Comparative Analysis of Cognitive Agreement between Human Analysts and Generative AI in Construction Safety Risk Assessment","authors":["U Ray, C Arteaga, JW Park - ISARC. Proceedings of the International Symposium on …, 2024"],"snippet":"The construction industry struggles with safety risk assessment complexities due to evolving work environments, diverse labor forces, time constraints, regulatory intricacies, and inconsistent practices. While previous studies have highlighted the …","url":["https://search.proquest.com/openview/cafe1eba93f0bf9dd30f5b09f629fc93/1?pq-origsite=gscholar&cbl=1646340"]}
{"year":"2024","title":"Comparative Analysis of Generative AI Tools in Enhancing Educational Engagement","authors":["F Borović, K Aleksić-Maslać, P Vranešić - 2024 47th MIPRO ICT and Electronics …, 2024"],"snippet":"Technological development is continuously reshaping the traditional educational setting, presenting various possibilities for educational refinement. It is pivotal to motivate active engagement among all participants, and generative AI tools emerge …","url":["https://ieeexplore.ieee.org/abstract/document/10569483/"]}
{"year":"2024","title":"Comparative evaluation of machine learning algorithms for phishing site detection","authors":["NF Almujahid, MA Haq, M Alshehri - PeerJ Computer Science, 2024"],"snippet":"The advent of Internet technologies has resulted in the proliferation of electronic trading and the use of the Internet for electronic transactions, leading to a rise in unauthorized access to sensitive user information and the depletion of resources for …","url":["https://peerj.com/articles/cs-2131/"]}
{"year":"2024","title":"Comparative Performance of Advanced NLP Models and LLMs in Multilingual Geo-Entity Detection","authors":["K Kopanov - Proceedings of the Cognitive Models and Artificial …, 2024"],"snippet":"The integration of advanced Natural Language Processing (NLP) methodologies and Large Language Models (LLMs) has significantly enhanced the extraction and analysis of geospatial data from multilingual texts, impacting sectors such as …","url":["https://dl.acm.org/doi/abs/10.1145/3660853.3660878"]}
{"year":"2024","title":"Comparative Study on Synthetic and Natural Error Analysis with BART & MarianMT","authors":["R Rohit, SA Gandheesh, GS Sannala, PB Pati - 2024 IEEE 9th International …, 2024"],"snippet":"Text is essential for communication, information sharing, knowledge acquisition, and analysis. It shapes public opinion, supports education, and drives online content, making it crucial in various domains. While there are various language models …","url":["https://ieeexplore.ieee.org/abstract/document/10543923/"]}
{"year":"2024","title":"Comparing Bad Apples to Good Oranges: Aligning Large Language Models via Joint Preference Optimization","authors":["H Bansal, A Suvarna, G Bhatt, N Peng, KW Chang… - arXiv preprint arXiv …, 2024"],"snippet":"A common technique for aligning large language models (LLMs) relies on acquiring human preferences by comparing multiple generations conditioned on a fixed context. This only leverages the pairwise comparisons when the generations are …","url":["https://arxiv.org/html/2404.00530v1"]}
{"year":"2024","title":"Comparing Explanation Faithfulness between Multilingual and Monolingual Fine-tuned Language Models","authors":["Z Zhao, N Aletras - arXiv preprint arXiv:2403.12809, 2024"],"snippet":"In many real natural language processing application scenarios, practitioners not only aim to maximize predictive performance but also seek faithful explanations for the model predictions. Rationales and importance distribution given by feature …","url":["https://arxiv.org/pdf/2403.12809"]}
{"year":"2024","title":"Comparing Fine-Tuning, Zero and Few-Shot Strategies with Large Language Models in Hate Speech Detection in English","authors":["R Pan, JA García-Díaz, R Valencia-García"],"snippet":"… This is a multilingual model based on RoBERTa, pre-trained with a 2.5 TB filtered CommonCrawl dataset containing 100 languages, using an MLM goal, where it randomly masks 15% of the words in the input, runs the entire masked sentence …","url":["https://cdn.techscience.cn/files/CMES/2024/TSP_CMES-140-3/TSP_CMES_49631/TSP_CMES_49631.pdf"]}
{"year":"2024","title":"Comparing Foundations: Insights into the Construction of Financial Causal Knowledge Graphs with and without Ontology","authors":["Z Xu, R Ichise - 人工知能学会全国大会論文集 第 38 回 (2024), 2024"],"snippet":"Simplicity in information navigation, interpretation, and reasoning has positioned mono-relation knowledge graphs (KGs) as a focus of attention, particularly in targeted scenarios. However, their deficiency in hierarchical interactions between …","url":["https://www.jstage.jst.go.jp/article/pjsai/JSAI2024/0/JSAI2024_2Q5IS102/_pdf"]}
{"year":"2024","title":"Comparing generative and retrieval-based chatbots in answering patient questions regarding age-related macular degeneration and diabetic retinopathy","authors":["KX Cheong, C Zhang, TE Tan, BJ Fenner, WM Wong… - British Journal of …, 2024"],"snippet":"… ChatGPT was trained on multiple extremely large datasets, of which Common Crawl (open repository of web crawl data) constituted the bulk of the datasets.30 31 Google Bard was trained on Infiniset (data comprising public forum dialogue …","url":["https://bjo.bmj.com/content/early/2024/05/15/bjo-2023-324533.abstract"]}
{"year":"2024","title":"Comparison of Common Crawl News & GDELT","authors":["A El Ouadi, D Beskow - 2024 IEEE International Systems Conference (SysCon), 2024"],"snippet":"… Common Crawl data has proven valuable for research and training artificial intelligence, noting that 82% of raw tokens used to train GPT-3 come from the Common Crawl dataset. CC-News, a derived corpus of news data from Common …","url":["https://ieeexplore.ieee.org/abstract/document/10553540/"]}
{"year":"2024","title":"Comparison of Machine Learning Algorithms and Large Language Models for Product Categorization","authors":["A İhsanoğlu, M Zaval, OT Yıldız - 2024 32nd Signal Processing and Communications …, 2024"],"snippet":"This study explores the efficacy of traditional machine learning algorithms and Large Language Models (LLMs) in automating product categorization for online e-commerce platforms. By comparing these methodologies, we assess their performance in …","url":["https://ieeexplore.ieee.org/abstract/document/10600809/"]}
{"year":"2024","title":"Compass: Large Multilingual Language Model for South-east Asia","authors":["S Maria - arXiv preprint arXiv:2404.09220, 2024"],"snippet":"… We categorized these sources into seven types: CommonCrawl, C4, Wikipedia, WebText, Academic, Books, and Code. We upsampled and … We expect that the introduction of biases may originate from CommonCrawl, as this substantial dataset …","url":["https://arxiv.org/pdf/2404.09220"]}
{"year":"2024","title":"Competition concerns with foundation models: a new feast for big tech?","authors":["S Mitra - European Competition Journal, 2024"],"snippet":"… Some well-known FMs such as GPT-3 and LLaMA have been trained on data from public sources (such as Common Crawl). However, there are concerns that publicly available data would eventually have been completely saturated for training …","url":["https://www.tandfonline.com/doi/abs/10.1080/17441056.2024.2379142"]}
{"year":"2024","title":"Compilation of a Synthetic Judeo-French Corpus","authors":["I Nikolova-Stoupak, G Lejeune, E Schaeffer-Lacroix - Proceedings of the 8th Joint …, 2024"],"snippet":"This is a short paper describing the process of derivation of synthetic Judeo-French text. Judeo-French is one of a number of rare languages used in speaking and writing by Jewish communities as confined to a particular temporal and …","url":["https://aclanthology.org/2024.latechclfl-1.5.pdf"]}
{"year":"2024","title":"Complex Word Identification for Italian Language: a dictionary-based approach","authors":["L Occhipinti - Sixth International Conference, 2024"],"snippet":"… The model used in our study was trained on Wikipedia and Common Crawl datasets6. These embeddings provided vector representations for each word in our dataset, primarily comprising isolated items, allowing us to incorporate contextual …","url":["https://dcl.bas.bg/clib/wp-content/uploads/2024/09/CLIB2024_PROCEEDINGS_v1.0.pdf#page=126"]}
{"year":"2024","title":"Compositional Text-to-Image Generation with Dense Blob Representations","authors":["W Nie, S Liu, M Mardani, C Liu, B Eckart, A Vahdat - arXiv preprint arXiv:2405.08246, 2024"],"snippet":"Existing text-to-image models struggle to follow complex text prompts, raising the need for extra grounding inputs for better controllability. In this work, we propose to decompose a scene into visual primitives - denoted as dense blob representations …","url":["https://arxiv.org/pdf/2405.08246"]}
{"year":"2024","title":"Comprehensive Analysis of Falcon 7B: A State-of-the-Art Generative Large Language Model","authors":["M Aridoss, KS Bisht, AK Natarajan - Generative AI: Current Trends and Applications","M Aridoss, KS Bisht, AK Natarajan - Generative AI: Current Trends and Applications, 2024"],"snippet":"This study provides an in-depth analysis of Falcon 7B, a state-of-theart generative language model, emphasizing its complex performance metrics, flexible features, and multifaceted attributes. This chapter thoroughly reviews Falcon 7B’s …","url":["https://link.springer.com/chapter/10.1007/978-981-97-8460-8_8","https://link.springer.com/content/pdf/10.1007/978-981-97-8460-8.pdf#page=159"]}
{"year":"2024","title":"Comprehensive Analysis of Falcon 7B: A State-of-the-Art Generative Large","authors":["M Aridoss, KS Bisht, AK Natarajan - Generative AI: Current Trends and Applications"],"snippet":"This study provides an in-depth analysis of Falcon 7B, a state-of-the-art generative language model, emphasizing its complex performance metrics, flexible features, and multifaceted attributes. This chapter thoroughly reviews Falcon 7B's …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=eec2EQAAQBAJ&oi=fnd&pg=PA147&dq=commoncrawl&ots=lZ4Ux7keh3&sig=-OIL-JTsKs2C-ZldhXp8KkfR2-w"]}
{"year":"2024","title":"Comprehensive analysis of natural language processing","authors":["RK Yadav, A Madaan - Global Journal of Engineering and Technology …, 2024"],"snippet":"… Huge datasets like the Penn Treebank and the Common Crawl drove the development of more sophisticated NLP models. Transfer learning techniques like BERT enabled finetuning of pre-trained models for specific tasks. TensorFlow and …","url":["http://gjeta.com/sites/default/files/GJETA-2024-0058.pdf"]}
{"year":"2024","title":"Comprehensive review and comparative analysis of transformer models in sentiment analysis","authors":["H Bashiri, H Naderi - Knowledge and Information Systems, 2024"],"snippet":"Sentiment analysis has become an important task in natural language processing because it is used in many different areas. This paper gives a detailed review of sentiment analysis, including its definition, challenges, and uses. Different …","url":["https://link.springer.com/article/10.1007/s10115-024-02214-3"]}
{"year":"2024","title":"COMPREHENSIVE STUDY OF CLINICAL ENTITY EXTRACTION AND CLASSIFICATION USING LARGE LANGUAGE MODELS","authors":["M Faedi, P Torroni, DA Galassi, DG Grundler…"],"snippet":"This project aims to evaluate various techniques for extraction and categorization of clinical terms in unstructured documents. The purpose of this study is to assist automated systems operating in the biomedical domain by highlighting relevant …","url":["https://amslaurea.unibo.it/30623/1/Tesi_MicheleFaedi.pdf"]}
{"year":"2024","title":"Comprehensive Study on Performance Evaluation and Optimization of Model Compression: Bridging Traditional Deep Learning and Large Language Models","authors":["A Saxena, AK Bishwas, AA Mishra, R Armstrong - arXiv preprint arXiv:2407.15904, 2024"],"snippet":"… For pruning language models, we used XLM-RoBERTA [30] trained on 2.5Tb of filtered CommonCrawl data containing 100 languages, BERTsmall [31] trained on disaster tweets dataset [32] and GPT-2 small [33] finetuned on E2E NLG [34]. …","url":["https://arxiv.org/pdf/2407.15904"]}
{"year":"2024","title":"Compressing Lengthy Context With UltraGist","authors":["P Zhang, Z Liu, S Xiao, N Shao, Q Ye, Z Dou - arXiv preprint arXiv:2405.16635, 2024"],"snippet":"Compressing lengthy context is a critical but technically challenging problem. In this paper, we propose a new method called UltraGist, which is distinguished for its high-quality compression of lengthy context due to the innovative design of the compression and …","url":["https://arxiv.org/pdf/2405.16635"]}
{"year":"2024","title":"Compression Represents Intelligence Linearly","authors":["Y Huang, J Zhang, Z Shan, J He - arXiv preprint arXiv:2404.09937, 2024"],"snippet":"… Concretely, for assessing knowledge and commonsense, we have compiled texts from the latest Common Crawl dataset. To evaluate coding ability, we have sourced data from GitHub repositories mainly on the Python language since the downstream …","url":["https://arxiv.org/pdf/2404.09937"]}
{"year":"2024","title":"Computational Approaches to Lexical Complexity Prediction and Simplification","authors":["K North - 2024"],"snippet":"Lexical Simplification (LS) automatically replaces difficult to understand words with easier alternatives whilst maintaining the original meaning of a sentence. LS serves as a preliminary step to Text Simplification with the aim of enhancing a text's …","url":["https://search.proquest.com/openview/99e60a496e095f106cba5d19a495bf5f/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
{"year":"2024","title":"Computational Collective Intelligence: 16th International Conference, ICCCI 2024, Leipzig, Germany, September 9–11, 2024, Proceedings, Part II","authors":["NT Nguyen"],"snippet":"This volume contains the first part of the proceedings of the 16th International Conference on Computational Collective Intelligence (ICCCI 2024), held in Leipzig, Germany from 9–11 September 2024. The conference was organized in a hybrid …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=KXsfEQAAQBAJ&oi=fnd&pg=PR5&dq=commoncrawl&ots=WZPC5hf0SY&sig=akBAFlqgGyJbJ-5BWkxh9zXpQ1g"]}
{"year":"2024","title":"Computational criminology: at-scale quantitative analysis of the evolution of cybercrime forums","authors":["J Hughes - 2024"],"snippet":"Cybercrime forums and marketplaces are used by members to share hacking techniques, general community-building discussions, and trade hacking tools. While there is a large corpus of literature studying these platforms, from a cross-forum …","url":["https://www.repository.cam.ac.uk/bitstreams/0b5dcda3-56e5-4f29-8d3e-e9aecb2b95dc/download"]}
{"year":"2024","title":"Computational Measures of Language Variation in Textual Utterances","authors":["K Vishnubhotla - 2024"],"snippet":"The use of language as a tool for self-expression and social communication is marked by extensive variation in the way that language is used by different people and communities. The computational modeling of this variation studies the social …","url":["https://www.cs.toronto.edu/pub/gh/Vishnubhotla-PhD-thesis-2024.pdf"]}
{"year":"2024","title":"Computerized diagnostic decision support systems–a comparative performance study of Isabel Pro vs. ChatGPT4","authors":["JM Bridges - Diagnosis, 2024"],"snippet":"… ChatGPT4 is trained on Common Crawl, a publicly available dataset and one of the most extensive text datasets. While not trained explicitly for medical diagnosis, ChatGPT4 accesses medical textbooks, medical websites, medical papers, and …","url":["https://www.degruyter.com/document/doi/10.1515/dx-2024-0033/html"]}
{"year":"2024","title":"Comquest: an Adaptive Crawler for User Comments on the Web","authors":["Z Chen - 2024"],"snippet":"This thesis introduces Comquest, an adaptive framework designed for the large-scale collection and integration of user comments from the Web. User comments are featured on many websites and there is growing interest in mining and studying user …","url":["https://scholarshare.temple.edu/bitstream/handle/20.500.12613/10236/Chen_temple_0225E_15673.pdf?sequence=1&isAllowed=y"]}
{"year":"2024","title":"Comquest: Large Scale User Comment Crawling and Integration","authors":["Z Chen, L He, A Mukherjee, E Dragut - 2024"],"snippet":"… To train the model, we collect an extensive dataset from the Common Crawl Project. We filter the webpages that show apparent code signals (eg, loading the commenting system libraries) of the supported commenting systems. …","url":["https://www.researchgate.net/profile/Zhijia-Chen-3/publication/379953271_Comquest_Large_Scale_User_Comment_Crawling_and_Integration/links/6622cba3f7d3fc28746df7e6/Comquest-Large-Scale-User-Comment-Crawling-and-Integration.pdf"]}
{"year":"2024","title":"Confounders in Instance Variation for the Analysis of Data Contamination","authors":["B Mehrbakhsha, D Garigliottid, F Martínez-Plumeda…"],"snippet":"… 2020) the same approach has been taken and all data points from the evaluation sets that had a 13-gram collision in the pre-training Common Crawl (C4) dataset were removed to tackle contamination. As contamination can involve minor …","url":["https://xai.w.uib.no/files/2024/07/ACL_2024_CONDA-Confounders.pdf"]}
{"year":"2024","title":"Consent in Crisis: The Rapid Decline of the AI Data Commons","authors":["S Longpre, R Mahari, A Lee, C Lund, H Oderinwale… - arXiv preprint arXiv …, 2024"],"snippet":"… In our study, we focus on three popular, open-source, and permissively licensed data sources which are derived from Common Crawl, the largest publicly available crawl of the web, which has collected and stored hundreds of billions of web pages …","url":["https://arxiv.org/pdf/2407.14933"]}
{"year":"2024","title":"Considering the Role of Fairness in Copyright Fair Use","authors":["B Rosenblatt - Houston Law Review, 2023"],"snippet":"Moral intuitions regarding when it is \"fair\" to engage in unauthorized copying or derivation from a copyrighted work may often take into account factors that the fair use statute, 17 USC § 107, does not enumerate among fair use considerations. This …","url":["https://houstonlawreview.org/article/92123-considering-the-role-of-fairness-in-copyright-fair-use"]}
{"year":"2024","title":"Conspiracy Theory Detection using Transformers with Multi-task and Multilingual Approaches","authors":["L Zrnić - Working Notes of CLEF, 2024"],"snippet":"The COVID-19 pandemic sparked a new age of conspiracy theories in society. This has become an issue, especially since these theories are mixed in with reasonable arguments that criticize the measures taken by governments and their effects. A way …","url":["https://ceur-ws.org/Vol-3740/paper-295.pdf"]}
{"year":"2024","title":"Constructing Multimodal Datasets from Scratch for Rapid Development of a Japanese Visual Language Model","authors":["K Sasagawa, K Maeda, I Sugiura, S Kurita, N Okazaki… - arXiv preprint arXiv …, 2024"],"snippet":"To develop high-performing Visual Language Models (VLMs), it is essential to prepare multimodal resources, such as image-text pairs, interleaved data, and instruction data. While multimodal resources for English are abundant, there is a …","url":["https://arxiv.org/pdf/2410.22736"]}
{"year":"2024","title":"Construction of Text Summarization Corpus in Economics Domain and Baseline Models","authors":["S Jumpathong, A Takhom, P Boonkwan… - 2024"],"snippet":"… It was pre-trained with a data collection of 101 languages from Common Crawl Due to time and resource constraints, we chose mT5-small… It was pre-trained with a data collection of 101 languages from Common Crawl. Due to time and resource …","url":["https://www.jicce.org/journal/view.html?uid=1254&vmd=Full"]}
{"year":"2024","title":"Context-aware embeddings for robust multiclass fraudulent URL detection in online social platforms","authors":["S Afzal, M Asim, MO Beg, T Baker, AI Awad, N Shamim - Computers and Electrical …, 2024"],"snippet":"… Their dataset comprised 2 million URLs from Common Crawl and PhishTank, and they applied three-fold cross-validation with 90% training data. Feature-ranking techniques were used to identify the most important among 14 features. They …","url":["https://www.sciencedirect.com/science/article/pii/S004579062400421X"]}
{"year":"2024","title":"Context-aware Transliteration of Romanized South Asian Languages","authors":["C Kirov, C Johny, A Katanova, A Gutkin, B Roark - Computational Linguistics, 2024"],"snippet":"While most transliteration research is focused on single tokens such as named entities – eg, transliteration of “અમદાવાદ” from the Gujarati script to the Latin script “Ahmedabad” – the informal romanization prevalent in South Asia and elsewhere …","url":["https://direct.mit.edu/coli/article-pdf/doi/10.1162/coli_a_00510/2213805/coli_a_00510.pdf"]}
{"year":"2024","title":"Context-Relevant Denoising for Unsupervised Domain-Adapted Sentence Embeddings","authors":["M Lowe, JD Prusa, JL Leevy, TM Khoshgoftaar - … and Integration for Data Science (IRI …, 2024"],"snippet":"… Over the course of this case study, we utilized two information archives as our primary data sources: CommonCrawl News (CC-News), a repository of archived worldwide news events in various languages; and MIMIC-III/IV, a publicly available …","url":["https://ieeexplore.ieee.org/abstract/document/10703818/"]}
{"year":"2024","title":"Contextual Chart Generation for Cyber Deception","authors":["DD Nguyen, D Liebowitz, S Nepal, SS Kanhere… - arXiv preprint arXiv …, 2024"],"snippet":"… (1) HPN-T5 is based on Text-to-Text Transfer Transformer (T5) [42], a highly scalable sequence-to-sequence Transformer pre-trained on a large corpus harvested from Common Crawl. T5 introduced a novel pre-training objective that …","url":["https://arxiv.org/pdf/2404.04854"]}
{"year":"2024","title":"Contextual Word Embedding for Biomedical Knowledge Extraction: a Rapid Review and Case Study","authors":["D Vithanage, P Yu, L Wang, C Deng - Journal of Healthcare Informatics Research, 2024"],"snippet":"Recent advancements in natural language processing (NLP), particularly contextual word embedding models, have improved knowledge extraction from biomedical and healthcare texts. However, limited comprehensive research compares these models …","url":["https://link.springer.com/article/10.1007/s41666-023-00157-y"]}
{"year":"2024","title":"Contextualized Word Embeddings in Azerbaijani Language","authors":["T Alizada, U Suleymanov, Z Rustamov - 2024 IEEE 18th International Conference on …, 2024"],"snippet":"This study delves into the implementation of Contextualized Word Embeddings in Azerbaijani. To this end, the project is capitalizing on the recent advancements in NLP, in particular, transformer models such as RoBERTa and GPT-2, to derive the …","url":["https://ieeexplore.ieee.org/abstract/document/10740448/"]}
{"year":"2024","title":"Contextually Enriched Meta-Learning Ensemble Model for Urdu Sentiment Analysis Symmetry 2023, 15, 645","authors":["K Ahmed, MI Nadeem, D Li, Z Zheng, N Al-Kahtani… - 2023"],"snippet":"… On the other hand, this model makes use of pre-trained word vectors that were trained on “common crawl” and “Wikipedia” through the use of the fastText model [82]. The CBOW algorithm with position-weighting is used to train this word vector. After …","url":["https://www.academia.edu/download/101809833/symmetry-15-00645-v2.pdf"]}
{"year":"2024","title":"Continual Pre-Training for Cross-Lingual LLM Adaptation: Enhancing Japanese Language Capabilities","authors":["K Fujii, T Nakamura, M Loem, H Iida, M Ohi, K Hattori… - arXiv preprint arXiv …, 2024"],"snippet":"Cross-lingual continual pre-training of large language models (LLMs) initially trained on English corpus allows us to leverage the vast amount of English language resources and reduce the pre-training cost. In this study, we constructed Swallow, an …","url":["https://arxiv.org/pdf/2404.17790"]}
{"year":"2024","title":"Continuous or Discrete, That Is the Question: A Survey on Large Multi-Modal Models from the Perspective of Input-Output Space Extension","authors":["Z Li, J Zhang, D Wang, Y Wang, X Huang, Z Wei - 2024"],"snippet":"… OBELICS [260] is constructed from HTML files obtained from Common Crawl dumps, and the resulting documents maintain the original linearity of images and texts as they appeared on the websites, while removing spam and ads. Exposing the …","url":["https://www.preprints.org/frontend/manuscript/8267896f227ef3f94a645a6b196f0b46/download_pub"]}
{"year":"2024","title":"CONTOR: Benchmarking strategies for completing ontologies with plausible missing rules","authors":["L Na, T Bailleux, Z Bouraoui, S Schockaert - 2024"],"snippet":"We consider the problem of finding plausible rules that are missing from a given ontology. A number of strategies for this problem have already been considered in the literature. Little is known about the relative performance of these strategies …","url":["https://orca.cardiff.ac.uk/id/eprint/173139/1/_EMNLP_2024_camera_ready__CONTOR_ontologies.pdf"]}
{"year":"2024","title":"Controllable Sentence Simplification in Dutch","authors":["T Seidl, V Vandeghinste - Computational Linguistics in the Netherlands Journal, 2024"],"snippet":"Text simplification aims to reduce complexity in vocabulary and syntax, enhancing the readability and comprehension of text. This paper presents a supervised sentence simplification approach for Dutch using a pre-trained large language …","url":["https://clinjournal.org/clinj/article/download/171/184"]}
{"year":"2024","title":"Controllable Sentence Simplification in Swedish Using Control Prefixes and Mined Paraphrases","authors":["J Monsen, A Jönsson - Proceedings of the 2024 Joint International Conference …, 2024"],"snippet":"… 2020), an opensource repository with tools to download and clean Common Crawl snapshots. Each file in the CC-100 corpus contains … The Common Crawl snapshots contain a large portion of low-quality data, including offensive and …","url":["https://aclanthology.org/2024.lrec-main.349.pdf"]}
{"year":"2024","title":"Cook Smarter Not Harder: Enhancing Learning Capacity in Smart Ovens with Supplementary Data","authors":["AM MIGEA, VA NEGRU, T Sebastian-Antonio… - 2024 IEEE 20th …, 2024"],"snippet":"This paper presents a novel approach to improve cooking experiences by integrating advanced natural language processing and machine learning techniques within the food industry. The research focuses on developing a …","url":["https://ieeexplore.ieee.org/abstract/document/10793043/"]}
{"year":"2024","title":"Copilot for Microsoft 365: A Comprehensive End-user Training Plan for Organizations","authors":["M Kytö - 2024"],"snippet":"This thesis presents a comprehensive end user training plan for Copilot for Microsoft 365, a generative AI tool that integrates with Microsoft’s productivity suite of applications. The research is conducted within the context of Sulava Ltd., a Finnish …","url":["https://www.theseus.fi/bitstream/handle/10024/852578/Kyto_Miska.pdf?sequence=2"]}
{"year":"2024","title":"Copyleft for Alleviating AIGC Copyright Dilemma: What-if Analysis, Public Perception and Implications","authors":["X Guo, Y Li, Y Peng, X Wei - arXiv preprint arXiv:2402.12216, 2024"],"snippet":"As AIGC has impacted our society profoundly in the past years, ethical issues have received tremendous attention. The most urgent one is the AIGC copyright dilemma, which can immensely stifle the development of AIGC and greatly cost the entire …","url":["https://arxiv.org/pdf/2402.12216"]}
{"year":"2024","title":"CORAL: Benchmarking Multi-turn Conversational Retrieval-Augmentation Generation","authors":["Y Cheng, K Mao, Z Zhao, G Dong, H Qian, Y Wu… - arXiv preprint arXiv …, 2024"],"snippet":"Retrieval-Augmented Generation (RAG) has become a powerful paradigm for enhancing large language models (LLMs) through external knowledge retrieval. Despite its widespread attention, existing academic research predominantly focuses …","url":["https://arxiv.org/pdf/2410.23090"]}
{"year":"2024","title":"CoRePooL—Corpus for Resource‐Poor Languages: Badaga Speech Corpus","authors":["HB Barathi Ganesh, G Jyothish Lal, R Jairam… - … Speech Recognition and …, 2024"],"snippet":"This chapter presents a corpus named CoRePooL that stands for Corpus for Resource‐Poor Languages. As voice‐specific human‐machine interaction applications are accelerated by deep learning algorithms, the lack of resources …","url":["https://onlinelibrary.wiley.com/doi/abs/10.1002/9781394214624.ch10"]}
{"year":"2024","title":"Corpus Considerations for Annotator Modeling and Scaling","authors":["OO Sarumi, B Neuendorf, J Plepi, L Flek, J Schlötterer… - arXiv preprint arXiv …, 2024"],"snippet":"Recent trends in natural language processing research and annotation tasks affirm a paradigm shift from the traditional reliance on a single ground truth to a focus on individual perspectives, particularly in subjective tasks. In scenarios where …","url":["https://arxiv.org/html/2404.02340v1"]}
{"year":"2024","title":"CorpusNÓS: A massive Galician corpus for training large language models","authors":["I de-Dios-Flores, SP Suárez, CC Pérez, DB Outeiriño… - Proceedings of the 16th …, 2024"],"snippet":"CorpusNÓS is a massive Galician corpus made up of 2.1 B words primarily devised for training large language models. The corpus sources are varied and represent a relatively wide range of genres. CorpusNÓS is, to the best of our knowledge, the …","url":["https://aclanthology.org/2024.propor-1.66.pdf"]}
{"year":"2024","title":"Correcting Auditory Spelling Mistakes in Jordanian Dialect Using Machine Learning Techniques","authors":["M Smadi, G Abandah - 2024 15th International Conference on Information and …, 2024"],"snippet":"This paper explores the application of machine learning techniques, specifically leveraging an efficient transformer model known as Byt5, to rectify Arabic auditory spelling mistakes. The model is trained using datasets with synthetic errors …","url":["https://ieeexplore.ieee.org/abstract/document/10638311/"]}
{"year":"2024","title":"Cost-Effective Big Data Orchestration Using Dagster: A Multi-Platform Approach","authors":["H Picatto, G Heiler, P Klimek - arXiv preprint arXiv:2408.11635, 2024"],"snippet":"… The Common Crawl dataset is a particular promising avenue for this kind of research, as it also contains historic data which allows one to … The temporal partitioning aligns with the Common Crawl1 dataset used, facilitating efficient data …","url":["https://arxiv.org/pdf/2408.11635"]}
{"year":"2024","title":"Cost-Effective Event Mining on the Web via Event Source Page Discovery and Data API Construction","authors":["YH Lin, CH Chang, HM Chuang, XS Lin, T Yeh… - IEEE Access, 2024"],"snippet":"… • Compared to the less than 1% of event pages found in the Common Crawl and Clueweb datasets when crawling the entire web, a significantly higher proportion of events, 13.3%, were identified when specifically targeting the websites of potential …","url":["https://ieeexplore.ieee.org/iel8/6287639/6514899/10638638.pdf"]}
{"year":"2024","title":"Cost-efficient prompt engineering for unsupervised entity resolution in the product matching domain","authors":["N Nananukul, K Sisaengsuwanchai, M Kejriwal - Discover Artificial Intelligence, 2024"],"snippet":"… Web Data Commons (WDC) [52]: The full version of this dataset contains 26 million products and descriptions from different e-commerce websites scraped from the Web as part of the Web Data Commons (Common Crawl). The products are …","url":["https://link.springer.com/article/10.1007/s44163-024-00159-8"]}
{"year":"2024","title":"Count information: retrieving and estimating cardinality of entity sets from the web","authors":["S Ghosh - 2024"],"snippet":"… (2007)], and massive crawls of the Web released regularly by the Common Crawl since 2008 [Crawl(2008)]. Wikipedia, for instance, is a … While C4 exclusively comes from pre-processing and filtering the Common Crawl data, the Pile dataset …","url":["https://publikationen.sulb.uni-saarland.de/bitstream/20.500.11880/38841/1/Thesis_Shrestha_Ghosh.pdf"]}
{"year":"2024","title":"Counter (media) Intelligence and Visioning: An Interview with Adam Harvey","authors":["A Harvey, PB Smith"],"snippet":"… Among the largest and most popular datasets used in AI research projects are Common Crawl (for NLP), and ImageNet and COCO (for computer vision), which are all derived from user-generated content. In my research project Exposing.ai, I’ve …","url":["https://salford-repository.worktribe.com/preview/2389095/Counter%28media%29%20Visioning%20and%20AI%20Harvey%20and%20Smith.pdf"]}
{"year":"2024","title":"Course-Skill Atlas: A national longitudinal dataset of skills taught in US higher education curricula","authors":["A Javadian Sabet, SH Bana, R Yu, MR Frank - Scientific Data, 2024"],"snippet":"Higher education plays a critical role in driving an innovative economy by equipping students with knowledge and skills demanded by the workforce. While researchers and practitioners have developed data systems to track detailed occupational skills …","url":["https://www.nature.com/articles/s41597-024-03931-8"]}
{"year":"2024","title":"Crafting clarity: Leveraging large language models to decode consumer reviews","authors":["SV Praveen, P Gajjar, RK Ray, A Dutt - Journal of Retailing and Consumer Services, 2024"],"snippet":"Large Language Models (LLMs) have emerged as powerful tools for understanding consumer perceptions and extracting insights from unstructured textual data. This study investigates the effectiveness of LLMs in comprehending consumer opinions …","url":["https://www.sciencedirect.com/science/article/pii/S0969698924002716"]}
{"year":"2024","title":"Creating Ad Campaigns Using Generative AI Check for updates","authors":["A Bulut, B Arslan - Applications of Generative AI"],"snippet":"Search campaigns consist of ad groups. An ad group contains a related set of keywords and ads. During an online campaign, search advertisers experiment with different marketing messages such as subtle vs. strong being used in ad copies, with …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=61_8EAAAQBAJ&oi=fnd&pg=PA23&dq=commoncrawl&ots=nk-w5Z-zal&sig=6KV6RzRkuWAeVreoPJlrVlxbFNU"]}
{"year":"2024","title":"Creating Ad Campaigns Using Generative AI","authors":["A Bulut, B Arslan - Applications of Generative AI, 2024"],"snippet":"… In particular, T5 and PEGASUS models were trained on 750 GB of English-language text from the public Common Crawl web scrape while the BART model was trained on the CNN/Daily Mail dataset, which contains roughly 300K unique news articles …","url":["https://link.springer.com/chapter/10.1007/978-3-031-46238-2_2"]}
{"year":"2024","title":"Creating Parallel Corpora for Ukrainian: a German-Ukrainian Parallel Corpus (ParaRook|| DE-UK)","authors":["M Shvedova, A Lukashevskyi - Proceedings of the Third Ukrainian Natural Language …, 2024"],"snippet":"Parallel corpora are currently a popular and vibrantly developing category of linguistic resources, used both in literature and translation studies, as well as in the field of NLP. For Ukrainian, though, there are still not enough significant parallel …","url":["https://aclanthology.org/2024.unlp-1.3.pdf"]}
{"year":"2024","title":"Creation of AI-driven Smart Spaces for Enhanced Indoor Environments--A Survey","authors":["A Varol, NH Motlagh, M Leino, S Tarkoma, J Virkki - arXiv preprint arXiv:2412.14708, 2024"],"snippet":"Smart spaces are ubiquitous computing environments that integrate diverse sensing and communication technologies to enhance space functionality, optimize energy utilization, and improve user comfort and well-being. The integration of emerging AI …","url":["https://arxiv.org/pdf/2412.14708"]}
{"year":"2024","title":"Creative Writers' Attitudes on Writing as Training Data for Large Language Models","authors":["KI Gero, M Desai, C Schnitzler, N Eom, J Cushman… - arXiv preprint arXiv …, 2024"],"snippet":"The use of creative writing as training data for large language models (LLMS) is highly contentious. While some argue that such use constitutes \"fair use\" and therefore does not require consent or compensation, others argue that consent and …","url":["https://arxiv.org/pdf/2409.14281"]}
{"year":"2024","title":"CroissantLLM: A Truly Bilingual French-English Language Model","authors":["M Faysse, P Fernandes, N Guerreiro, A Loison, D Alves… - arXiv preprint arXiv …, 2024"],"snippet":"We introduce CroissantLLM, a 1.3B language model pretrained on a set of 3T English and French tokens, to bring to the research and industrial community a high-performance, fully open-sourced bilingual model that runs swiftly on consumer-grade local …","url":["https://arxiv.org/pdf/2402.00786"]}
{"year":"2024","title":"Cross-cultural Inspiration Detection and Analysis in Real and LLM-generated Social Media Data","authors":["O Ignat, GG Lakshmy, R Mihalcea - arXiv preprint arXiv:2404.12933, 2024"],"snippet":"Inspiration is linked to various positive outcomes, such as increased creativity, productivity, and happiness. Although inspiration has great potential, there has been limited effort toward identifying content that is inspiring, as opposed to just engaging …","url":["https://arxiv.org/pdf/2404.12933"]}
{"year":"2024","title":"Cross-Language Harmonization of Linguistic Resources","authors":["D Zeman"],"snippet":"The presented work consists of two parts. In the first part I summarize the main directions of my research since the defense of my PhD thesis in 2005. I start with cross-language transfer of parsing models to languages that have little or no …","url":["https://chres.is.cuni.cz/media/documents/2024/02/25/thesis-without-papers.pdf"]}
{"year":"2024","title":"Cross-language Retrieval","authors":["P Galuščáková, DW Oard, S Nair - Information Retrieval: Advanced Topics and …, 2024"],"snippet":"8.1 Two key assumptions shape the usual view of ranked retrieval:(1) that the searcher can choose words for their query that might appear in the documents that they wish to see, and (2) that ranking retrieved documents will suffice because the …","url":["https://dl.acm.org/doi/pdf/10.1145/3674127.3674136"]}
{"year":"2024","title":"Cross-Lingual Cross-Modal Retrieval with Noise-Robust Fine-Tuning","authors":["R Cai, J Dong, T Liang, Y Liang, Y Wang, X Yang… - IEEE Transactions on …, 2024"],"snippet":"… from snapshots of the CommonCrawl public dataset2. Experiments in this paper concern parallel data between English and other four languages, namely Chinese (ZH), French (FR), German (DE) and Czech (CZ). Evaluation metrics. … https://commoncrawl.org/ …","url":["https://www.computer.org/csdl/journal/tk/5555/01/10530137/1WUyX1bSatO"]}
{"year":"2024","title":"Cross-lingual Editing in Multilingual Language Models","authors":["H Beniwal, M Singh - arXiv preprint arXiv:2401.10521, 2024"],"snippet":"The training of large language models (LLMs) necessitates substantial data and computational resources, and updating outdated LLMs entails significant efforts and resources. While numerous model editing techniques (METs) have emerged to …","url":["https://arxiv.org/pdf/2401.10521"]}
{"year":"2024","title":"Cross-lingual Human-Preference Alignment for Neural Machine Translation with Direct Quality Optimization","authors":["K Uhlig, J Wuebker, R Reinauer, J DeNero - arXiv preprint arXiv:2409.17673, 2024"],"snippet":"Reinforcement Learning from Human Feedback (RLHF) and derivative techniques like Direct Preference Optimization (DPO) are task-alignment algorithms used to repurpose general, foundational models for specific tasks. We show that applying …","url":["https://arxiv.org/pdf/2409.17673"]}
{"year":"2024","title":"Cross-Lingual Named Entity Recognition for Low-Resource Languages: A Hindi-Nepali Case Study Using Multilingual BERT Models","authors":["D Yadav, S Suravee, T Strauß, K Yordanova - Proceedings of the Fourth Workshop on …, 2024"],"snippet":"… RemBERT (Rebalanced multilingual BERT) is a transformer model trained on large unlabeled Wikipedia and Common Crawl 2 data in … ) MuRIL (Multilingual Representations for Indian Languages) is a transformer-based model trained on the …","url":["https://aclanthology.org/2024.mrl-1.12.pdf"]}
{"year":"2024","title":"Cross-lingual Transfer and Multilingual Learning for Detecting Harmful Behaviour in African Under-Resourced Language Dialogue","authors":["TO Ajayi, M Arcan, P Buitelaar - Proceedings of the 25th Annual Meeting of the …, 2024"],"snippet":"Most harmful dialogue detection models are developed for high-resourced languages. Consequently, users who speak under-resourced languages cannot fully benefit from these models in terms of usage, development, detection and …","url":["https://aclanthology.org/2024.sigdial-1.49.pdf"]}
{"year":"2024","title":"Cross-lingual transfer for the annotation of the SynSemClass ontology","authors":["P Kašpárek - 2024"],"snippet":"This work compares two approaches to automatic preannotation of semantic class to verbs in a sentence for the purpose of adding a new language to the SynSemClass ontology. Both approaches rely on a multilingual deep learning classification model …","url":["https://dspace.cuni.cz/bitstream/handle/20.500.11956/192066/130389119.pdf?sequence=1"]}
{"year":"2024","title":"Cross-Lingual Transfer of Debiasing and Detoxification in Multilingual LLMs: An Extensive Investigation","authors":["V Neplenbroek, A Bisazza, R Fernández - arXiv preprint arXiv:2412.14050, 2024"],"snippet":"… We select the Common Crawl corpus to investigate percentages of language data as we assume models have likely been trained on it, or a similar collection of web crawl data. We select the Common Crawl version from week 30 of 2024, as this is …","url":["https://arxiv.org/pdf/2412.14050"]}
{"year":"2024","title":"Cross-lingual transfer of multilingual models on low resource African Languages","authors":["H Thangaraj, A Chenat, JS Walia, V Marivate - arXiv preprint arXiv:2409.10965, 2024"],"snippet":"… 2019) introduce XLM-R, a large-scale multilingual language model trained on 100 languages using two terabytes of CommonCrawl data. XLM-R offers better performance than models such as mBERT, particularly in low-resource languages such as …","url":["https://arxiv.org/pdf/2409.10965"]}
{"year":"2024","title":"Cultural Fidelity in Large-Language Models: An Evaluation of Online Language Resources as a Driver of Model Performance in Value Representation","authors":["S Kazemi, G Gerhardt, J Katz, CI Kuria, E Pan… - arXiv preprint arXiv …, 2024"],"snippet":"The training data for LLMs embeds societal values, increasing their familiarity with the language's culture. Our analysis found that 44% of the variance in the ability of GPT-4o to reflect the societal values of a country, as measured by the World Values …","url":["https://arxiv.org/pdf/2410.10489"]}
{"year":"2024","title":"Current strategies to address data scarcity in artificial intelligence-based drug discovery: A comprehensive review","authors":["A Gangwal, A Ansari, I Ahmad, AK Azad… - Computers in Biology and …, 2024"],"snippet":"Artificial intelligence (AI) has played a vital role in computer-aided drug design (CADD). This development has been further accelerated with the increasing use of machine learning (ML), mainly deep learning (DL), and computing hardware and software …","url":["https://www.sciencedirect.com/science/article/pii/S0010482524008199"]}
{"year":"2024","title":"Cyber Risks of Machine Translation Critical Errors: Arabic Mental Health Tweets as a Case Study","authors":["H Saadany, A Tantawy, C Orasan - arXiv preprint arXiv:2405.11668, 2024"],"snippet":"With the advent of Neural Machine Translation (NMT) systems, the MT output has reached unprecedented accuracy levels which resulted in the ubiquity of MT tools on almost all online platforms with multilingual content. However, NMT systems, like …","url":["https://arxiv.org/pdf/2405.11668"]}
{"year":"2024","title":"Cyberbullying Detection Using PCA Extracted GLOVE Features and RoBERTaNet Transformer Learning Model","authors":["M Umer, EA Alabdulqader, AA Alarfaj, L Cascone… - IEEE Transactions on …, 2024"],"snippet":"Online platforms are nurturing social interactions, yet regrettably, they have also led to the proliferation of antisocial behaviors such as cyberbullying, trolling, and hate speech on a global scale. The identification of hate speech and aggression has …","url":["https://ieeexplore.ieee.org/iel8/6570650/6780646/10666825.pdf"]}
{"year":"2024","title":"D3. 2: Report on Citizen discourses and attitudes towards controversies","authors":["P Troullinou, I Bonavita, FU TRI, FT ERI, S Stoyanov…"],"snippet":"… Social media listening analysed data from the open web repository, CommonCrawl, for the period 2013-2021. The analysis indicated which … Social listening The findings of the analysis conducted on the CommonCrawl database will …","url":["https://www.pop-ai.eu/wp-content/uploads/2024/03/popAI-D3.2-Report-on-citizen-discourses-and-attitudes-towards-controversies.pdf"]}
{"year":"2024","title":"DANSK: Domain Generalization of Danish Named Entity Recognition","authors":["K Enevoldsen, ET Jessen, R Baglini - Northern European Journal of Language …, 2024"],"snippet":"Named entity recognition is an important application within Danish NLP, essential within both industry and research. However, Danish NER is inhibited by a lack coverage across domains and entity types. As a consequence, no current models …","url":["https://nejlt.ep.liu.se/article/view/5249/4332"]}
{"year":"2024","title":"Data Analysis of Twitter's Nasdaq100 Sentiments and Topics as Indicators for News Articles Retrieval: Fine-Tuning RoBERTa and RAG","authors":["K Timur - 2024"],"snippet":"This study explores the combination of sentiment analysis with vader-lexicon and semantic analysis with latent dirichlet allocation to identify real-life events, particularly in the context of Twitter datasets. While sentiment analysis alone may not …","url":["https://arc.cct.ie/cgi/viewcontent.cgi?article=1048&context=ict"]}
{"year":"2024","title":"Data Analyst Competencies: A Theory-Driven Investigation of Industry Requirements in the Field of Data Analytics","authors":["CA Collier, AL Powell - Journal of Information Systems Education, 2024"],"snippet":"… First, the job postings utilized in Dong and Triche’s study were not comprehensive but rather only those captured by the Common Crawl tool to facilitate the longitudinal nature of their study. Second, the wildcard searches used by Dong and Triche …","url":["https://aisel.aisnet.org/jise/vol35/iss3/8/"]}
{"year":"2024","title":"Data Augmentation and Large Language Model for Legal Case Retrieval and Entailment","authors":["MQ Bui, DT Do, NK Le, DH Nguyen, KVH Nguyen… - The Review of Socionetwork …, 2024"],"snippet":"The Competition on Legal Information Extraction and Entailment (COLIEE) is a well-known international competition organized each year with the goal of applying machine learning algorithms and techniques in the analysis and understanding of legal …","url":["https://link.springer.com/article/10.1007/s12626-024-00158-2"]}
{"year":"2024","title":"Data augmentation for language generation inspired by machine translation","authors":["P Chen - 2024"],"snippet":"The field of natural language processing has witnessed a surge in the adoption of deep learning, which faces notable hurdles when the training data is scarce. This thesis aims to study automatic data augmentation for language generation tasks …","url":["https://era.ed.ac.uk/bitstream/handle/1842/41873/Chen2024.pdf?sequence=1&isAllowed=y"]}
{"year":"2024","title":"Data Augmentation with Semantic Enrichment for Deep Learning Invoice Text Classification","authors":["WW Chi, TY Tang, NM Salleh, M Mukred, H AlSalman… - IEEE Access, 2024"],"snippet":"Natural language processing (NLP) is a research field that provides huge potential to automate accounting tasks dealing with text data. This research studies the application of NLP in automatically categorizing invoices based on the invoice text …","url":["https://ieeexplore.ieee.org/iel7/6287639/6514899/10496671.pdf"]}
{"year":"2024","title":"Data Authenticity, Consent, & Provenance for AI are all broken: what will it take to fix them?","authors":["S Longpre, R Mahari, N Obeng-Marnu, W Brannon… - arXiv preprint arXiv …, 2024"],"snippet":"… Common Crawl is accurate with wide coverage, but not detailed. Hugging Face can be inaccurate with varying levels of detail, but it has extensive coverage. The Data Provenance Initiative is highly accurate and detailed but is currently limited in scope. …","url":["https://arxiv.org/pdf/2404.12691"]}
{"year":"2024","title":"Data Collection Pipeline for Low-Resource Languages: A Case Study on Constructing a Tetun Text Corpus","authors":["G de Jesus, SS Nunes - Proceedings of the 2024 Joint International Conference …, 2024"],"snippet":"This paper proposes Labadain Crawler, a data collection pipeline tailored to automate and optimize the process of constructing textual corpora from the web, with a specific target to low-resource languages. The system is built on top of Nutch, an …","url":["https://aclanthology.org/2024.lrec-main.390.pdf"]}
{"year":"2024","title":"Data Contamination Report from the 2024 CONDA Shared Task","authors":["O Sainz, I García-Ferrero, A Jacovi, JA Campos… - arXiv preprint arXiv …, 2024"],"snippet":"… The reported corpora are mainly based on CommonCrawl snapshots, GitHub, or a mix of sources. For CommonCrawlbased corpora, there are 35 events reported for C4 (Raffel et al.… Ortiz Su’arez et al., 2019) and 6 for CommonCrawl (Rana…","url":["https://arxiv.org/pdf/2407.21530"]}
{"year":"2024","title":"Data Engineering for Scaling Language Models to 128K Context","authors":["Y Fu, R Panda, X Niu, X Yue, H Hajishirzi, Y Kim… - arXiv preprint arXiv …, 2024"],"snippet":"We study the continual pretraining recipe for scaling language models' context lengths to 128K, with a focus on data engineering. We hypothesize that long context modeling, in particular \\textit{the ability to utilize information at arbitrary input …","url":["https://arxiv.org/pdf/2402.10171"]}
{"year":"2024","title":"Data Mixing Made Efficient: A Bivariate Scaling Law for Language Model Pretraining","authors":["C Ge, Z Ma, D Chen, Y Li, B Ding - arXiv preprint arXiv:2405.14908, 2024"],"snippet":"Large language models exhibit exceptional generalization capabilities, primarily attributed to the utilization of diversely sourced data. However, conventional practices in integrating this diverse data heavily rely on heuristic schemes, lacking …","url":["https://arxiv.org/pdf/2405.14908"]}
{"year":"2024","title":"Data Mixture Inference Attack: BPE Tokenizers Reveal Training Data Compositions","authors":["J Hayase, A Liu, Y Choi, S Oh, NA Smith - ICML 2024 Workshop on Foundation Models in …","J Hayase, A Liu, Y Choi, S Oh, NA Smith - The Thirty-eighth Annual Conference on Neural …"],"snippet":"… Natural Language Mixtures We use the Oscar v23.01 corpus [1], which is based on the Nov/Dec 2022 dump from Common Crawl. We … -23.01, which is the January 2023 version of the OSCAR Corpus based on the November/December …","url":["https://openreview.net/pdf?id=0SRg6Cwx3h","https://openreview.net/pdf?id=EHXyeImux0"]}
{"year":"2024","title":"Data Mixture Inference: What do BPE Tokenizers Reveal about their Training Data?","authors":["J Hayase, A Liu, Y Choi, S Oh, NA Smith - arXiv preprint arXiv:2407.16607, 2024"],"snippet":"… on the Nov/Dec 2022 dump from Common Crawl. We consider the 112 languages with at least 1 MB of data. … The training data is reportedly sourced from Common Crawl … November/December 2022 dump of Common Crawl. We only …","url":["https://arxiv.org/pdf/2407.16607"]}
{"year":"2024","title":"Data Processing for the OpenGPT-X Model Family","authors":["N Brandizzi, H Abdelwahab, A Bhowmick, L Helmer… - arXiv preprint arXiv …, 2024"],"snippet":"… RefinedWeb [40] is a 2.8TB English dataset created from filtered CommonCrawl data, employing the MacroData refinement pipeline. … CommonCrawl derived data combined with code, social media, scientific papers, and fiction from the specialized …","url":["https://arxiv.org/pdf/2410.08800"]}
{"year":"2024","title":"Data Proportion Detection for Optimized Data Management for Large Language Models","authors":["H Liang, K Zhao, Y Yang, B Cui, G Dong, Z Zhou… - arXiv preprint arXiv …, 2024"],"snippet":"… initial data proportion detection process accurately identifies the proportions of common-crawl and code, as they constitute a significant portion of the dataset. However, for other categories, the preliminary detection method fails to accurately …","url":["https://arxiv.org/pdf/2409.17527"]}
{"year":"2024","title":"Data Selection for Generalization in Unimodal & Multimodal Models","authors":["A Maharana - 2024"],"snippet":"In this thesis, I present research on improving datasets for deep learning models with automateddata transformation methods. The immediate goal of this work is to maximize the in-domainperformance, out-of-domain generalization, and robustness …","url":["https://cdr.lib.unc.edu/downloads/9019sd14f"]}
{"year":"2024","title":"Data Selection for Task-Specific Model Finetuning","authors":["Z Liu, A Karbasi, T Rekatsinas - arXiv preprint arXiv:2410.11303, 2024"],"snippet":"… For example, a study [13] on several snapshots of ClueWeb2 and Common Crawl shows that 14% to 52% of the documents are near-duplicates. Previous … The high volume of candidate data (eg, 250 billion pages in Common Crawl) poses a great …","url":["https://arxiv.org/pdf/2410.11303"]}
{"year":"2024","title":"Data Selection via Optimal Control for Language Models","authors":["Y Gu, L Dong, H Wang, Y Hao, Q Dong, F Wei… - arXiv preprint arXiv …, 2024"],"snippet":"… In our experiments, we select data from the CommonCrawl2 with PDS and pre-train LMs with 160M, 470M, 1B, and 1.7B parameters from scratch. We observe around 2 times speed-up in pre-training on the 1.7B LM and constant improvement in …","url":["https://arxiv.org/pdf/2410.07064"]}
{"year":"2024","title":"Data, Data Everywhere: A Guide for Pretraining Dataset Construction","authors":["J Parmar, S Prabhumoye, J Jennings, B Liu… - arXiv preprint arXiv …, 2024"],"snippet":"… We close this gap by conducting a large-scale analysis on over 90 Common Crawl web snapshots for the attributes of domain, quality, toxicity, and type of speech. We then show how such data attributes can aid in pretraining set construction to …","url":["https://arxiv.org/pdf/2407.06380"]}
{"year":"2024","title":"Data-centric Advanced Knowledge Interface for Legal Archives","authors":["M Roque, S Chu, M Cabatuan, N Abejuela, M Ng…"],"snippet":"This study presents an innovative and novel approach to section retrieval from the National Internal Revenue Code (NIRC) of the Philippines, leveraging advanced Natural Language Processing (NLP) techniques. The study shares the first …","url":["https://pcsc.dlsu.edu.ph/proceedings/main-conference/28.pdf"]}
{"year":"2024","title":"Data-Centric AI Governance: Addressing the Limitations of Model-Focused Policies","authors":["R Gupta, L Walker, R Corona, S Fu, S Petryk… - arXiv preprint arXiv …, 2024"],"snippet":"… 2009) and Common Crawl,9 brought modern machine learning capabilities to bear. Today, AI datasets are often orders of magnitude larger, created by scraping content across the internet. … 9https://commoncrawl.org/the-data/ …","url":["https://arxiv.org/pdf/2409.17216"]}
{"year":"2024","title":"Data-Centric and Heterogeneity-Adaptive Sequence Parallelism for Efficient LLM Training","authors":["Y Wang, S Wang, S Zhu, F Fu, X Liu, X Xiao, H Li, J Li… - arXiv preprint arXiv …, 2024"],"snippet":"… mechanism in sequence blaster (§4.2), we compare the performance of complete version of FlexSP against various ablated versions on CommonCrawl, as shown in Fig. 7. Sequence sorting in sequence blaster helps reduce sequence length …","url":["https://arxiv.org/pdf/2412.01523"]}
{"year":"2024","title":"Data-Centric Methods for Decentralizing Large Language Models","authors":["S Gururangan - 2024"],"snippet":"… from large web crawl services like Common Crawl. Web crawl is perceived to be wholly representative of activity on the Internet [Brügger… Indeed, web dumps like Common Crawl offer the promise of more diverse text than what is available in …","url":["https://digital.lib.washington.edu/researchworks/bitstream/handle/1773/51332/Gururangan_washington_0250E_26513.pdf?sequence=1&isAllowed=y"]}
{"year":"2024","title":"Data-Prep-Kit: getting your data ready for LLM application development","authors":["D Wood, B Lublinsky, A Roytman, S Singh, A Adebayo… - arXiv preprint arXiv …, 2024"],"snippet":"Data preparation is the first and a very important step towards any Large Language Model (LLM) development. This paper introduces an easy-to-use, extensible, and scale-flexible open-source data preparation toolkit called Data Prep Kit (DPK). DPK …","url":["https://arxiv.org/pdf/2409.18164"]}
{"year":"2024","title":"Data-to-Text Generation with Neural Language Models","authors":["Z Kasner"],"snippet":"Data-to-text generation systems need to produce texts with high levels of semantic accuracy. Rule-based systems can guarantee this aspect, but their fluency and adaptability to new domains remain limited. Meanwhile, neural language models …","url":["https://kasnerz.github.io/assets/papers/pdf/thesis.pdf"]}
{"year":"2024","title":"DataComp Challenge","authors":["D Brunner - 2023"],"snippet":"… billion sample image-text dataset filtered from a comparable pool of samples to Common Crawl. For the creation of the LAION-2B dataset, first language filtering is applied to the original Common Crawl pool so that only samples with English texts …","url":["https://pub.tik.ee.ethz.ch/students/2023-HS/GA-2023-09.pdf"]}
{"year":"2024","title":"DataComp-LM: In search of the next generation of training sets for language models","authors":["J Li, A Fang, G Smyrnis, M Ivgi, M Jordan, S Gadre… - arXiv preprint arXiv …, 2024"],"snippet":"… As part of DCLM, we provide a standardized corpus of 240T tokens extracted from Common Crawl, effective pretraining recipes based on the OpenLM framework, and a broad suite of 53 downstream evaluations. Participants in the DCLM benchmark …","url":["https://arxiv.org/abs/2406.11794"]}
{"year":"2024","title":"DataDecon: Data Cleansing Tools for Large Language Model with Efficient Decontamination Techniques","authors":["S Yuenyong, N Buppodom, K Sangkaew… - 2024 19th International Joint …, 2024"],"snippet":"… coRpus) Dataset is a multilingual corpus extracted from Common Crawl by crawling the web and filtering for high quality … from Common Crawl and cleaning the extracted documents. 3) mC4: The mC4 Dataset contains English documents …","url":["https://ieeexplore.ieee.org/abstract/document/10799278/"]}
{"year":"2024","title":"DataSculpt: Crafting Data Landscapes for LLM Post-Training through Multi-objective Partitioning","authors":["K Lu, Z Liang, X Nie, D Pan, S Zhang, K Zhao, W Chen… - arXiv preprint arXiv …, 2024"],"snippet":"… For instance, less than 5% of documents within CommonCrawl exceed 2k tokens in length [8], which hinders LLMs’ exposure to complex narratives. Despite these challenges, significant strides have been made toward enhancing LLMs’ capabilities …","url":["https://arxiv.org/pdf/2409.00997"]}
{"year":"2024","title":"Dataset Decomposition: Faster LLM Training with Variable Sequence Length Curriculum","authors":["H Pouransari, CL Li, JHR Chang, PKA Vasu, C Koc… - arXiv preprint arXiv …, 2024"],"snippet":"… Although the benefits of ICLM with large-scale Common Crawl data (used in our experiments) are marginal in regular evaluation, it significantly boosts long-context evaluation metrics from 27.5 to 28.7 by constructing long data sequences through …","url":["https://arxiv.org/pdf/2405.13226"]}
{"year":"2024","title":"Dataset Growth","authors":["Z Qin, Z Xu, Y Zhou, Z Zheng, Z Cheng, H Tang… - arXiv preprint arXiv …, 2024"],"snippet":"Deep learning benefits from the growing abundance of available data. Meanwhile, efficiently dealing with the growing data scale has become a challenge. Data publicly available are from different sources with various qualities, and it is …","url":["https://arxiv.org/pdf/2405.18347"]}
{"year":"2024","title":"Datasets for Large Language Models: A Comprehensive Survey","authors":["Y Liu, J Cao, C Liu, K Ding, L Jin - arXiv preprint arXiv:2402.18041, 2024"],"snippet":"… The first method involves building upon Common Crawl1. Common Crawl is a massive, unstructured, multilingual web corpus that provides public access to web archives by regularly crawling and storing webpage data from the Internet. However …","url":["https://arxiv.org/pdf/2402.18041"]}
{"year":"2024","title":"Dataverse: Open-Source ETL (Extract, Transform, Load) Pipeline for Large Language Models","authors":["H Park, S Lee, G Gim, Y Kim, D Kim, C Park - arXiv preprint arXiv:2403.19340, 2024"],"snippet":"To address the challenges associated with data processing at scale, we propose Dataverse, a unified open-source Extract-Transform-Load (ETL) pipeline for large language models (LLMs) with a user-friendly design at its core. Easy addition of …","url":["https://arxiv.org/pdf/2403.19340"]}
{"year":"2024","title":"Dated Data: Tracing Knowledge Cutoffs in Large Language Models","authors":["J Cheng, M Marone, O Weller, D Lawrie, D Khashabi… - arXiv preprint arXiv …, 2024"],"snippet":"… Our analysis reveals two reasons for these inconsistencies: (1) temporal biases of CommonCrawl data due to non-trivial amounts of old data in new dumps and (2) complications in LLM deduplication schemes involving semantic duplicates and …","url":["https://arxiv.org/pdf/2403.12958"]}
{"year":"2024","title":"DDK: Distilling Domain Knowledge for Efficient Large Language Models","authors":["J Liu, C Zhang, J Guo, Y Zhang, H Que, K Deng, Z Bai… - arXiv preprint arXiv …, 2024"],"snippet":"Despite the advanced intelligence abilities of large language models (LLMs) in various applications, they still face significant computational and storage demands. Knowledge Distillation (KD) has emerged as an effective strategy to improve the …","url":["https://arxiv.org/pdf/2407.16154"]}
{"year":"2024","title":"DE-COP: Detecting Copyrighted Content in Language Models Training Data","authors":["AV Duarte, X Zhao, AL Oliveira, L Li - arXiv preprint arXiv:2402.09910, 2024"],"snippet":"How can we detect if copyrighted content was used in the training process of a language model, considering that the training data is typically undisclosed? We are motivated by the premise that a language model is likely to identify verbatim …","url":["https://arxiv.org/pdf/2402.09910"]}
{"year":"2024","title":"Dear GPT-3: Collaborative Writing with Neural Networks","authors":["J Becker - Artificial Intelligence-Intelligent Art?: Human-Machine …, 2024"],"snippet":"GPT-3 and I engaged in this dialogue about four months ago. I wanted to develop a collaborative writing project, not only to collectively realise a novel, but also to negotiate poetological questions which might arise during the process. These …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=gDoGEQAAQBAJ&oi=fnd&pg=PA189&dq=commoncrawl&ots=SRY3txNCwF&sig=VbXixnNRFp15ZSTcqSY4fdZnrCA"]}
{"year":"2024","title":"DeBERTa-BiLSTM: A multi-label classification model of arabic medical questions using pre-trained models and deep learning","authors":["BS Al-Smadi - Computers in Biology and Medicine, 2024"],"snippet":"… Using data from CommonCrawl in 100 different languages, the authors in [38] introduce XLM-RoBERTa, an advanced masked multilingual language model. XLM-RoBERTa outperformed previous multilingual models such as XLM and mBERT. [39] …","url":["https://www.sciencedirect.com/science/article/pii/S0010482524000052"]}
{"year":"2024","title":"Deciphering the Role of Representation Disentanglement: Investigating Compositional Generalization in CLIP Models","authors":["R Abbasi, MH Rohban, MS Baghshah - arXiv preprint arXiv:2407.05897, 2024"],"snippet":"… In our experiments, we evaluate CLIP models trained on a diverse selection of datasets, including OpenAI’s private dataset, LAION, YFCC15m, CC12m, DataComp, DFN-5B, WebLI, and CommonCrawl. These models leverage a variety of backbone …","url":["https://arxiv.org/pdf/2407.05897"]}
{"year":"2024","title":"Decluttering the data mess in LLM training","authors":["M Böther, D Graur, X Yao, A Klimovic"],"snippet":"… When training an LLM, developers first collect training data from various sources, such as Wikipedia, Common Crawl, or ArXiv. They then clean the data, which typically involves deduplicating, filtering, and applying classifiers to the data …","url":["https://hotinfra24.github.io/papers/hotinfra24-final5.pdf"]}
{"year":"2024","title":"Decoding the Diversity: A Review of the Indic AI Research Landscape","authors":["S KJ, V Jain, S Bhaduri, T Roy, A Chadha - arXiv preprint arXiv:2406.09559, 2024"],"snippet":"This review paper provides a comprehensive overview of large language model (LLM) research directions within Indic languages. Indic languages are those spoken in the Indian subcontinent, including India, Pakistan, Bangladesh, Sri Lanka, Nepal, and …","url":["https://arxiv.org/pdf/2406.09559"]}
{"year":"2024","title":"Deconstructing AI literacy for librarians","authors":["S Seah - 2024"],"snippet":"In this presentation, Samantha shares ways we can think about AI literacy-how it is similar and dissimilar from traditional information literacy, what we need to know about the mechanics of AI tools, and how SMU Libraries support the different users …","url":["https://ink.library.smu.edu.sg/cgi/viewcontent.cgi?article=1229&context=library_research"]}
{"year":"2024","title":"Deconstructing In-Context Learning: Understanding Prompts via Corruption","authors":["N Shivagunde, V Lialin, S Muckatira, A Rumshisky - arXiv preprint arXiv:2404.02054, 2024"],"snippet":"The ability of large language models (LLMs) to \"learn in context\" based on the provided prompt has led to an explosive growth in their use, culminating in the proliferation of AI assistants such as ChatGPT, Claude, and Bard. These AI …","url":["https://arxiv.org/pdf/2404.02054"]}
{"year":"2024","title":"DecorateLM: Data Engineering through Corpus Rating, Tagging, and Editing with Language Models","authors":["R Zhao, ZL Thai, Y Zhang, S Hu, Y Ba, J Zhou, J Cai… - arXiv preprint arXiv …, 2024"],"snippet":"… Specifically, we select five large pre-training datasets including Common Crawl Chn (CC-CN), Dolma, C4, The Pile, and Baidu Wiki (BD-Wiki). Due to limited resources, we only sample a volume of 100 billion tokens from these datasets. …","url":["https://arxiv.org/pdf/2410.05639"]}
{"year":"2024","title":"Decoupled Vocabulary Learning Enables Zero-Shot Translation from Unseen Languages","authors":["C Mullov, NQ Pham, A Waibel"],"snippet":"Multilingual neural machine translation systems learn to map sentences of different languages into a common representation space. Intuitively, with a growing number of seen languages the encoder sentence representation grows more flexible and …","url":["https://isl.anthropomatik.kit.edu/downloads/ACL2024-paper-carlos.pdf"]}
{"year":"2024","title":"Deep learning aided clinical decision support","authors":["R Schneider - 2023"],"snippet":"Medical professionals create vast amounts of clinical texts during patient care. Often, these documents describe medical cases from anamnesis to the final clinical outcome. Automated understanding and selection of relevant medical records pose …","url":["https://elib.uni-stuttgart.de/bitstream/11682/13875/1/20231204%20Thesis%20Deep%20Learning%20aided%20Clinical%20Decision%20Support.pdf"]}
{"year":"2024","title":"Deep Learning Based Multi-document Summarization","authors":["C Ma - 2024"],"snippet":"In this era of rapidly advancing technology, the exponential increase of data availability makes analyzing and understanding text files a tedious, labor-intensive, and time-consuming task. Multi-document summarization (MDS) is an effective tool …","url":["https://digital.library.adelaide.edu.au/dspace/bitstream/2440/140499/1/Ma2024_PhD.pdf"]}
{"year":"2024","title":"Deep Learning based Visually Rich Document Content Understanding: A Survey","authors":["Y Ding, J Lee, SC Han - arXiv preprint arXiv:2408.01287, 2024"],"snippet":"Visually Rich Documents (VRDs) are essential in academia, finance, medical fields, and marketing due to their multimodal information content. Traditional methods for extracting information from VRDs depend on expert knowledge and manual labor …","url":["https://arxiv.org/pdf/2408.01287"]}
{"year":"2024","title":"Deep Learning for Cross-Domain Data Fusion in Urban Computing: Taxonomy, Advances, and Outlook","authors":["X Zou, Y Yan, X Hao, Y Hu, H Wen, E Liu, J Zhang, Y Li… - arXiv preprint arXiv …, 2024"],"snippet":"As cities continue to burgeon, Urban Computing emerges as a pivotal discipline for sustainable development by harnessing the power of cross-domain data fusion from diverse sources (eg, geographical, traffic, social media, and environmental data) …","url":["https://arxiv.org/pdf/2402.19348"]}
{"year":"2024","title":"Deep Learning for Economists","authors":["M Dell - arXiv preprint arXiv:2407.15339, 2024"],"snippet":"Deep learning provides powerful methods to impute structured information from large-scale, unstructured text and image datasets. For example, economists might wish to detect the presence of economic activity in satellite images, or to measure the topics or …","url":["https://arxiv.org/pdf/2407.15339"]}
{"year":"2024","title":"Deep Learning Impacts in the Field of Artificial Intelligence","authors":["R Gulwani, M Aggarwal - Deep Learning Concepts in Operations Research, 2024"],"snippet":"This book chapter explores the profound impacts of deep learning on the field of artificial intelligence (AI). Deep learning has revolutionized various domains within AI, enabling significant advancements in computer vision, natural language processing …","url":["https://www.taylorfrancis.com/chapters/edit/10.1201/9781003433309-14/deep-learning-impacts-field-artificial-intelligence-reshma-gulwani-minal-aggarwal"]}
{"year":"2024","title":"Deep Learning Model for Tamil Part-of-Speech Tagging","authors":["H Visuwalingam, R Sakuntharaj, J Alawatugoda… - The Computer Journal, 2024"],"snippet":"… These pre-trained word embeddings are trained on Common Crawl and Wikipedia. This model was trained using CBOW with position-weights, in dimension 300, with character n-grams of length 5, a window of size 5 and 10 negatives. …","url":["https://academic.oup.com/comjnl/advance-article/doi/10.1093/comjnl/bxae033/7641754"]}
{"year":"2024","title":"DeepSeek LLM: Scaling Open-Source Language Models with Longtermism","authors":["X Bi, D Chen, G Chen, S Chen, D Dai, C Deng, H Ding… - arXiv preprint arXiv …, 2024"],"snippet":"… Our analysis revealed that deduplicating the entire Common Crawl corpus results in higher removal of duplicate instances compared to deduplicating within a single dump. Table 1 illustrates that deduplicating across 91 dumps eliminates four times …","url":["https://arxiv.org/pdf/2401.02954"]}
{"year":"2024","title":"DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence","authors":["Q Zhu, D Guo, Z Shao, D Yang, P Wang, R Xu, Y Wu… - arXiv preprint arXiv …, 2024"],"snippet":"… For the math corpus, we collect 221B math-related tokens sourced from CommonCrawl using the same pipeline, which approximately doubles the size of the 120B DeepSeekMath corpus (Shao et al., 2024), while for the natural language …","url":["https://arxiv.org/pdf/2406.11931"]}
{"year":"2024","title":"DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal Understanding","authors":["Z Wu, X Chen, Z Pan, X Liu, W Liu, D Dai, H Gao, Y Ma… - arXiv preprint arXiv …, 2024"],"snippet":"We present DeepSeek-VL2, an advanced series of large Mixture-of-Experts (MoE) Vision-Language Models that significantly improves upon its predecessor, DeepSeek-VL, through two key major upgrades. For the vision component, we …","url":["https://arxiv.org/pdf/2412.10302"]}
{"year":"2024","title":"DeepSeek-VL: Towards Real-World Vision-Language Understanding","authors":["H Lu, W Liu, B Zhang, B Wang, K Dong, B Liu, J Sun… - arXiv preprint arXiv …, 2024"],"snippet":"We present DeepSeek-VL, an open-source Vision-Language (VL) Model designed for real-world vision and language understanding applications. Our approach is structured around three key dimensions: We strive to ensure our data is diverse …","url":["https://arxiv.org/pdf/2403.05525"]}
{"year":"2024","title":"DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models","authors":["Z Shao, P Wang, Q Zhu, R Xu, J Song, M Zhang, YK Li… - arXiv preprint arXiv …, 2024"],"snippet":"… the DeepSeekMath Corpus from Common Crawl. As depicted in Figure 2, … Common Crawl, we employ URL-based deduplication and near-deduplication techniques, resulting in 40B HTML web pages. We then recall mathematical web …","url":["https://arxiv.org/pdf/2402.03300"]}
{"year":"2024","title":"Defining Boundaries: The Impact of Domain Specification on Cross-Language and Cross-Domain Transfer in Machine Translation","authors":["L Shahnazaryan, M Beloucif - arXiv preprint arXiv:2408.11926, 2024"],"snippet":"… 2021) and mined from the Common Crawl corpus.While all languages used in our experiments, except for Italian, are considered bridge languages in the M2M-100 model, the lack of information on the exact data sizes mined for each language limits …","url":["https://arxiv.org/pdf/2408.11926"]}
{"year":"2024","title":"Deliverable 3.1: WP3 1st Interim technical report","authors":["A May-Wachowius–UC, A Lintulampi–UC…"],"snippet":"1.1. Background This document is the first Interim Technical Report (deliverable 3.1) prepared within the WP3 New usecases for the ESSnet Trusted Smart Statistics–Web Intelligence Network project (ESSnet TSS-WIN). The report covers the period from …","url":["https://cros.ec.europa.eu/system/files/2023-12/wp3_deliverable_3_1_wp3_1st_interim_technical_report_20220330.pdf"]}
{"year":"2024","title":"Delta: A Cloud-assisted Data Enrichment Framework for On-Device Continual Learning","authors":["C Gong, Z Zheng, F Wu, X Jia, G Chen - arXiv preprint arXiv:2410.18378, 2024"],"snippet":"In modern mobile applications, users frequently encounter various new contexts, necessitating on-device continual learning (CL) to ensure consistent model performance. While existing research predominantly focused on developing …","url":["https://arxiv.org/pdf/2410.18378"]}
{"year":"2024","title":"Demonstration of Efficacy of Exploiting ChatGPT Data to the Transformers-Based Models by Performing Bangla Intent Analysis","authors":["K Shimada - International Journal of Integrated Engineering, 2024"],"snippet":"With the expanding mode of online opinion sharing, an automatic approach to intent analysis is necessary and useful in the practical scenario. Intent analysis inspects persons' and entities’ viewpoints from online user-created texts. Conventional …","url":["https://penerbit.uthm.edu.my/ojs/index.php/ijie/article/download/18533/6864"]}
{"year":"2024","title":"Demystifying Workload Imbalances in Large Transformer Model Training over Variable-length Sequences","authors":["H Li, F Fu, S Lin, H Ge, X Wang, J Niu, J Jiang, B Cui - arXiv preprint arXiv …, 2024"],"snippet":"… Using the LLaMA 7B model and the CommonCrawl dataset, we start with a default setup of 16 GPUs, a maximum sequence length of 32K, and 200K tokens per iteration. By systematically altering one factor while keeping the others constant, we …","url":["https://arxiv.org/pdf/2412.07894"]}
{"year":"2024","title":"Deriving the Meaning of Out-of-Vocabulary Words","authors":["BCS GAZDA"],"snippet":"… It consists of the articles that were collected using CommonCrawl[34]. The articles originated from five Czech news portals: … It is trained on more than 2TB of data from the filtered CommonCrawl[34] containing 100 languages. They report that the …","url":["https://is.muni.cz/th/u58r4/Deriving_meaning_of_the_Out_of_vocabulary_words_Archive.pdf"]}
{"year":"2024","title":"Design and Analysis of Machine Learning Algorithms for Predicting Pattern and Trends of Crime in India","authors":["S Giri"],"snippet":"Crime is very a old concept which transmitted in our society from generation to generation. No one is safe today. Crime is a social evil. Our society suffers a lot because of crimes committed by its members. The world is full of criminals and …","url":["https://lp-admin.mrgroupofcolleges.com/public/storage/notices/6756d02888073.pdf"]}
{"year":"2024","title":"Design of Artificial Intelligence Companion Chatbot","authors":["X Chen, J Kang, C Hu"],"snippet":"With the development of cities and the prevalence of networks, interpersonal relationships have become increasingly distant. When people crave communication, they hope to find someone to confide in. With the rapid advancement of deep …","url":["https://cdn.techscience.cn/files/jnm/2024/TSP_JNM-6/TSP_JNM_45833/TSP_JNM_45833.pdf"]}
{"year":"2024","title":"Design, Implementation and Evaluation of a Chatbot for Accounting Firm: A Fine-Tuning Approach With Two Novel Dataset","authors":["M Basilico - 2024"],"snippet":"Artificial intelligence, particularly in the field of Chatbots, is fundamentally reshaping learning, communication, and work paradigms. This phenomenon has sparked growing interest among businesses, viewing Chatbots as a means to streamline …","url":["https://webthesis.biblio.polito.it/secure/31058/1/tesi.pdf"]}
{"year":"2024","title":"Designing a course for pre-service science teachers using ChatGPT: what ChatGPT brings to the table","authors":["HZ Okulu, N Muslu - Interactive Learning Environments, 2024"],"snippet":"ChatGPT holds significant potential for enhancing learning through integration into education as an advanced chatbot. With the goal of harnessing this potential, our research focused on exploring the utilization of ChatGPT in designing a course plan …","url":["https://www.tandfonline.com/doi/abs/10.1080/10494820.2024.2322462"]}
{"year":"2024","title":"Designing a Robust Radiology Report Generation System","authors":["S Singh - arXiv preprint arXiv:2411.01153, 2024"],"snippet":"Recent advances in deep learning have enabled researchers to explore tasks at the intersection of computer vision and natural language processing, such as image captioning, visual question answering, visual dialogue, and visual language …","url":["https://arxiv.org/pdf/2411.01153"]}
{"year":"2024","title":"Designing a Tactile Document UI for 2D Refreshable Tactile Displays: Towards Accessible Document Layouts for Blind People","authors":["S Alzalabny, O Moured, K Müller, T Schwarz, B Rapp… - Multimodal Technologies …, 2024"],"snippet":"… The dataset was initially curated by crawling 1017 documents from Commoncrawl using a keyword-based filtering approach to capture eight unique artistic categories (refer to Table 1). We then manually selected 37 documents from each category, ensuring …","url":["https://www.mdpi.com/2414-4088/8/11/102"]}
{"year":"2024","title":"Designing an Intelligent System to Map Global Connections","authors":["E Bellamy, K Farrell, A Hopping, J Pinter, M Saju… - 2024"],"snippet":"… Extended Abstract: This study develops a knowledge graph from the Common Crawl News Dataset to provide situational awareness and … We developed a data pipeline to extract semantic content from the Common Crawl News feed and filter it …","url":["https://www.ieworldconference.org/content/WP2024/Papers/GDRKMCC24_2.pdf"]}
{"year":"2024","title":"Designing and developing a dedicated Natural Language Processing Framework for Healthcare Information Technology Management and Assessment","authors":["A Luschi - 2024"],"snippet":"The escalating complexity of the hospital environment, propelled by technological advancements, necessitates a comprehensive exploration of the integration and management of diverse tools and technologies in healthcare settings. In this context …","url":["https://flore.unifi.it/bitstream/2158/1353284/1/Luschi_PhD_Thesis.pdf"]}
{"year":"2024","title":"Designing and engineering a Q&A LLM for network packet representation","authors":["G Dettori - 2024"],"snippet":"As internet traffic continues its ever-growing rapid expansion, the development of solutions for automatic analysis becomes increasingly important for ensuring network performance, security, and reliability. Tools like Wireshark and traffic …","url":["https://webthesis.biblio.polito.it/33158/1/tesi.pdf"]}
{"year":"2024","title":"Designing Heterogeneous LLM Agents for Financial Sentiment Analysis","authors":["F Xing - arXiv preprint arXiv:2401.05799, 2024"],"snippet":"… GPT-3.5 was trained mainly on the Common Crawl corpus [2], which archives the web. BLOOMZ was trained on an even larger Open-science Open-collaboration Text Sources corpus [19], which is mainly crowd-sourced scientific datasets. The five …","url":["https://arxiv.org/pdf/2401.05799"]}
{"year":"2024","title":"Detect Secrets using Machine Learning","authors":["N Deogade"],"snippet":"Leaked secrets detected by malicious actors can lead to a system compromise and have far reaching consequences for entire IT systems. Secrets such as API tokens can be designed to be easily detectable. However, cryptographic keys and …","url":["http://publications.hnu.de/4787/1/masterthesis_290475_deogade%20%281%29.pdf"]}
{"year":"2024","title":"Detecting Dementia from Transcribed Speech in Slovak using Pre-trained BERT Models","authors":["J Staš, D Hládek, A Kopnický - 2024 34th International Conference Radioelektronika …, 2024"],"snippet":"… TB of texts written in 100 languages from the Common Crawl dataset [14]; • RemBERT model6: a Rebalanced multilingual BERT model pre-trained on a large unlabeled text created by the combination of mC4 Common Crawl and Wikipedia …","url":["https://ieeexplore.ieee.org/abstract/document/10524067/"]}
{"year":"2024","title":"Detecting Depression and Anxiety on Social Media Using Selective Masking","authors":["P Mullatahiri - 2024"],"snippet":"Mental health problems are one of the major problems in the world. It is estimated that once in their life, at least one mental health condition will affect one in four people. Depression is the most common condition, with 5\\% of adults suffering from …","url":["https://repositum.tuwien.at/bitstream/20.500.12708/198293/1/Mullatahiri%20Princ%20-%202024%20-%20Detecting%20Depression%20and%20Anxiety%20on%20Social%20Media...pdf"]}
{"year":"2024","title":"Detecting Hidden Meaning in Stock Images","authors":["P Sülzle"],"snippet":"OBJECTIVE − Automated extraction of hidden meaning in stock images− Is it possible to distinguish what is shown from what is meant?− Examine the divergence of text and image− Analyze the usage of stock images and textual descriptions on the web …","url":["https://downloads.webis.de/theses/slides/suelzle_2023.pdf"]}
{"year":"2024","title":"Detecting Machine-Generated News Using Fine-Tuned Transformers","authors":["JH Kuk - 2024"],"snippet":"… The dataset for this research was a collection of pre-generated GPT-2 news articles, along with real news articles gathered from the internet using Common Crawl. This data combined with the latest popular LLMs such as Llama, Gemma …","url":["https://search.proquest.com/openview/7c83a43f564e11b95cb9503b8948722e/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
{"year":"2024","title":"Detecting Textual Deception in Courtroom Testimonies for Romanian Language Using Neural Network Methods","authors":["M Crudu, M Lupea - 2024 IEEE 20th International Conference on Intelligent …, 2024"],"snippet":"Detecting deception through automated tools involves computational techniques to identify falsehoods in text, which is crucial for evaluating the truthfulness of testimonies in the legal field. The present research explores deception detection in …","url":["https://ieeexplore.ieee.org/abstract/document/10793021/"]}
{"year":"2024","title":"Detection of adversarial phishing attack using machine learning techniques","authors":["KM Sudar, M Rohan, K Vignesh - Sādhanā, 2024"],"snippet":"The frequency of cyberattacks, particularly phishing attacks, is increasing exponentially every day. Many users fall victim to clicking on malicious URLs, leading to the exploitation of their information. The traditional methodologies …","url":["https://link.springer.com/article/10.1007/s12046-024-02582-0"]}
{"year":"2024","title":"Detection of bullying with MachineLearning: Using Supervised Machine Learning and LLMs to classify bullying in text","authors":["SA Yousef, L Svensson - 2024"],"snippet":"In recent years, there has been a increase in the issue of bullying, particularly in academic settings [1]. This degree project examines the use of supervised machine learning techniques to identify bullying in text data from school surveys provided by …","url":["https://www.diva-portal.org/smash/get/diva2:1877152/FULLTEXT01.pdf"]}
{"year":"2024","title":"Detection of Hate Speech and Offensive Language CodeMix Text in Dravidian Languages using Cost-Sensitive Learning Approach","authors":["K Sreelakshmi, B Premjith, BR Chakravarthi… - IEEE Access, 2024"],"snippet":"… It was trained using more than two terabytes of filtered CommonCrawl data. It has significantly improved performance on various cross-lingual transfer tasks and outperformed the mBERT model. XLM-R has 24 layers and 16 attention heads …","url":["https://ieeexplore.ieee.org/iel7/6287639/6514899/10419328.pdf"]}
{"year":"2024","title":"DETECTION OF KEY INFORMATION IN EMERGENCY CALLS","authors":["BM SARVAŠ"],"snippet":"… The model used in the experiments was trained on 2.5TB of filtered CommonCrawl data containing 100 languages and has a vocabulary of 250k tokens. Conneau et al. [8] show that such multilingual models can outperform their …","url":["https://theses.cz/id/viznm6/DP_final.pdf"]}
{"year":"2024","title":"Detection of phishing addresses and pages with a data set balancing approach by generative adversarial network (GAN) and convolutional neural network (CNN) …","authors":["S Jafari, N Aghaee‐Maybodi - Concurrency and Computation: Practice and …"],"snippet":"Phishing attacks have a remarkable ability to steal user information by using simple techniques. Phishing attacks steal valuable information, such as user names and passwords. The loss caused by phishing attacks is significant, and every year …","url":["https://onlinelibrary.wiley.com/doi/abs/10.1002/cpe.8033"]}
{"year":"2024","title":"Detection of Sarcasm in Urdu Tweets using Deep Learning and Transformer based Hybrid Approaches","authors":["ME Hassan, M Hussain, I Maab, U Habib, MA Khan… - IEEE Access, 2024"],"snippet":"Sarcasm has a significant role in human communication especially on social media platforms where users express their sentiments through humor, satire, and criticism. The identification of sarcasm is crucial in comprehending the sentiment and the …","url":["https://ieeexplore.ieee.org/iel7/6287639/6514899/10508575.pdf"]}
{"year":"2024","title":"Detection of Twitter Spam Using GLoVe Vocabulary Features, Bidirectional LSTM and Convolution Neural Network","authors":["P Manasa, A Malik, I Batra - SN Computer Science, 2024"],"snippet":"… The training of the GloVe model involves a substantial text corpus, like Wikipedia or Common Crawl, which facilitates the learning of connections between words and phrases. For every word in the corpus, the model creates a vector, wherein each …","url":["https://link.springer.com/article/10.1007/s42979-023-02518-1"]}
{"year":"2024","title":"Developing a Question Answering (QA) Subsystem for Dialogue Systems. Case Study: Theano, a Greek-speaking Conversational Agent for COVID-19","authors":["P Griziotis - 2024"],"snippet":"Basic retrieval-based methods in dialogue systems are restricted by a finite set of predefined responses, often leaving user questions unanswered. In this work, we develop a single-turn Question Answering (QA) subsystem to enhance a closed-domain …","url":["https://pergamos.lib.uoa.gr/uoa/dl/object/3440487/file.pdf"]}
{"year":"2024","title":"Developing a Thai Grammatical Error Correction Tool for Deaf Students","authors":["S Traitruengsakul, E Chuangsuwanich - IEEE Access, 2024"],"snippet":"Deaf students face challenges in written communication due to errors such as insertion, deletion, word order issues, misusage, and misspellings. Grammatical error correction (GEC) technology can help mitigate these issues. However, existing …","url":["https://ieeexplore.ieee.org/iel8/6287639/6514899/10713308.pdf"]}
{"year":"2024","title":"Developing and Backtesting a Trading Strategy Using Large Language Models, Macroeconomic and Technical Indicators","authors":["A Kargarzadeh"],"snippet":"This thesis explores the development and backtesting of a trading strategy that integrates Large Language Models (LLMs) with macroeconomic and technical indicators. The primary objective is to enhance stock return predictions by …","url":["https://www.imperial.ac.uk/media/imperial-college/faculty-of-natural-sciences/department-of-mathematics/math-finance/Kargarzadeh_Alireza_02092220.pdf"]}
{"year":"2024","title":"Developing and Deploying AI Applications on NVIDIA Jetson Orin NX: A Comprehensive Guide","authors":["DC Youvan - 2024"],"snippet":"The NVIDIA Jetson Orin NX is a cutting-edge platform that brings powerful AI capabilities to the edge, enabling a wide range of applications from real-time computer vision to advanced robotics. This comprehensive guide provides detailed …","url":["https://www.researchgate.net/profile/Douglas-Youvan/publication/381434888_Developing_and_Deploying_AI_Applications_on_NVIDIA_Jetson_Orin_NX_A_Comprehensive_Guide/links/666d7390de777205a32fceb6/Developing-and-Deploying-AI-Applications-on-NVIDIA-Jetson-Orin-NX-A-Comprehensive-Guide.pdf"]}
{"year":"2024","title":"Developing ChatGPT for Biology and Medicine: A Complete Review of Biomedical Question Answering","authors":["Q Li, L Li, Y Li - arXiv preprint arXiv:2401.07510, 2024"],"snippet":"ChatGPT explores a strategic blueprint of question answering (QA) in delivering medical diagnosis, treatment recommendations, and other healthcare support. This is achieved through the increasing incorporation of medical domain data via natural …","url":["https://arxiv.org/pdf/2401.07510"]}
{"year":"2024","title":"Development and Evaluation of a German Language Model for the Financial Domain","authors":["N Kozaeva, S Hamotskyi, C Hänig - Proceedings of the Joint Workshop of the 7th …, 2024"],"snippet":"… The German colossal, cleaned Common Crawl corpus15 was employed, comprising texts of varying lengths. Further the results of LM performance for mixed datasets (financial corpus mixed with common language sentences and financial …","url":["https://aclanthology.org/2024.finnlp-1.5.pdf"]}
{"year":"2024","title":"Development and Evaluation of Pre-trained Language Models for Historical Danish and Norwegian Literary Texts","authors":["A Al-Laith, A Conroy, J Bjerring-Hansen… - Proceedings of the 2024 …, 2024"],"snippet":"We develop and evaluate the first pre-trained language models specifically tailored for historical Danish and Norwegian texts. Three models are trained on a corpus of 19th-century Danish and Norwegian literature: two directly on the corpus with no …","url":["https://aclanthology.org/2024.lrec-main.431.pdf"]}
{"year":"2024","title":"Development of a Geographical Question-Answering System in the Kazakh Language","authors":["A Mukanova, A Barlybayev, A Nazyrova, L Kussepova… - IEEE Access, 2024"],"snippet":"… Among the pre-trained models, the KazBERT model, trained on cleansed CommonCrawl data in the Kazakh language, achieved the most favorable outcomes. For the test dataset, the KazBERT model demonstrated an Exact Match (EM) …","url":["https://ieeexplore.ieee.org/iel8/6287639/6514899/10609382.pdf"]}
{"year":"2024","title":"Development of an Adaptive Multi-Domain Artificial Intelligence System Built using Machine Learning and Expert Systems Technologies","authors":["J Straub - arXiv preprint arXiv:2406.11272, 2024"],"snippet":"Producing an artificial general intelligence (AGI) has been an elusive goal in artificial intelligence (AI) research for some time. An AGI would have the capability, like a human, to be exposed to a new problem domain, learn about it and then use …","url":["https://arxiv.org/pdf/2406.11272"]}
{"year":"2024","title":"Development of an Interface for Multi-Dimensional Clinical Language Analysis of Dementia and Assessment of its Market Viability","authors":["A Allard, T Josefsson - 2024"],"snippet":"… This model, from Microsoft, is initialized from the transformer model XLM-RoBERTa-Large, which is pre-trained on 2.5TB of filtered CommonCrawl data containing 100 languages [24]. CommonCrawl data consists of a comprehensive corpus of web …","url":["https://www.diva-portal.org/smash/get/diva2:1884570/FULLTEXT01.pdf"]}
{"year":"2024","title":"Development of Natural Language Processing Tools and Resources for Assamese Text","authors":["D Pathak"],"snippet":"It is my immense pleasure to convey my heartfelt gratitude to my supervisors, Prof. Sukumar Nandi and Prof. Priyankoo Sarmah, for their unwavering support and guidance during my research work. I am grateful to both of my supervisors for …","url":["https://gyan.iitg.ac.in/bitstreams/6c06d24f-f5b1-4911-9caf-9ff3484e92e2/download"]}
{"year":"2024","title":"Diagonalization & Forcing FLEX: From Cantor to Cohen and Beyond","authors":["E Moritz - 2024"],"snippet":"Background: Maybe very high energy cosmic radiation started a synaptic butterfly cascade 2... who knows? For one reason or another, I decided to embark on a journey of exploring and discussing the possible role of Artificial Intelligence (AI) on …","url":["https://www.academia.edu/download/113574252/Moritz_Diagonalization_FLEX_21APR2024.pdf","https://www.researchgate.net/profile/Elan-Moritz/publication/379960940_Diagonalization_Forcing_FLEX_From_Cantor_to_Cohen_and_Beyond_Alt_Title_Learning_from_Leibniz_Cantor_Turing_Godel_and_Cohen_crawling_towards_AGI/links/662498f743f8df018d1e5573/Diagonalization-Forcing-FLEX-From-Cantor-to-Cohen-and-Beyond-Alt-Title-Learning-from-Leibniz-Cantor-Turing-Goedel-and-Cohen-crawling-towards-AGI.pdf"]}
{"year":"2024","title":"Dialectal and Low Resource Machine Translation for Aromanian","authors":["AI Jerpelea, AŞ Rădoi, S Nisioi - arXiv preprint arXiv:2410.17728, 2024"],"snippet":"We present a neural machine translation system that can translate between Romanian, English, and Aromanian (an endangered Eastern Romance language); the first of its kind. BLEU scores range from 17 to 32 depending on the direction and …","url":["https://arxiv.org/pdf/2410.17728"]}
{"year":"2024","title":"Differentially Private Low-Rank Adaptation of Large Language Model Using Federated Learning","authors":["XY Liu, R Zhu, D Zha, J Gao, S Zhong, M Qiu - arXiv preprint arXiv:2312.17493, 2023"],"snippet":"The surge in interest and application of large language models (LLMs) has sparked a drive to fine-tune these models to suit specific applications, such as finance and medical science. However, concerns regarding data privacy have emerged …","url":["https://arxiv.org/pdf/2312.17493"]}
{"year":"2024","title":"Diffused Seeing: The Epistemological Challenge","authors":["J ZYLINSKA - 2024"],"snippet":"This article examines the transformation of the relationship between seeing and understanding in humans and machines by the technologies of machine learning known as ‘generative AI’. Taking Stable Diffusion as the main case study, while also …","url":["https://kclpure.kcl.ac.uk/portal/files/270820361/229-258_Zylinska.pdf"]}
{"year":"2024","title":"Digilog: Enhancing Website Embedding on Local Governments-A Comparative Analysis","authors":["J Gerber, B Kreiner, J Saxer, A Weiler - International Symposium on Methodologies …, 2024"],"snippet":"The ability to understand and process websites, known as website embedding, is crucial across various domains. It lays the foundation for machine understanding of websites. Specifically, website embedding proves invaluable when monitoring local …","url":["https://link.springer.com/chapter/10.1007/978-3-031-62700-2_12"]}
{"year":"2024","title":"Digital Protection and Innovative Development Path of Red Culture Resources Based on Distributed Machine Learning Supported by Intelligent Information","authors":["M Huang, X Zeng - Journal of Combinatorial Mathematics and …"],"snippet":"As a product of the revolutionary war years, red culture, with its strong vitality, strong cohesion and extraordinary charm, with its incomparable positive energy, resists vulgar and flattering culture, promotes people to rebuild their faith, purify their minds …","url":["https://combinatorialpress.com/article/jcmcc/volume%20120/digital-protection-and-innovative-development-path-of-red-culture-resources-based-on-distributed-machine-learning-supported-by-intelligent-information.pdf"]}
{"year":"2024","title":"Digital Threats","authors":["S Samtani, E Raff, H Anderson, E Domschot… - 2024"],"snippet":"… First, we used the common crawl GloVe embedding, created by Stanford [28]. This embedding was trained over 42 billion tokens, with a 300-dimensional vector space, and was used as the embedding layer of the BiLSTM model. Results are …","url":["https://dl.acm.org/doi/pdf/10.1145/3613525"]}
{"year":"2024","title":"DINOv2 Meets Text: A Unified Framework for Image-and Pixel-Level Vision-Language Alignment","authors":["C Jose, T Moutakanni, D Kang, F Baldassarre, T Darcet…"],"snippet":"… We apply the text and image curation process described in Section 3.2 to an initial data pool derived from CommonCrawl [1], consisting of 2.3 billion image-text pairs. We sample 650 million pairs per-epoch using our curation strategy. For the text-based …","url":["https://arxiv.org/pdf/2412.16334"]}
{"year":"2024","title":"DiPaCo: Distributed Path Composition","authors":["A Douillard, Q Feng, AA Rusu, A Kuncoro, Y Donchev… - arXiv preprint arXiv …, 2024"],"snippet":"Progress in machine learning (ML) has been fueled by scaling neural network models. This scaling has been enabled by ever more heroic feats of engineering, necessary for accommodating ML approaches that require high bandwidth …","url":["https://arxiv.org/html/2403.10616v1"]}
{"year":"2024","title":"Dipartimento di Informatica","authors":["F DELL'ORLETTA, M PAPUCCI"],"snippet":"In recent years, the world of Natural Language Processing (NLP) underwent a revolution that shook the foundation of the field. This brought results that were never achieved before and lead to the creation of products that became commercial hits …","url":["https://michelepapucci.github.io/pdfs/tesi_magistrale.pdf"]}
{"year":"2024","title":"Directionality and representativeness are differentiable components of stereotypes in large language models","authors":["G Nicolas, A Caliskan - PNAS Nexus, 2024"],"snippet":"… The ChatGPT model was trained on vast 19 amounts of data, including the Common Crawl (a large scraping of internet webpages), books, 20 Reddit, and Wikipedia (45), as well as human feedback in reinforcement learning (46), and 21 …","url":["https://academic.oup.com/pnasnexus/advance-article-pdf/doi/10.1093/pnasnexus/pgae493/60396251/pgae493.pdf"]}
{"year":"2024","title":"Disambiguating Homographs and Homophones Simultaneously: A Regrouping Method for Japanese","authors":["Y Sato - Proceedings of the 2024 Joint International Conference …, 2024"],"snippet":"We present a method that re-groups surface forms into clusters representing synonyms, and help disambiguate homographs as well as homophone. The method is applied post-hoc to trained contextual word embeddings. It is beneficial to …","url":["https://aclanthology.org/2024.lrec-main.442.pdf"]}
{"year":"2024","title":"Disambiguating natural language via aligning meaningful descriptions","authors":["Y Xin - 2023"],"snippet":"Artificial Intelligence (AI) technologies are increasingly pervading aspects of our lives. Because people use natural language to communicate with each other, computers should also use natural language to communicate with us. One of the principal …","url":["https://open.bu.edu/bitstream/handle/2144/48024/Xin_bu_0017E_17540.pdf?sequence=6"]}
{"year":"2024","title":"DISENTANGLING AND INTEGRATING RELATIONAL AND SENSORY INFORMATION IN TRANSFORMER ARCHITECTURES","authors":["T ARCHITECTURES"],"snippet":"… We train on 10 billion GPT2 tokens of the FineWeb-Edu dataset [37], which is a curated dataset of high-quality educational text data from CommonCrawl. We train models at multiple parameter scales to study the scaling properties of DAT on …","url":["https://openreview.net/pdf?id=Oq7BhRSy0a"]}
{"year":"2024","title":"Disfluency annotated corpora for Indian English in technical domains","authors":["V Mujadia, P Mishra, DM Sharma - Language Resources and Evaluation, 2024"],"snippet":"Disfluencies are common in spontaneous speech and can significantly affect the accuracy of automated systems that process spoken input. In this work, we tackled this issue for Indian English by developing a human-annotated disfluency corpus (DASIE …","url":["https://link.springer.com/article/10.1007/s10579-024-09781-5"]}
{"year":"2024","title":"Display options","authors":["Z Zhai, C Druckenbrodt, C Thorne"],"snippet":"Chemical patents are a commonly used channel for disclosing novel compounds and reactions, and hence represent important resources for chemical and pharmaceutical research. Key chemical data in patents is often presented in tables …","url":["https://www.uiindex.org/search/articledetails/32298116"]}
{"year":"2024","title":"Dissecting Whiteness: consistencies and differences in the stereotypes of lower-and upper-class White US Americans","authors":["T Morgenroth, CT Begeny, TA Kirby, B Paaßen, Y Zeng - Self and Identity, 2024"],"snippet":"Economic inequality is increasing in the United States, making categorization and stereotyping based on social class more likely. Yet, social class stereotypes have received relatively little attention. Focusing on spontaneously generated stereotypes …","url":["https://www.tandfonline.com/doi/abs/10.1080/15298868.2024.2322179"]}
{"year":"2024","title":"Distance Comparison Operators for Approximate Nearest Neighbor Search: Exploration and Benchmark","authors":["Z Wang, H Xiong, Z He, P Wang - arXiv preprint arXiv:2403.13491, 2024"],"snippet":"Approximate nearest neighbor search (ANNS) on high-dimensional vectors has become a fundamental and essential component in various machine learning tasks. Prior research has shown that the distance comparison operation is the bottleneck of …","url":["https://arxiv.org/html/2403.13491v1"]}
{"year":"2024","title":"Distortions in Judged Spatial Relations in Large Language Models","authors":["N Fulman, A Memduhoğlu, A Zipf - The Professional Geographer, 2024"],"snippet":"We present a benchmark for assessing the capability of large language models (LLMs) to discern intercardinal directions between geographic locations and apply it to three prominent LLMs: GPT-3.5, GPT-4, and Llama-2. This benchmark specifically …","url":["https://www.tandfonline.com/doi/abs/10.1080/00330124.2024.2372792"]}
{"year":"2024","title":"Diversifying Multi-Head Attention in the Transformer Model","authors":["N Ampazis, F Sakketou - Machine Learning and Knowledge Extraction, 2024"],"snippet":"Recent studies have shown that, due to redundancy, some heads of the Transformer model can be pruned without diminishing the efficiency of the model. In this paper, we propose a constrained optimization algorithm based on Hebbian learning, which …","url":["https://www.mdpi.com/2504-4990/6/4/126"]}
{"year":"2024","title":"Do Language Models Care About Text Quality? Evaluating Web-Crawled Corpora Across 11 Languages","authors":["R van Noord, T Kuzman, P Rupnik, N Ljubešić… - arXiv preprint arXiv …, 2024"],"snippet":"… rest of corpora compared in this paper, MaCoCu corpora are not obtained by processing Common Crawl data. Instead, a strategy consisting of crawling relevant internet top-level domains directly for the targeted languages is followed (eg, .al for …","url":["https://arxiv.org/pdf/2403.08693"]}
{"year":"2024","title":"Do llms plan like human writers? comparing journalist coverage of press releases with llms","authors":["A Spangher, N Peng, S Gehrmann, M Dredze - … of the 2024 Conference on Empirical …, 2024"],"snippet":"… We query Common Crawl for all URLs from 9 major financial newspapersin all scrapes since 2021, resulting in 114 million URLs. From these URLs, we discover 940,000 URLs of news articles, specifically, using a supervised model by Welsh (2022) …","url":["https://aclanthology.org/2024.emnlp-main.1216.pdf"]}
{"year":"2024","title":"Do Localization Methods Actually Localize Memorized Data in LLMs? A Tale of Two Benchmarks","authors":["TY Chang, J Thomason, R Jia"],"snippet":"The concept of localization in LLMs is often mentioned in prior work; however, methods for localization have never been systematically and directly evaluated. We propose two complementary benchmarks that evaluate the ability of localization …","url":["https://terarachang.github.io/assests/loc.pdf"]}
{"year":"2024","title":"Do Multilingual Large Language Models Mitigate Stereotype Bias?","authors":["S Nie, M Fromm, C Welch, R Görge, A Karimi, J Plepi… - arXiv preprint arXiv …, 2024"],"snippet":"While preliminary findings indicate that multilingual LLMs exhibit reduced bias compared to monolingual ones, a comprehensive understanding of the effect of multilingual training on bias mitigation, is lacking. This study addresses this gap by …","url":["https://arxiv.org/pdf/2407.05740"]}
{"year":"2024","title":"Do not shut up and do dribble: social media and TV consumption","authors":["M Pazzona, N Spagnolo - Journal of Population Economics, 2024"],"snippet":"… Footnote 11 The NLP model utilized in this study, XLM-RoBERTa, undergoes pre-training on 2.5TB of filtered CommonCrawl data encompassing 100 languages. For tweet classification, we employed the general-purpose Python library TweetNLP (Camacho-Collados …","url":["https://link.springer.com/article/10.1007/s00148-024-01034-7"]}
{"year":"2024","title":"Document Parsing Unveiled: Techniques, Challenges, and Prospects for Structured Information Extraction","authors":["Q Zhang, VSJ Huang, B Wang, J Zhang, Z Wang… - arXiv preprint arXiv …, 2024"],"snippet":"Document parsing is essential for converting unstructured and semi-structured documents-such as contracts, academic papers, and invoices-into structured, machine-readable data. Document parsing extract reliable structured data from …","url":["https://arxiv.org/pdf/2410.21169"]}
{"year":"2024","title":"Document Type Classification using File Names","authors":["Z Li, S Larson, K Leach - arXiv preprint arXiv:2410.01166, 2024"],"snippet":"… We train file name classifiers on the Web Search dataset described in Section 5.1 and evaluate our models against the Common Crawl dataset described in Section 5.2. Recall that 22.2% of the file names in our Common Crawl dataset belong to a …","url":["https://arxiv.org/pdf/2410.01166"]}
{"year":"2024","title":"Document-Level Machine Translation with Large-Scale Public Parallel Corpora","authors":["P Pal, A Birch, K Heafield"],"snippet":"Despite the fact that document-level machine translation has inherent advantages over sentence-level machine translation due to additional information available to a model from document context, most translation systems continue to operate at a …","url":["https://proyag.github.io/files/papers/docmt.pdf"]}
{"year":"2024","title":"Document-Level Similarity Analysis on Pretraining Language Models","authors":["최광호 - 2024"],"snippet":"… CommonCrawl is a project that periodically crawls the entire web, storing snapshots of web content, including textual information, which is made publicly available. C4 (14), or the Colossal Clean Crawled Corpus, is a dataset that refines …","url":["https://s-space.snu.ac.kr/bitstream/10371/209784/1/000000183077.pdf"]}
{"year":"2024","title":"Document-level Translation with LLM Reranking: Team-J at WMT 2024 General Translation Task","authors":["K Kudo, H Deguchi, M Morishita, R Fujii, T Ito, S Ozaki… - Proceedings of the Ninth …, 2024"],"snippet":"… models, we only used the Common Crawl and Extended Common Crawl due to the limited … We qualitatively examined the Common Crawl and Extended Common Crawl datasets. Our … Qualitative analysis of the Common Crawl data revealed a …","url":["https://www2.statmt.org/wmt24/pdf/2024.wmt-1.14.pdf"]}
{"year":"2024","title":"Documenting Geographically and Contextually Diverse Language Data Sources","authors":["A McMillan-Major, F De Toni, Z Alyafeai, S Biderman… - Northern European Journal …, 2024"],"snippet":"… Typically, this data is collected from online sources, ranging from highly edited and structured text such as Wikipedia to the myriad text and audiovisual components of web pages, eg, collected by the Common Crawl Founda… Data from Common …","url":["https://nejlt.ep.liu.se/article/download/5217/4359"]}
{"year":"2024","title":"Does Context Help Mitigate Gender Bias in Neural Machine Translation?","authors":["H Gete, T Etchegoyhen - arXiv preprint arXiv:2406.12364, 2024"],"snippet":"Neural Machine Translation models tend to perpetuate gender bias present in their training data distribution. Context-aware models have been previously suggested as a means to mitigate this type of bias. In this work, we examine this claim by …","url":["https://arxiv.org/pdf/2406.12364"]}
{"year":"2024","title":"Does Lack of Knowledge and Hardship of Information Access Signify Powerful AI? A Large Language Model Perspective","authors":["IA Zahid, SS Joudar - Applied Data Science and Analysis, 2023"],"snippet":"Large Language Models (LLMs) are evolving and expanding enormously. With the consistent improvement of LLMs, more complex and sophisticated tasks will be tackled. Handling various tasks and fulfilling different queries will be more precise …","url":["https://journals.mesopotamian.press/index.php/ADSA/article/download/235/211"]}
{"year":"2024","title":"Does sentiment help in asset pricing? A novel approach using large language models and market-based labels","authors":["F Audrino, J Schüttler, F Sigrist - 2024"],"snippet":"We present a novel approach to sentiment analysis in financial markets by using a state-ofthe-art large language model, a market data-driven labeling approach, and a large dataset consisting of diverse financial text sources including earnings call …","url":["https://www.researchgate.net/profile/Francesco-Audrino/publication/382529609_Does_sentiment_help_in_asset_pricing_A_novel_approach_using_large_language_models_and_market-based_labels/links/66a20a545919b66c9f688c58/Does-sentiment-help-in-asset-pricing-A-novel-approach-using-large-language-models-and-market-based-labels.pdf"]}
{"year":"2024","title":"Does the Language Matter? Curriculum Learning over Neo-Latin Languages","authors":["G Pucci, L Ranaldi - Proceedings of the 2024 Joint International Conference …, 2024"],"snippet":"Curriculum Learning (CL) is emerging as a relevant technique to reduce the cost of pre-training Large Language Models. The idea, tested for the English language, is to train LLMs by organizing training examples from the simplest to the most complex …","url":["https://aclanthology.org/2024.lrec-main.464.pdf"]}
{"year":"2024","title":"Does your data spark joy? Performance gains from domain upsampling at the end of training","authors":["C Blakeney, M Paul, BW Larsen, S Owen, J Frankle - arXiv e-prints, 2024"],"snippet":"Pretraining datasets for large language models (LLMs) have grown to trillions of tokens composed of large amounts of CommonCrawl (CC) web scrape along with smaller, domain-specific datasets. It is expensive to understand the impact of these …","url":["https://ui.adsabs.harvard.edu/abs/2024arXiv240603476B/abstract"]}
{"year":"2024","title":"Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research","authors":["L Soldaini, R Kinney, A Bhagia, D Schwenk, D Atkinson… - arXiv preprint arXiv …, 2024"],"snippet":"… In total, we find 0.02% of documents in the 25 Common Crawl snapshots match this filter. … Head, Middle, and Tail parts of our Common Crawl data. The correlation is computed for 24M, … The correlation among the documents flagged for removal …","url":["https://arxiv.org/pdf/2402.00159"]}
{"year":"2024","title":"Domain-Specific Pretraining of Language Models: A Comparative Study in the Medical Field","authors":["T Kerner - arXiv preprint arXiv:2407.14076, 2024"],"snippet":"… CommonCrawl, or collecting multiple datasets that are at least slightly related to our domain. Large-scale webscraping is a timeand resource-intensive task, so it is recommended to consider using data from CommonCrawl … [3] Assuming we chose …","url":["https://arxiv.org/pdf/2407.14076"]}
{"year":"2024","title":"DomURLs_BERT: Pre-trained BERT-based Model for Malicious Domains and URLs Detection and Classification","authors":["AE Mahdaouy, S Lamsiyah, MJ Idrissi, H Alami… - arXiv preprint arXiv …, 2024"],"snippet":"… This is a cleaned version of the Common Crawl’s web corpus, curated by the Allen Institute for Artificial Intelligence [38], containing … This dataset is compiled from CommonCrawl, using strict filtering and extensive deduplication [39], and …","url":["https://arxiv.org/pdf/2409.09143"]}
{"year":"2024","title":"DoPAMine: Domain-specific Pre-training Adaptation from seed-guided data Mining","authors":["V Arannil, SS Bhabesh, N Narwal, SN Thirandas… - arXiv preprint arXiv …, 2024"],"snippet":"… From a large corpus D like the Common Crawl [16], we can now mine and collate real-world domain-representative documents for all industries listed in table 1. It is possible that a mined document may belong to multiple industry domains. We …","url":["https://arxiv.org/pdf/2410.00260"]}
{"year":"2024","title":"Downstream bias mitigation is all you need","authors":["A Baksi, R Singh, T Joshi - arXiv preprint arXiv:2408.00612, 2024"],"snippet":"The advent of transformer-based architectures and large language models (LLMs) have significantly advanced the performance of natural language processing (NLP) models. Since these LLMs are trained on huge corpuses of data from the web and …","url":["https://arxiv.org/pdf/2408.00612"]}
{"year":"2024","title":"DPHANet: Discriminative Parallel and Hierarchical Attention Network for Natural Language Video Localization","authors":["R Chen, J Tan, Z Yang, X Yang, Q Dai, Y Cheng, L Lin - IEEE Transactions on …, 2024"],"snippet":"Natural Language Video Localization (NLVL) has recently attracted much attention because of its practical significance. However, the existing methods still face the following challenges: 1) When the models learn intra-modal semantic association …","url":["https://ieeexplore.ieee.org/abstract/document/10517423/"]}
{"year":"2024","title":"Dr. Nahid Ebrahimi Majd","authors":["R Ferdaws - 2024"],"snippet":"The issue of web phishing attacks has been more prevalent in recent years, and phishing is one of the riskiest online crimes that can have disastrous consequences. The aim of phishing is to collect confidential information by tricking a target and …","url":["https://scholarworks.calstate.edu/downloads/s1784t388"]}
{"year":"2024","title":"DrawL: Understanding the Effects of Non-Mainstream Dialects in Prompted Image Generation","authors":["JN Williams, M FitzMorris, O Aka, S Laszlo - arXiv preprint arXiv:2405.05382, 2024"],"snippet":"… Stable Diffusion is trained in part using the LAION-5B dataset [50], which consists of text-image pairs from Common CrawlCommon Crawl includes archived data from a large variety of sources, including sites such as Reddit and a variety of blogs …","url":["https://arxiv.org/pdf/2405.05382"]}
{"year":"2024","title":"DrBenchmark: A Large Language Understanding Evaluation Benchmark for French Biomedical Domain","authors":["Y Labrak, A Bazoge, OE Khettari, M Rouvier, N Grabar… - arXiv preprint arXiv …, 2024"],"snippet":"The biomedical domain has sparked a significant interest in the field of Natural Language Processing (NLP), which has seen substantial advancements with pre-trained language models (PLMs). However, comparing these models has proven …","url":["https://arxiv.org/pdf/2402.13432"]}
{"year":"2024","title":"Dreaming Out Loud: A Self-Synthesis Approach For Training Vision-Language Models With Developmentally Plausible Data","authors":["B AlKhamissi, Y Tang, A Gökce, J Mehrer, M Schrimpf - arXiv preprint arXiv …, 2024"],"snippet":"While today's large language models exhibit impressive abilities in generating human-like text, they require massive amounts of data during training. We here take inspiration from human cognitive development to train models in limited data …","url":["https://arxiv.org/pdf/2411.00828"]}
{"year":"2024","title":"Dredge Word, Social Media, and Webgraph Networks for Unreliable Website Classification and Identification","authors":["EM Williams, P Carragher, KM Carley - arXiv preprint arXiv:2406.11423, 2024"],"snippet":"In an attempt to mimic the complex paths through which unreliable content spreads between search engines and social media, we explore the impact of incorporating both webgraph and large-scale social media contexts into website credibility …","url":["https://arxiv.org/pdf/2406.11423"]}
{"year":"2024","title":"DsDm: Model-Aware Dataset Selection with Datamodels","authors":["L Engstrom, A Feldmann, A Madry - arXiv preprint arXiv:2401.12926, 2024"],"snippet":"When selecting data for training large-scale models, standard practice is to filter for examples that match human notions of data quality. Such filtering yields qualitatively clean datapoints that intuitively should improve model behavior. However, in …","url":["https://arxiv.org/pdf/2401.12926"]}
{"year":"2024","title":"Dual Modalities of Text: Visual and Textual Generative Pre-training","authors":["Y Chai, Q Liu, J Xiao, S Wang, Y Sun, H Wu - arXiv preprint arXiv:2404.10710, 2024"],"snippet":"… Meanwhile, The C4 dataset represents a substantial refinement of the Common Crawl corpus. This dataset, derived from the extensive Common Crawl web scrape, undergoes rigorous cleaning and preprocessing to ensure the quality and relevance …","url":["https://arxiv.org/pdf/2404.10710"]}
{"year":"2024","title":"Duth at semeval 2024 task 8: Comparing classic machine learning algorithms and llm based methods for multigenerator, multidomain and multilingual machine …","authors":["T Kyriakou, I Maslaris, A Arampatzis - Proceedings of the 18th International Workshop …, 2024"],"snippet":"Text-generative models evolve rapidly nowadays. Although, they are very useful tools for a lot of people, they have also raised concerns for different reasons. This paper presents our work for SemEval2024 Task-8 on 2 out of the 3 subtasks. This …","url":["https://aclanthology.org/2024.semeval-1.156.pdf"]}
{"year":"2024","title":"Dynamic Context-Aware Representation for Semantic Alignment in Large Language Models","authors":["J Baronova, C Stevens, L Tennant, A MacPhee"],"snippet":"… The model was fine-tuned on the Common Crawl dataset, which provided a large and diverse corpus of text to ensure that the LLM could generalize well across different topics and domains. The experiment utilized an NVIDIA A100 GPU to …","url":["https://osf.io/svcn3/download"]}
{"year":"2024","title":"Dynamic decoding and dual synthetic data for automatic correction of grammar in low-resource scenario","authors":["A Musyafa, Y Gao, A Solyman, S Khan, W Cai… - PeerJ Computer Science, 2024"],"snippet":"… The data was collected from January–December 2018 using Commoncrawl snapshots in the CC-Net repository and organized into a single text document with a total data size of 36 GB. We selected the CC100 Indonesian corpus due to its open …","url":["https://peerj.com/articles/cs-2122/"]}
{"year":"2024","title":"Dynamic Ensemble Reasoning for LLM Experts","authors":["J Hu, Y Wang, S Zhang, K Zhou, G Chen, Y Hu, B Xiao… - arXiv preprint arXiv …, 2024"],"snippet":"Ensemble reasoning for the strengths of different LLM experts is critical to achieving consistent and satisfactory performance on diverse inputs across a wide range of tasks. However, existing LLM ensemble methods are either computationally …","url":["https://arxiv.org/pdf/2412.07448"]}
{"year":"2024","title":"Dynamic Few-shot Learning for Computational Social Science","authors":["R Malla, TG Coan, V Srinivasan, C Boussalis"],"snippet":"Large Language Models (LLMs) have revolutionized Natural Language Processing (NLP) and have recently demonstrated remarkable potential in social science research through their capacity to efficiently perform a wide range of text-as-data tasks …","url":["https://files.osf.io/v1/resources/nfhe8/providers/osfstorage/65c1f35335be200988a501a7?action=download&direct&version=1"]}
{"year":"2024","title":"Dynamic Neural Embedding Framework for Accurate Knowledge Representation","authors":["D Lemal, B Lindholm, A Falkenberg, I Fairbairn… - 2024"],"snippet":"… The datasets utilized for training and testing encompassed a diverse range of text corpora, including the Common Crawl dataset for … model with the integrated dynamic embedding layer was pretrained on the Common Crawl dataset, allowing …","url":["https://www.authorea.com/doi/pdf/10.22541/au.173204430.00287924"]}
{"year":"2024","title":"Dynamic Tensor Reconfiguration in Large Language Models Using Adaptive Contextual Folding","authors":["S Aturd, J Roberts, C White, S Walker"],"snippet":"… The experimental data comprised a diverse corpus of text datasets, including the Common Crawl, Wikipedia, and BookCorpus. Preprocessing steps involved tokenization, normalization, and the removal of duplicates to ensure data quality and …","url":["https://files.osf.io/v1/resources/93srw/providers/osfstorage/673ebfd2af8211b073b2874b?action=download&direct&version=1"]}
{"year":"2024","title":"Easy Problems That LLMs Get Wrong","authors":["J Huckle, S Williams - … in Information and Communication: Proceedings of the …","S Williams, J Huckle - arXiv preprint arXiv:2405.19616, 2024"],"snippet":"We introduce a comprehensive Linguistic Benchmark designed to evaluate the limitations of Large Language Models (LLMs) in domains such as logical reasoning, spatial intelligence, and linguistic understanding, among others. Through a series of …","url":["https://arxiv.org/pdf/2405.19616","https://books.google.de/books?hl=en&lr=lang_en&id=2wtMEQAAQBAJ&oi=fnd&pg=PA313&dq=commoncrawl&ots=zYl78jSmj-&sig=XRC5oowQ1oPiZ9byEZjAHRUgkgs"]}
{"year":"2024","title":"Echoes of culture: Relationships of implicit and explicit attitudes with contemporary English, historical English, and 53 non-English languages","authors":["TES Charlesworth, K Morehouse, V Rouduri… - Social Psychological and …, 2024"],"snippet":"Attitudes are intertwined with culture and language. But to what extent? Emerging perspectives in attitude research suggest that cultural representations in language are more related to implicitly measured (vs. explicitly measured) attitudes, and that …","url":["https://journals.sagepub.com/doi/abs/10.1177/19485506241256400"]}
{"year":"2024","title":"Ecosystem Graphs: Documenting the Foundation Model Supply Chain","authors":["R Bommasani, D Soylu, TI Liao, KA Creel, P Liang - … of the AAAI/ACM Conference on …, 2024"],"snippet":"Foundation models (eg GPT-4, Gemini, Llama 3) pervasively influence society, warranting greater understanding. While the models garner much attention, accurately characterizing their impact requires considering the broader …","url":["https://ojs.aaai.org/index.php/AIES/article/download/31629/33796"]}
{"year":"2024","title":"Edge-LLMs: Edge-Device Large Language Model Competition","authors":["S Liu, K Han, A Fernandez-Lopez, A Jaiswal…"],"snippet":"… The C4 dataset is a colossal, cleaned version of Common Crawl’s web crawl corpus, which is mainly intended to pre-train language models and word representations. Language models like MPT-7B and T5 are pre-trained with the C4 …","url":["https://openreview.net/pdf?id=jeCMRoIn15"]}
{"year":"2024","title":"EDGE: Enhanced Grounded GUI Understanding with Enriched Multi-Granularity Synthetic Data","authors":["X Chen, H Li, J Liang, S Jiang, D Yang - arXiv preprint arXiv:2410.19461, 2024"],"snippet":"… 24], we collect general webpages from Common Crawl1, a large-scale web crawl data repository, and drive Playwright2 to automatically annotate them. Then we format these annotations to synthesize question-answering (QA) data using various …","url":["https://arxiv.org/pdf/2410.19461"]}
{"year":"2024","title":"EEG Emotion Copilot: Pruning LLMs for Emotional EEG Interpretation with Assisted Medical Record Generation","authors":["H Chen, W Zeng, C Chen, L Cai, F Wang, L Wang… - arXiv preprint arXiv …, 2024"],"snippet":"… General LLMs are typically trained on broad datasets like Wikitext [20] and Common Crawl [21] for general knowledge and logical reasoning. For domainspecific applications, they are trained on specialized datasets, such as BioBERT [58] for …","url":["https://arxiv.org/pdf/2410.00166"]}
{"year":"2024","title":"Effects of Language-and Culture-Specific Prompting on ChatGPT","authors":["M Tuna, K Schaaff, T Schlippe"],"snippet":"… Some of these tokens come from wellknown datasets such as CommonCrawl and RefinedWeb, while others come from undisclosed sources [28], [29]. GPT-4 was first fine-tuned with data sourced from ScaleAI plus text data from OpenAI. Subsequently …","url":["https://fllm2024.fllm-conference.org/papers/1523.pdf"]}
{"year":"2024","title":"Effektivisering av fakturaklassificering enligt UNSPSC-standarden: en maskininlärningslösning","authors":["E Salam, M Norberg - 2024"],"snippet":"Procurement requirements and procurement analysis are approaches used by the Swedish National Agency for Public Procurement to ensure and maintain a sustainable societal development. The aim is to safeguard tax funds and ensure that …","url":["https://www.diva-portal.org/smash/get/diva2:1880162/FULLTEXT01.pdf"]}
{"year":"2024","title":"Efficiency Comparison of Dataset Generated by LLMs using Machine Learning Algorithms","authors":["P Pawade, M Kulkarni, S Naik, A Raut, KS Wagh - 2024 International Conference on …, 2024"],"snippet":"… • Bing Chat was trained on web text data, including Common Crawl, Wikipedia, news articles, social media posts, and other publicly available text, via a technique called denoising autoencoder (DAE). In DAE, the model is given a noisy version of a …","url":["https://ieeexplore.ieee.org/abstract/document/10497340/"]}
{"year":"2024","title":"Efficient learning in spiking neural networks","authors":["A Rast, MA Aoun, EG Elia, N Crook - Neurocomputing, 2024"],"snippet":"… Training data required is similarly massive: the CommonCrawl dataset is 242 TB in size, and hyperparameter tuning remains an expensive, search-based process that can require ∼ 1000 − 10 , 000 + sweeps. After evaluating a number of possible …","url":["https://www.sciencedirect.com/science/article/pii/S0925231224007331"]}
{"year":"2024","title":"Efficient Model-Relational Data Management: Challenges and Opportunities","authors":["V Sanca, A Ailamaki - IEEE Transactions on Knowledge and Data …, 2024"],"snippet":"As modern data pipelines continue to collect, produce, and store various data formats, extracting and combining value from traditional and context-rich sources becomes unsuitable for RDBMS. To tap into the dark data, domain experts analyze …","url":["https://ieeexplore.ieee.org/abstract/document/10488724/"]}
{"year":"2024","title":"Efficient multilingual and domain adaptation of language models under resource constraints","authors":["A Chronopoulou - 2024"],"snippet":"… It has been trained on 25 languages using monolingual Common Crawl data using a subword vocabulary of 250K tokens. It has 680M … Second, in EnDe, we use high-quality corpora for both languages (NewsCrawl), whereas Mk and Sq are …","url":["https://edoc.ub.uni-muenchen.de/34205/1/Chronopoulou_Alexandra.pdf"]}
{"year":"2024","title":"Efficient query clustering and information retrieval using Sequenced User Search Pattern Query Optimization","authors":["S Surya, P Sumitra - Multimedia Tools and Applications, 2024"],"snippet":"The rapid growth of the internet has ushered in an era of unprecedented information availability. However, this expansion has also given rise to the formidable challenge of efficiently extracting relevant data from the vast expanse of web pages …","url":["https://link.springer.com/article/10.1007/s11042-024-19463-7"]}
{"year":"2024","title":"Efficient Training and Inference: Techniques for Large Language Models Using Llama","authors":["SR Cunningham, D Archambault, A Kung"],"snippet":"… The training dataset consisted of a mixture of the Common Crawl, Wikipedia, and BooksCorpus datasets, encompassing a diverse range of linguistic structures and vocabularies. For evaluation, the GLUE benchmark suite was utilized, providing a …","url":["https://www.techrxiv.org/doi/pdf/10.36227/techrxiv.171651876.65094225"]}
{"year":"2024","title":"Efficient URL and URI Compression","authors":["F Savins, K Saric, GS Ramachandran, R Jurdak - 2024 33rd International Conference …, 2024"],"snippet":"… The dataset explored was taken from the Common Crawl project and consists of 5 million URIs in 5 sets. The URIs were found to be 99.4% URLs with the rest being other URI formats such as “Javascript:” and “Tel:”. These URIs were selected …","url":["https://ieeexplore.ieee.org/abstract/document/10637589/"]}
{"year":"2024","title":"Efficiently Identifying Watermarked Segments in Mixed-Source Texts","authors":["X Zhao, C Liao, YX Wang, L Li - arXiv preprint arXiv:2410.03600, 2024"],"snippet":"… The “Colossal Clean Crawled Corpus” (C4) dataset is a collection of English-language text sourced from the public Common Crawl web scrape, a rich source for unwatermarked human-written text. We use random samples from the news-like …","url":["https://arxiv.org/pdf/2410.03600"]}
{"year":"2024","title":"Efficiently Learning at Test-Time: Active Fine-Tuning of LLMs","authors":["J Hübotter, S Bongni, I Hakimi, A Krause - arXiv preprint arXiv:2410.08020, 2024"],"snippet":"Recent efforts in fine-tuning language models often rely on automatic data selection, commonly using Nearest Neighbors retrieval from large datasets. However, we theoretically show that this approach tends to select redundant data, limiting its …","url":["https://arxiv.org/pdf/2410.08020"]}
{"year":"2024","title":"Eir: Thai Medical Large Language Models","authors":["Y Thiprak, R Ngodngamthaweesuk… - arXiv preprint arXiv …, 2024"],"snippet":"We present Eir Thai Medical LLM, a large language model with 8 billion parameters, specifically designed to enhance the accuracy of handling medical tasks in the Thai language. This model focuses on providing clear and easy-to-understand answers …","url":["https://arxiv.org/pdf/2409.08523"]}
{"year":"2024","title":"Eliciting Big Five Personality Traits in Large Language Models: A Textual Analysis with Classifier-Driven Approach","authors":["A Hilliard, C Munoz, Z Wu, AS Koshiyama - arXiv preprint arXiv:2402.08341, 2024"],"snippet":"… GPT-3 followed, with 175 billion parameters and training on datasets like Common Crawl [15]. GPT-3.5 Turbo was introduced to enhance real-time performance, and the latest, GPT-4, boasts 1.76 trillion parameters and capabilities …","url":["https://arxiv.org/pdf/2402.08341"]}
{"year":"2024","title":"EMBA: Entity Matching using Multi-Task Learning of BERT with Attention-over-Attention","authors":["J Zhang, H Sun, JC Ho - 2024"],"snippet":"… The WDC Product Data Corpus for Large-scale Product Matching [34], was built by extracting product offers from Common Crawl. The WDC datasets serve as a popular benchmark and have been used for evaluation in DITTO, JointBERT, and …","url":["https://openproceedings.org/2024/conf/edbt/paper-76.pdf"]}
{"year":"2024","title":"Embedding Geometries of Contrastive Language-Image Pre-Training","authors":["JCC Chou, N Alam - arXiv preprint arXiv:2409.13079, 2024"],"snippet":"… Variance of the dataset: That is, if we construct a new version of DataComp datasets with newer Common Crawl or new version of RedCaps with newer reddit images, the results may change again. 3. Difference in numerical smoothing …","url":["https://arxiv.org/pdf/2409.13079"]}
{"year":"2024","title":"Embedding-based Query Spelling Correction","authors":["I Zelch, G Lahmann, M Hagen - 2024"],"snippet":"For many retrieval systems, correcting spelling errors in the queries that searchers submit is an essential step of query understanding. Inspired by a blog post on spelling correction from 2018, we implement and analyze a simple embedding-based …","url":["https://downloads.webis.de/publications/papers/zelch_2024b.pdf"]}
{"year":"2024","title":"Emergence of Abstractions: Concept Encoding and Decoding Mechanism for In-Context Learning in Transformers","authors":["S Han, J Song, J Gore, P Agrawal - arXiv preprint arXiv:2412.12276, 2024"],"snippet":"Humans distill complex experiences into fundamental abstractions that enable rapid learning and adaptation. Similarly, autoregressive transformers exhibit adaptive learning through in-context learning (ICL), which begs the question of how. In this …","url":["https://arxiv.org/pdf/2412.12276"]}
{"year":"2024","title":"Emergent Abilities in Reduced-Scale Generative Language Models","authors":["S Muckatira, V Deshpande, V Lialin, A Rumshisky - arXiv preprint arXiv:2404.02204, 2024"],"snippet":"Large language models can solve new tasks without task-specific fine-tuning. This ability, also known as in-context learning (ICL), is considered an emergent ability and is primarily seen in large language models with billions of parameters. This …","url":["https://arxiv.org/html/2404.02204v1"]}
{"year":"2024","title":"Emergent Lexical Synthesis Through Contextual Feedback Mechanisms in Large Language Models","authors":["V Zakiev, E Cumberledge, C Ravenscroft…"],"snippet":"Adaptive mechanisms capable of refining intermediate latent states during text generation are essential for addressing limitations in current model architectures, particularly with respect to contextual drift, linguistic coherence, and output diversity …","url":["https://osf.io/t8mj9/download"]}
{"year":"2024","title":"Emerging AI Tools for Education and Research: Perspective and Policies for IISc","authors":["GJ OC, AK CSA, V Kumar, YN CSA…"],"snippet":"The Director, IISc, constituted a committee on August 21, 2023 with the following mandate:(a) Explore the challenges and benefits of emerging AI tools in the context of academic teaching and learning,(b) provide guidance and recommendations to …","url":["https://iisc.ac.in/wp-content/uploads/2024/03/Report-of-Committee-on-AI-Tools-for-Education-and-Research.pdf"]}
{"year":"2024","title":"Emerging Roots: Investigating Early Access to Meaning in Maltese Auditory Word Recognition","authors":["J Nieder, R van de Vijver, A Ussishkin - Cognitive Science, 2024"],"snippet":"In Semitic languages, the consonantal root is central to morphology, linking form and meaning. While psycholinguistic studies highlight its importance in language processing, the role of meaning in early lexical access and its representation remain …","url":["https://onlinelibrary.wiley.com/doi/pdf/10.1111/cogs.70004"]}
{"year":"2024","title":"EMMA-500: Enhancing Massively Multilingual Adaptation of Large Language Models","authors":["S Ji, Z Li, I Paul, J Paavola, P Lin, P Chen, D O'Brien… - arXiv preprint arXiv …, 2024"],"snippet":"In this work, we introduce EMMA-500, a large-scale multilingual language model continue-trained on texts across 546 languages designed for enhanced multilingual performance, focusing on improving language coverage for low-resource languages …","url":["https://arxiv.org/pdf/2409.17892"]}
{"year":"2024","title":"EMMeTT: Efficient Multimodal Machine Translation Training","authors":["P Żelasko, Z Chen, M Wang, D Galvez, O Hrinchuk… - arXiv preprint arXiv …, 2024"],"snippet":"A rising interest in the modality extension of foundation language models warrants discussion on the most effective, and efficient, multimodal training approach. This work focuses on neural machine translation (NMT) and proposes a joint multimodal …","url":["https://arxiv.org/pdf/2409.13523"]}
{"year":"2024","title":"Emotion Analysis in Narrative Economics","authors":["A Kremm - 2024"],"snippet":"The purpose of this quantitative cross-sectional design using a structural equation model was to determine if emotions mediate the viral spread of narratives with potentially far-reaching economic and political consequences. This dissertation …","url":["https://search.proquest.com/openview/1b97a8fa22e57007ebb8ca78200c6bf6/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
{"year":"2024","title":"Emotional significance in Cross-Cultural Semantic Crossmodal Correspondences","authors":["J Alvarado - Proceedings of the Annual Meeting of the Cognitive …, 2024"],"snippet":"Crossmodal correspondences are associations between perceptual features from different senses that aid in crossmodal binding. The semantic coding of these correspondences is expected to capture and mediate the emergence of perceptual …","url":["https://escholarship.org/content/qt2sc9n8q9/qt2sc9n8q9.pdf"]}
{"year":"2024","title":"Employing Siamese MaLSTM Model and ELMO Word Embedding for Quora Duplicate Questions Detection","authors":["A Altamimi, M Umer, D Hanif, S Alsubai, TH Kim… - IEEE Access, 2024"],"snippet":"… 3) FastText Subword FastText Subword comprises a collection of 2 million word vectors trained on the Common Crawl dataset, which consists of a massive 600 billion tokens. In contrast to traditional word embeddings, sub-word embeddings …","url":["https://ieeexplore.ieee.org/iel7/6287639/6514899/10440276.pdf"]}
{"year":"2024","title":"Empowering geoportals HCI with task-oriented chatbots through NLP and deep transfer learning","authors":["MH Vahidnia - Big Earth Data, 2024"],"snippet":"In the past ten years, chatbot development has matured to become one of the most well-distinguished outcomes of artificial intelligence. Despite some criticism, Bing AI, ChatGPT and other natural language processing (NLP) products of similar nature …","url":["https://www.tandfonline.com/doi/full/10.1080/20964471.2024.2403166"]}
{"year":"2024","title":"Empowering hate speech detection: leveraging linguistic richness and deep learning","authors":["IGBJ Abasan, EB Setiawan - Bulletin of Electrical Engineering and Informatics, 2024"],"snippet":"… What they don’t realize is the use of pre-trained models, namely CommonCrawl and Wiki, in extraction using FastText or GloVe. The pre-trained model used is not specific for hate speech detection and, of course, consists of many languages, and …","url":["https://www.beei.org/index.php/EEI/article/download/6938/3660"]}
{"year":"2024","title":"Empowering Humans with Machines: From Explanations to Teaching","authors":["H Liu - 2024"],"snippet":"… This dataset contains hundreds of thousands of online biographies from the Common Crawl corpus. The task is to predict a person’s profession given a biography. The original dataset consists of 29 professions, and we narrow it down to …","url":["https://knowledge.uchicago.edu/record/12649/files/Han_Liu_Dissertation_To_Submit.pdf"]}
{"year":"2024","title":"Empowering knowledge through AI: open scholarship proactively supporting well trained generative AI","authors":["B Montague-Hellen - Insights, 2024"],"snippet":"… The bulk of the content consists of the common crawl dataset, a free-to-use dataset consisting of over 250 billion webpages from the last 17 … Both the common crawl dataset and the WebText2 dataset rely heavily on well-linked and well-described …","url":["https://insights.uksg.org/en/articles/10.1629/uksg.649"]}
{"year":"2024","title":"Empowering Multi-step Reasoning across Languages via Program-Aided Language Models","authors":["L Ranaldi, G Pucci, B Haddow, A Birch - Proceedings of the 2024 Conference on …, 2024"],"snippet":"In-context learning methods are popular inference strategies where Large Language Models (LLMs) are elicited to solve a task using provided demonstrations without parameter updates. Among these approaches are the reasoning methods …","url":["https://aclanthology.org/2024.emnlp-main.678.pdf"]}
{"year":"2024","title":"Enabling action crossmodality for a pretrained large language model","authors":["A Caesar, O Özdemir, C Weber, S Wermter - Natural Language Processing Journal, 2024"],"snippet":"Natural language processing and vision tasks have seen large improvements recently through the rise of Transformer architectures. The high performing large language models (LLMs) benefit from large textual datasets that are numerously …","url":["https://www.sciencedirect.com/science/article/pii/S2949719124000207"]}
{"year":"2024","title":"Enabling High-Sparsity Foundational Llama Models with Efficient Pretraining and Deployment","authors":["A Agarwalla, A Gupta, A Marques, S Pandit, M Goin… - arXiv preprint arXiv …, 2024"],"snippet":"Large language models (LLMs) have revolutionized Natural Language Processing (NLP), but their size creates computational bottlenecks. We introduce a novel approach to create accurate, sparse foundational versions of performant LLMs that achieve full …","url":["https://arxiv.org/pdf/2405.03594"]}
{"year":"2024","title":"Enabling Parallelism Hot Switching for Efficient Training of Large Language Models","authors":["H Ge, F Fu, H Li, X Wang, S Lin, Y Wang, X Nie… - Proceedings of the ACM …, 2024"],"snippet":"… We consider two datasets in our experiments, ie, CommonCrawl and GitHub, and the distributions of sequence lengths are shown in Figure 3. Protocols. For each pair of model and dataset, we vary the context length (s) from 4K to 32K to assess the …","url":["https://dl.acm.org/doi/abs/10.1145/3694715.3695969"]}
{"year":"2024","title":"Enabling self-identification in intelligent agent: insights from computational psychoanalysis","authors":["L Li, C Li - arXiv preprint arXiv:2403.07664, 2024"],"snippet":"Building upon prior framework of computational Lacanian psychoanalysis with the theory of active inference, this paper aims to further explore the concept of self-identification and its potential applications. Beginning with two classic paradigms in psychology …","url":["https://arxiv.org/pdf/2403.07664"]}
{"year":"2024","title":"End to End Urdu Abstractive Text Summarization with Dataset and Improvement in Evaluation Metric","authors":["H Raza, W Shahzad - IEEE Access, 2024"],"snippet":"Urdu, being a common language in South Asia, has not received significant attention in terms of language processing compared to more advanced languages. In the field of Natural Language Processing (NLP), the task of text summarization …","url":["https://ieeexplore.ieee.org/iel7/6287639/6514899/10472483.pdf"]}
{"year":"2024","title":"Energy and AI","authors":["J Göpfert, JM Weinand, P Kuckertz, D Stolten"],"snippet":"… Because models can be trained on this objective in a self-supervised setting, large unlabeled corpora (such as Wikipedia, book corpora, and Common Crawl data) can be used for training. The computational advantages of the transformer …","url":["https://publications.rwth-aachen.de/record/989122/files/989122.pdf"]}
{"year":"2024","title":"English-language abstract text summarization using the T5 model","authors":["RD Darshan, I Surya, G Malarselvi - AIP Conference Proceedings, 2024"],"snippet":"… The Common Crawl public web scrape is the source for the 750GB of English-language text that makes up the C4 dataset. The news summary dataset that we've used in this instance has 4515 samples and includes the following information: Headlines, Short …","url":["https://pubs.aip.org/aip/acp/article-abstract/3075/1/020028/3304969"]}
{"year":"2024","title":"Enhanced Blood Cell Classification Performance and Conditional Image Generation With Transformer Based Models","authors":["TS Patel - 2024"],"snippet":"Blood cancer accounted for over 1.24 million cases globally in 2020 (6.6% of all cancers) and has imposed significant financial and health burdens. The World Health Organization (WHO) emphasizes the need for improved detection and …","url":["https://search.proquest.com/openview/336303d74942772d64ff2b54fa50b9a7/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
{"year":"2024","title":"EnhancedBERT: A Feature-rich Ensemble Model for Arabic Word Sense Disambiguation with Statistical Analysis and Optimized Data Collection","authors":["S Kaddoura, R Nassar - Journal of King Saud University-Computer and …, 2024"],"snippet":"Accurate assignment of meaning to a word based on its context, known as Word Sense Disambiguation (WSD), remains challenging across languages. Extensive research aims to develop automated methods for determining word senses in …","url":["https://www.sciencedirect.com/science/article/pii/S1319157823004652"]}
{"year":"2024","title":"Enhancing 3D Asset Retrieval with Semantic Search","authors":["SA FatemiJahromi - 2024"],"snippet":"Semantic search goes beyond exact keyword matching and instead focuses on the comprehension of search queries' purpose and the surrounding context to deliver relevant search results. In this work, we focus on integrating hybrid search, which …","url":["https://aaltodoc.aalto.fi/bitstreams/76d339fd-de51-4bb0-8a8c-e43d799b7023/download"]}
{"year":"2024","title":"Enhancing AI Tutoring in Robotics Education: Evaluating the Effect of Retrieval-Augmented Generation and Fine-Tuning on Large Language Models","authors":["S Kahl, F Löffler, M Maciol, F Ridder, M Schmitz… - 2024"],"snippet":"… The majority of data is gained from CommonCrawl with about 850 billion tokens. CommonCrawl is a free and open of data gathered by web crawls.In addition, the corpus is based on data from C4 (about 190 billion tokens), Github (about 100 billion …","url":["https://www.uni-muenster.de/imperia/md/content/angewandteinformatik/aktivitaeten/publikationen/enhancing_ai_tutoring_in_robotics_education_-_2024.pdf"]}
{"year":"2024","title":"Enhancing Assamese NLP Capabilities: Introducing a Centralized Dataset Repository","authors":["S Tamang, DJ Bora - arXiv preprint arXiv:2410.11291, 2024"],"snippet":"This paper introduces a centralized, open-source dataset repository designed to advance NLP and NMT for Assamese, a low-resource language. The repository supports various tasks like sentiment analysis, named entity recognition, and …","url":["https://arxiv.org/pdf/2410.11291"]}
{"year":"2024","title":"ENHANCING AUTOMATIC INVOICE CODING PERFORMANCE WITH UNSTRUCTURED DATA","authors":["T Eerola - 2024"],"snippet":"… The published word vectors are 300 dimensional and trained on the internet data from Common Crawl3. The pretrained word vectors can be further fine-tuned using the provided code and datasets more similar to the final usage scenario to increase …","url":["https://trepo.tuni.fi/bitstream/handle/10024/155981/EerolaTeemu.pdf?sequence=2"]}
{"year":"2024","title":"Enhancing Automatic Keyphrase Labelling with Text-to-Text Transfer Transformer (T5) Architecture: A Framework for Keyphrase Generation and Filtering","authors":["J Gabín, ME Ares, J Parapar - arXiv preprint arXiv:2409.16760, 2024"],"snippet":"Automatic keyphrase labelling stands for the ability of models to retrieve words or short phrases that adequately describe documents' content. Previous work has put much effort into exploring extractive techniques to address this task; however, these …","url":["https://arxiv.org/pdf/2409.16760"]}
{"year":"2024","title":"Enhancing Bias Assessment for Complex Term Groups in Language Embedding Models: Quantitative Comparison of Methods","authors":["M Gray, M Milanova, L Wu - JMIR Medical Informatics, 2024"],"snippet":"… 300d” from the Stanford NLP Group [15], which was trained on 840 billion tokens from Common Crawl data, has a vocab size of 2.2 million, and generates 300-dimension vectors. Moreover, other input embedding methods, including those of BERT [12], Sci-BERT …","url":["https://medinform.jmir.org/2024/1/e60272"]}
{"year":"2024","title":"Enhancing Computer Programming Education with LLMs: A Study on Effective Prompt Engineering for Python Code Generation","authors":["T Wang, N Zhou, Z Chen - arXiv preprint arXiv:2407.05437, 2024"],"snippet":"Large language models (LLMs) and prompt engineering hold significant potential for advancing computer programming education through personalized instruction. This paper explores this potential by investigating three critical research questions: the …","url":["https://arxiv.org/pdf/2407.05437"]}
{"year":"2024","title":"Enhancing Cyber Security Enhancement Through Generative AI","authors":["O Krishnamurthy"],"snippet":"… GPT-1: Released in 2018, GPT-1 was trained on the Common Crawl and BookCorpus datasets. It demonstrated proficient language comprehension but limited conversational coherence and retention of context. GPT-2: Trained on …","url":["https://ijuse.in/admin1/upload/06%20Oku%20Krishnamurthy%2001155.pdf"]}
{"year":"2024","title":"Enhancing Cybersecurity: A Review and Comparative Analysis of Convolutional Neural Network Approaches for Detecting URL-Based Phishing Attacks","authors":["M Nanda, M Saraswat, PK Sharma - e-Prime-Advances in Electrical Engineering …, 2024"],"snippet":"Phishing attempts to mimic the official websites of businesses, including banks, e-commerce, government offices, and financial institutions. Phishing websites aim to collect and retrieve sensitive data from users, including passwords, credit card numbers, email …","url":["https://www.sciencedirect.com/science/article/pii/S2772671124001153"]}
{"year":"2024","title":"Enhancing Ecological Knowledge Discovery Using Large Language Models","authors":["V Domazetoski"],"snippet":"Earth is home to an astonishing diversity of life forms. Among these, vascular plants stand as one of the most vital and ubiquitous groups, accounting for approximately 80% of global biomass [3]. The census of vascular plants, which presently exceeds …","url":["https://gipplab.org/wp-content/papercite-data/pdf/domazetoski2024.pdf"]}
{"year":"2024","title":"ENHANCING EDUCATIONAL CHATBOTS WITH RETRIEVAL-AUGMENTED GENERATION SYSTEMS: A STUDY ON PHYSICS AND MATHEMATICS COURSES","authors":["H Monteiro, H Mokayed - ICERI2024 Proceedings, 2024"],"snippet":"The integration of Large Language Models (LLMs) with educational tools offers significant potential to enhance student learning by providing tailored, contextually accurate responses through chatbots. This thesis investigates the implementation of …","url":["https://library.iated.org/view/MONTEIRO2024ENH"]}
{"year":"2024","title":"Enhancing English Translation Quality Assessment through Knowledge Transfer in Artificial Intelligence Context","authors":["X Zhao - 2024"],"snippet":"Abstract Machine translation technology, which employs computers to autonomously convert text between source and target languages, represents a pivotal realm within artificial intelligence and natural language processing research. This paper …","url":["https://www.researchsquare.com/article/rs-4483708/latest.pdf"]}
{"year":"2024","title":"ENHANCING JAPANESE LEXICAL NETWORKS USING LARGE LANGUAGE MODELS","authors":["D Špica, B Perak"],"snippet":"This study presents an innovative approach to crafting and enhancing Japanese lexical networks by incorporating large language models (LLMs), especially GPT-4o, utilizing data from Matsushita’s (2011) Vocabulary Database for Reading Japanese …","url":["https://www.researchgate.net/profile/Dragana-Spica/publication/384885027_ENHANCING_JAPANESE_LEXICAL_NETWORKS_USING_LARGE_LANGUAGE_MODELS_Extracting_Synonyms_and_Antonyms_with_GPT-4o/links/670c39b768e0f20a6111fd8e/ENHANCING-JAPANESE-LEXICAL-NETWORKS-USING-LARGE-LANGUAGE-MODELS-Extracting-Synonyms-and-Antonyms-with-GPT-4o.pdf"]}
{"year":"2024","title":"Enhancing knowledge graphs with microdata and LLMs: the case of Schema. org and Wikidata in touristic information","authors":["L Gonzalez-Garcia, G González-Carreño… - The Electronic Library, 2024"],"snippet":"… We have used the Common Crawl (CC) corpus of crawled Web pages to extract metadata published in the wild, and then used a mapping of Schema.org annotations to Wikidata to get estimates of the added value (in terms of additional …","url":["https://www.emerald.com/insight/content/doi/10.1108/EL-06-2023-0160/full/html"]}
{"year":"2024","title":"Enhancing Large Language Models for Structured Data Extraction","authors":["S Meijboom - 2024"],"snippet":"This thesis examines the application of large language models for structured data extraction using microdata-annotated webpages from the Web Data Commons (WDC). It compares the performance of models trained on WDC data with those trained on …","url":["https://www.cs.ru.nl/bachelors-theses/2024/Sven_Meijboom___1054374___Enhancing_Large_Language_Models_for_Structured_Data_Extraction.pdf"]}
{"year":"2024","title":"Enhancing Large Language Models with Stochastic Multi-Level Embedding Fusion: An Experimental Approach on Open-Source LLM","authors":["H Raines, E Ferreira, L Fitzwilliam, B Everson… - Authorea Preprints, 2024"],"snippet":"… The experiment utilized the Common Crawl dataset for training, given its extensive coverage of diverse web-based text, which offered a wide variety of linguistic structures and semantic contexts. The dataset was particularly valuable for …","url":["https://www.authorea.com/doi/pdf/10.22541/au.172893952.22145551"]}
{"year":"2024","title":"Enhancing misogyny detection in bilingual texts using explainable AI and multilingual fine-tuned transformers","authors":["E Hashmi, SY Yayilgan, MM Yamin, M Ullah - Complex & Intelligent Systems, 2025"],"snippet":"… It boasts a vast dictionary containing 2 million words from the Common Crawl database, with each word represented in a 300-dimensional vector space, totaling an impressive 600 billion word vectors. In our research, we have employed both the …","url":["https://link.springer.com/article/10.1007/s40747-024-01655-1"]}
{"year":"2024","title":"Enhancing Misogyny Detection in Bilingual Texts Using FastText and Explainable AI","authors":["E Hashmi, MM Yamin, S Imran, SY Yayilgan, M Ullah - 2024 International Conference …, 2024"],"snippet":"… It features an extensive dictionary with 2 million words drawn from the Common Crawl database. Every word is depicted in a 300-dimensional vector space, amassing an enormous total of 600 billion word vectors. 1) Unsupervised FastText …","url":["https://ieeexplore.ieee.org/abstract/document/10581058/"]}
{"year":"2024","title":"Enhancing Multilingual Hate Speech Detection: From Language-Specific Insights to Cross-Linguistic Integration","authors":["E Hashmi, SY Yayilgan, IA Hameed, MM Yamin… - IEEE Access, 2024"],"snippet":"… It features a vast vocabulary of 2 million words from the Common Crawl dataset, mapping each to a 300-dimensional vector space. What … This model was built using Common Crawl and Wikipedia using FastText’s unsupervised learning …","url":["https://ieeexplore.ieee.org/iel8/6287639/6514899/10662891.pdf"]}
{"year":"2024","title":"Enhancing News Articles: Automatic SEO Linked Data Injection for Semantic Web Integration","authors":["H Salem, H Salloum, K Sabbagh, M Mazzara - 2024"],"snippet":"This paper presents a novel solution aimed at enhancing news web pages for seamless integration into the Semantic Web. By utilizing advanced pattern mining techniques alongside OpenAI’s GPT-3, we rewrite news articles to improve their …","url":["https://www.preprints.org/manuscript/202410.2489/download/final_file"]}
{"year":"2024","title":"Enhancing Parameter Efficiency in Model Inference Using an Ultralight Inter-Transformer Linear Structure","authors":["H Shi, T Sakai - IEEE Access, 2024"],"snippet":"… It was constructed from the Chuweb21 generated based on the April 2021 block of the Common Crawl dataset. The WWW-4 dataset comprises 50 queries. Robust04 dataset is also an English web corpus generated from TREC disks 4 and 5, and …","url":["https://ieeexplore.ieee.org/iel7/6287639/10380310/10474022.pdf"]}
{"year":"2024","title":"Enhancing Phishing Detection, Leveraging Deep Learning Techniques","authors":["A Ullah, RA Shah, SA Nawaz, N Ahmad, MH Malik - Journal of Computing & …, 2024"],"snippet":"… To achieve this, we utilized the Common Crawl Corpus, which aggregates extensive data collected over seven years. This corpus comprises raw web page data, metadata, and textual content. Legitimate domains with substantial backlink …","url":["https://jcbi.org/index.php/Main/article/download/340/252"]}
{"year":"2024","title":"Enhancing pre-trained models for text summarization: a multi-objective genetic algorithm optimization approach","authors":["GB Mohan, RP Kumar, R Elakkiya - Multimedia Tools and Applications, 2024"],"snippet":"… A significant aspect of their work was the introduction of C4, a substantial text corpus derived from Common Crawl, utilized in several of their model variations. During its pre-training phase, T5 employed an intriguing technique of masking …","url":["https://link.springer.com/article/10.1007/s11042-024-20374-w"]}
{"year":"2024","title":"Enhancing Product Design through AI-Driven Sentiment Analysis of Amazon Reviews Using BERT","authors":["MK Shaik Vadla, MA Suresh, VK Viswanathan - Algorithms, 2024"],"snippet":"Understanding customer emotions and preferences is paramount for success in the dynamic product design landscape. This paper presents a study to develop a prediction pipeline to detect the aspect and perform sentiment analysis on review …","url":["https://www.mdpi.com/1999-4893/17/2/59"]}
{"year":"2024","title":"Enhancing Sentiment Analysis Accuracy in Borobudur Temple Visitor Reviews through Semi-Supervised Learning and SMOTE Upsampling","authors":["C Agustina, P Purwanto, F Farikhin - Journal of Advances in Information Technology, 2024"],"snippet":"The level of visitor satisfaction with tourist destinations can be known from reviews on social media. One method used is to carry out sentiment analysis on comments given by visitors on social media or related websites. This study was envisioned as a …","url":["https://www.jait.us/uploadfile/2024/JAIT-V15N4-492.pdf"]}
{"year":"2024","title":"Enhancing Sentiment Analysis on Social Media Data with Advanced Deep Learning Techniques.","authors":["HH Nguyen - International Journal of Advanced Computer Science & …, 2024"],"snippet":"This paper introduces a comprehensive methodology for conducting sentiment analysis on social media using advanced deep learning techniques to address the unique challenges of this domain. As digital platforms play an increasingly pivotal …","url":["https://search.ebscohost.com/login.aspx?direct=true&profile=ehost&scope=site&authtype=crawler&jrnl=2158107X&AN=177684405&h=gXTVgMzshbdYbIB8QB5iY2khYefExufWIzwbWX54fXIt%2Bfzrlh8r7t0tSXHbiXxI0typ97LA8y%2FqCMzmDhr%2FjA%3D%3D&crl=c"]}
{"year":"2024","title":"Enhancing Text Summarization in a Limited Data and Long Sample Setting","authors":["V Shevchuk - 2024"],"snippet":"This thesis addresses the challenges of automatic text summarization in a limited amount of data and a significantly large sample size setting. The study introduces a novel dataset of Ukrainian legislative documents professionally translated into …","url":["https://www.researchsquare.com/article/rs-4535506/latest.pdf"]}
{"year":"2024","title":"Enhancing Text Summarization in a Limited Data and Long Sample","authors":["V Shevchuk"],"snippet":"In our rapidly digitizing world, the volume of online information is growing at an unprecedented rate. Legal systems worldwide do not lag behind and generate massive amounts of documents daily. Lawyers are tasked with navigating an ever-growing …","url":["https://www.vdu.lt/cris/bitstreams/9fb482d3-fcf0-4790-9dae-dc634419c317/download"]}
{"year":"2024","title":"Enhancing Vision-Language Pre-training with Rich Supervisions","authors":["Y Gao, K Shi, P Zhu, E Belval, O Nuriel, S Appalaraju… - arXiv preprint arXiv …, 2024"],"snippet":"… This is expected as our data collected from Common Crawl has different distribution against the original Pix2struct data due to the data size (2M vs. 80M) and potentially different website filtering strategies. Specifically, we filter out website …","url":["https://arxiv.org/pdf/2403.03346"]}
{"year":"2024","title":"Enriching Interactive Explanations with Fuzzy Temporal Constraint Networks","authors":["M Canabal-Juanatey, JM Alonso-Moral, A Catala… - International Journal of …, 2024"],"snippet":"… such as BERT [2] (Bidirectional Encoder Representations from Transformers), GPT [26] (Generative Pre-trained Transformer) and their successors (ALBERT [4], RoBERTa [3], BART [7], GPT-3 [5] or GPT-4 [27]), which were trained with huge …","url":["https://www.sciencedirect.com/science/article/pii/S0888613X2400015X"]}
{"year":"2024","title":"Enriching satellite image annotations of forests with keyphrases from a specialized corpus","authors":["N Neptune, J Mothe - Multimedia Tools and Applications, 2024"],"snippet":"… We test fastText embeddings trained on Common Crawl Footnote 4 and Wikipedia Footnote 5 with dimension 300 and a context size of 5 … These fastText models were pre-trained on Common Crawl and Wikipedia. None of the models was …","url":["https://link.springer.com/article/10.1007/s11042-024-20015-2"]}
{"year":"2024","title":"Ensemble based high performance deep learning models for fake news detection","authors":["M E. Almandouh, MF Alrahmawy, M Eisa, M Elhoseny… - Scientific Reports, 2024"],"snippet":"… It boasts an extensive lexicon of 2 million words obtained from Common Crawl. Each word is embedded in a 300-dimensional vector space, resulting in a comprehensive library of 600-billion-word vectors. FastText architecture, as seen in Fig. …","url":["https://www.nature.com/articles/s41598-024-76286-0"]}
{"year":"2024","title":"Entrant: A large financial dataset for table understanding","authors":["E Zavitsanos, D Mavroeidis, E Spyropoulou… - Scientific Data, 2024"],"snippet":"Tabular data is a way to structure, organize, and present information conveniently and effectively. Real-world tables present data in two dimensions by arranging cells in matrices that summarize information and facilitate side-by-side comparisons …","url":["https://www.nature.com/articles/s41597-024-03605-5"]}
{"year":"2024","title":"Entropy and type-token ratio in gigaword corpora","authors":["P Rosillo-Rodes, MS Miguel, D Sanchez - arXiv preprint arXiv:2411.10227, 2024"],"snippet":"Lexical diversity measures the vocabulary variation in texts. While its utility is evident for analyses in language change and applied linguistics, it is not yet clear how to operationalize this concept in a unique way. We here investigate entropy and text-token …","url":["https://arxiv.org/pdf/2411.10227"]}
{"year":"2024","title":"EpilepsyLLM: Domain-Specific Large Language Model Fine-tuned with Epilepsy Medical Knowledge","authors":["X Zhao, Q Zhao, T Tanaka - arXiv preprint arXiv:2401.05908, 2024"],"snippet":"With large training datasets and massive amounts of computing sources, large language models (LLMs) achieve remarkable performance in comprehensive and generative ability. Based on those powerful LLMs, the model fine-tuned with domain-specific …","url":["https://arxiv.org/pdf/2401.05908"]}
{"year":"2024","title":"Error Patterns in Vision Transformers: A Focused Study on InternVL's Real-World Performance","authors":["J Yang"],"snippet":"This study focuses on the errors in Vision Transformers, particularly examining the realworld performance of InternVL, an opensource multimodal model designed to rival commercial systems. The primary tasks explored include image captioning and …","url":["https://www.researchgate.net/profile/Jason-Yang-49/publication/381650191_Error_Patterns_in_Vision_Transformers_A_Focused_Study_on_InternVL's_Real-World_Performance/links/6678694a8408575b838483a3/Error-Patterns-in-Vision-Transformers-A-Focused-Study-on-InternVLs-Real-World-Performance.pdf"]}
{"year":"2024","title":"Establishing Global AI Accountability: Training Data Transparency, Copyright, and Misinformation","authors":["AS George, T Baskar, D Pandey - 2024"],"snippet":"As artificial intelligence (AI) technologies continue advancing at a rapid pace, the systems' growing capabilities as well as their expanding integration into vital social functions are raising complex questions around trust and accountability. AI models …","url":["https://www.researchgate.net/profile/A-Shaji-George/publication/381429227_Establishing_Global_AI_Accountability_Training_Data_Transparency_Copyright_and_Misinformation/links/666c7a1785a4ee7261c14cdb/Establishing-Global-AI-Accountability-Training-Data-Transparency-Copyright-and-Misinformation.pdf"]}
{"year":"2024","title":"Establishing the importance of co-creation and self-efficacy in creative collaboration with artificial intelligence","authors":["J McGuire, D De Cremer, T Van de Cruys - Scientific Reports, 2024"],"snippet":"The emergence of generative AI technologies has led to an increasing number of people collaborating with AI to produce creative works. Across two experimental studies, in which we carefully designed and programmed state-of-the-art human–AI …","url":["https://www.nature.com/articles/s41598-024-69423-2"]}
{"year":"2024","title":"Ethical aspects of ChatGPT: An approach to discuss and evaluate key requirements from different ethical perspectives","authors":["M Steen, J Greeff, M Boer, C Veenman - AI and Ethics, 2024"],"snippet":"… Many LLMs have been trained with data from Common Crawl, Footnote 9 which contains inaccuracies, errors, and bias. Another concern is whether people can access ChatGPT and, for example, change parameters or delete data, so that the …","url":["https://link.springer.com/article/10.1007/s43681-024-00571-x"]}
{"year":"2024","title":"Ethical Considerations for Generative AI in Social Science Research","authors":["BA Brown, KL Heitner - Generative AI and Implications for Ethics, Security, and …, 2024"],"snippet":"Social science research embodies the inquiry into people as individuals and their interpersonal interactions with each other in communities and varied societies, with due consideration for their natural, technological, and constructed environments …","url":["https://www.igi-global.com/chapter/ethical-considerations-for-generative-ai-in-social-science-research/354606"]}
{"year":"2024","title":"Ethical recommendations for Artificial Intelligence technology in the Geological Sciences-with a focus on Language Models","authors":["PH Cleverley - Journal of Geoethics and Social Geosciences, 2024"],"snippet":"… Common Crawl, an open and up to date dataset of large swaths of the Internet has been freely available for several years and is used by most foundation LLMs and also some domain specific ones3. Over recent years, the amount of freely …","url":["https://www.journalofgeoethics.eu/index.php/jgsg/article/download/63/22"]}
{"year":"2024","title":"Ethics of AI in the Teaching of English","authors":["A Piotrowski"],"snippet":"New technologies have always impacted literacy, and artificial intelligence (AI) is no exception (Tyner, 1998). English teachers find themselves having to consider how AI may impact how they teach. NCTE’s Beliefs for Integrating Technology Into the …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=HtIDEQAAQBAJ&oi=fnd&pg=PA221&dq=commoncrawl&ots=Wd6CuXLoH8&sig=-k9bfBVB4zHhmTOBXH6OEGq0Xws"]}
{"year":"2024","title":"EthioLLM: Multilingual Large Language Models for Ethiopian Languages with Task Evaluation","authors":["AL Tonja, IA Azime, TD Belay, MG Yigezu… - arXiv preprint arXiv …, 2024"],"snippet":"Large language models (LLMs) have gained popularity recently due to their outstanding performance in various downstream Natural Language Processing (NLP) tasks. However, low-resource languages are still lagging behind current state-of-the-art …","url":["https://arxiv.org/pdf/2403.13737"]}
{"year":"2024","title":"Euphemism in AI Discourse as Colonial Harm & Effect: Learnings from Subaltern Puerto Rico","authors":["J Oquendo - 2024"],"snippet":"Through three integrated studies, this dissertation explores complex human-AI interactions by comparing the perceptions of two groups of US citizens: subaltern Puerto Ricans and stateside Americans’ interactions with ChatGPT. This corpus-assisted …","url":["https://repository.lsu.edu/cgi/viewcontent.cgi?article=7773&context=gradschool_dissertations"]}
{"year":"2024","title":"Evading VBA Malware Classification using Model Extraction Attacks and Stochastic Search Methods","authors":["B Fehrman, F Akowuah, R Hoover - 2024 Cyber Awareness and Research …, 2024"],"snippet":"Antivirus (AV) software that relies on learning-based methods is potentially vulnerable to adversarial attacks from threat actors. Threat actors can utilize model-extraction attacks against AV software to create a surrogate model. Malware samples can be …","url":["https://ieeexplore.ieee.org/abstract/document/10778829/"]}
{"year":"2024","title":"EvalQuiz: self-assessment generated through language transformer models","authors":["J Kieslinger - 2023"],"snippet":"This thesis explores the constraints of self-assessment creation in higher education, focusing on the lack of tools, standardization, and time. We conduct didactic field expert interviews to investigate how teaching evolves towards learning management …","url":["http://elib.uni-stuttgart.de/bitstream/11682/13953/1/Julian_Kieslinger_Bachelorarbeit_Abgabe_offiziell.pdf"]}
{"year":"2024","title":"Evaluating and Adapting Large Language Models to Represent Folktales in Low-Resource Languages","authors":["JA Meaney, B Alex, W Lamb - arXiv preprint arXiv:2411.05593, 2024"],"snippet":"Folktales are a rich resource of knowledge about the society and culture of a civilisation. Digital folklore research aims to use automated techniques to better understand these folktales, and it relies on abstract representations of the textual …","url":["https://arxiv.org/pdf/2411.05593"]}
{"year":"2024","title":"Evaluating and Aligning CodeLLMs on Human Preference","authors":["J Yang, J Yang, K Jin, Y Miao, L Zhang, L Yang, Z Cui… - arXiv preprint arXiv …, 2024"],"snippet":"… Recall from Common Crawl. A trained fasttext is used to distinguish the code-related text and other common raw text, which is used to recall and clean potential code data and filter out low-quality content using weak model-based classifiers and …","url":["https://arxiv.org/pdf/2412.05210"]}
{"year":"2024","title":"Evaluating and improving lexical language understanding in neural machine translation","authors":["D Emelin - 2024"],"snippet":"Lexical understanding is an inalienable component of the translation process. In order to correctly map the meaning of a linguistic unit to the appropriate target language expression, the meaning of its constituent words has first to be identified …","url":["https://era.ed.ac.uk/bitstream/handle/1842/41561/EmelinD_2024.pdf?sequence=1"]}
{"year":"2024","title":"Evaluating and Improving the Reasoning Abilities of Language Models","authors":["C Helwe - 2024"],"snippet":"This thesis focuses on evaluating and improving the reasoning abilities of Smaller Language Models (SLMs) and Large Language Models (LLMs). It explores SLMs’ performance on complex tasks and their limitations with simpler ones. This thesis …","url":["https://theses.hal.science/tel-04654171/document"]}
{"year":"2024","title":"Evaluating and Mitigating Limitations of Large Language Models in Clinical Decision Making","authors":["P Hager, F Jungmann, K Bhagat, I Hubrecht, M Knauer… - medRxiv, 2024"],"snippet":"Clinical decision making is one of the most impactful parts of a physician's responsibilities and stands to benefit greatly from AI solutions and large language models (LLMs) in particular. However, while LLMs have achieved excellent …","url":["https://www.medrxiv.org/content/medrxiv/early/2024/01/26/2024.01.26.24301810.full.pdf"]}
{"year":"2024","title":"Evaluating Cultural Awareness of LLMs for Yoruba, Malayalam, and English","authors":["F Dawson, Z Mosunmola, S Pocker, RA Dandekar… - arXiv preprint arXiv …, 2024"],"snippet":"… Table 1 shows the distribution of languages in Common Crawl, a dataset commonly used for training LLMs. … The Common Crawl data 1 shows that English dominates LLM training data (45%), while Yoruba and Malayalam account for only …","url":["https://arxiv.org/pdf/2410.01811"]}
{"year":"2024","title":"Evaluating Differential Privacy Approaches for Query Obfuscation in Information Retrieval","authors":["G Faggioli, N Ferro - 2023"],"snippet":"Protecting the privacy of a user while they interact with an Information Retrieval (IR) system is crucial. This becomes more challenging when the IR system is not cooperative in satisfying the user’s privacy needs. Recent advancements in Natural …","url":["https://ceur-ws.org/Vol-3643/paper5.pdf"]}
{"year":"2024","title":"Evaluating embedded semantics for accessibility description of web crawl data","authors":["R Navarrete, D Martinez-Mosquera, L Recalde… - AHFE (2023) International …, 2023"],"snippet":"… The dataset for analysis is provided by Web Data Commons (WDC), an organization that releases extracted data from Common Crawl (CC), the largest web corpus available to the public. The dataset was released in October 2021 …","url":["https://www.researchgate.net/profile/Diana-Martinez-Mosquera/publication/372284128_Evaluating_embedded_semantics_for_accessibility_description_of_web_crawl_data/links/658ee9706f6e450f19b4b6a5/Evaluating-embedded-semantics-for-accessibility-description-of-web-crawl-data.pdf"]}
{"year":"2024","title":"Evaluating Embedding Models for Clustering Italian Political News: A Comparative Study of Text-Embedding-3-Large and UmBERTo","authors":["F Giglietto"],"snippet":"… This study compares two embedding models: OpenAI's text-embedding-3-large model and umberto-commoncrawl-cased-v1 (hereafter referred to as UmBERTo) (Parisi et al., 2020). UmBERTo, a BERT-based model (more specifically RoBERTa-based) …","url":["https://osf.io/2j9ed/download"]}
{"year":"2024","title":"Evaluating English-language morphological awareness assessments","authors":["CL Hudson Kam, E Sadlier-Brown, S Clark, C Jang… - First Language, 2024","CLH Kam, E Sadlier-Brown, S Clark, C Jang, CD Epp… - First Language, 2024"],"snippet":"… These corpora were selected because they contain language that children are exposed to, and so, provide a more realistic picture of children’s potential knowledge than an adult-language based corpus would (eg the Enron email dataset …","url":["https://journals.sagepub.com/doi/pdf/10.1177/01427237241245500","https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11293997/"]}
{"year":"2024","title":"Evaluating Gender, Racial, and Age Biases in Large Language Models: A Comparative Analysis of Occupational and Crime Scenarios","authors":["V Mirza, R Kulkarni, A Jadhav - arXiv preprint arXiv:2409.14583, 2024"],"snippet":"Recent advancements in Large Language Models(LLMs) have been notable, yet widespread enterprise adoption remains limited due to various constraints. This paper examines bias in LLMs-a crucial issue affecting their usability, reliability, and …","url":["https://arxiv.org/pdf/2409.14583"]}
{"year":"2024","title":"Evaluating Generative Language Models in Japanese Using Question-Answering Templates: A Synthetic Data Generation Approach","authors":["V Norrman - 2024"],"snippet":"In the last five years, transformer-based large language models have not only made tremendous advancements in fluent and accurate text generation, but also show unparalleled performance as zero-or few-shot shot learners of numerous …","url":["https://www.diva-portal.org/smash/get/diva2:1897405/FULLTEXT01.pdf"]}
{"year":"2024","title":"Evaluating GPT and BERT models for Protein-Protein interaction identification in biomedical text","authors":["H Rehana, NB Çam, M Basmaci, J Zheng, C Jemiyo… - Bioinformatics Advances, 2024"],"snippet":"Detecting protein-protein interactions is crucial for understanding genetic mechanisms, disease pathogenesis, and drug design. As biomedical literature continues to grow rapidly, there is an increasing need for automated and accurate …","url":["https://academic.oup.com/bioinformaticsadvances/advance-article-pdf/doi/10.1093/bioadv/vbae133/59091493/vbae133.pdf"]}
{"year":"2024","title":"Evaluating Language Model Vulnerability to Poisoning Attacks in Low-Resource Settings","authors":["R Plant, MV Giuffrida, N Pitropakis, D Gkatzia - IEEE/ACM Transactions on Audio …, 2024"],"snippet":"Pre-trained language models are a highly effective source of knowledge transfer for natural language processing tasks, as their development represents an investment of resources beyond the reach of most researchers and end users. The widespread …","url":["https://ieeexplore.ieee.org/abstract/document/10771712/"]}
{"year":"2024","title":"Evaluating Large Language Model Performance on Haskell","authors":["A Chen - 2024"],"snippet":"I introduce HaskellEval, a Haskell evaluation benchmark for Large Language Models. HaskellEval’s curation leverages a novel synthetic generation framework, streamlining the process of dataset curation by minimizing manual intervention. The …","url":["https://scholarworks.wm.edu/cgi/viewcontent.cgi?article=3209&context=honorstheses"]}
{"year":"2024","title":"Evaluating Large Language Models for Generalization and Robustness via Data Compression","authors":["Y Li, Y Guo, F Guerin, C Lin - arXiv preprint arXiv:2402.00861, 2024"],"snippet":"Existing methods for evaluating large language models face challenges such as data contamination, sensitivity to prompts, and the high cost of benchmark creation. To address this, we propose a lossless data compression based evaluation …","url":["https://arxiv.org/pdf/2402.00861"]}
{"year":"2024","title":"Evaluating Large Language Models on Academic Literature Understanding and Review: An Empirical Study among Early-stage Scholars","authors":["J Wang, H Hu, Z Wang, Y Song, Y Sheng, D He - 2024"],"snippet":"The rapid advancement of large language models (LLMs) such as ChatGPT makes LLM-based academic tools possible. However, little research has empirically evaluated how scholars perform different types of academic tasks with LLMs …","url":["https://personal.hkust-gz.edu.cn/hedengbo/assets/publicationPDFs/Wang_CHI_2024a.pdf"]}
{"year":"2024","title":"Evaluating LLMs on large contexts: a RAG approach on text comprehension","authors":["B Lu - 2024"],"snippet":"While the latest Large Language Models (LLMs) continue to expand in size and context window capacity, their knowledge base remains constrained by their training corpus. Retrieval Augmented Generation (RAG) offers a solution to this limitation by …","url":["https://matheo.uliege.be/bitstream/2268.2/21150/4/Master_thesis.pdf"]}
{"year":"2024","title":"Evaluating Machine Learning and Deep Learning Approaches for Phishing URL Detection: A Systematic Review and Future Directions","authors":["PS PREETI - International Journal of Computer Science and …, 2024"],"snippet":"Attacks involving phishing URLs have become a significant menace in digital realm, presenting substantial dangers to individuals. In response to this escalating danger, researcher and professionals have formulated a range of anti-phishing strategies …","url":["https://www.academia.edu/download/119240057/01092413_IJCSIS_Paper.pdf"]}
{"year":"2024","title":"Evaluating Multilingual Abstractive Dialogue Summarization in Indian Languages using mT5-small & IndicBART","authors":["M Sharma, G Goyal, A Gupta, R Rani, A Sharma, A Dev - 2024 IEEE 9th International …, 2024"],"snippet":"… The mC4 dataset consists of natural text in 101 languages including Indian languages like Hindi, Mararti, Punjabi and others, that was collected from the public Common Crawl web scrape. Introduced as a multilingual, sequence-to-sequence pre-trained …","url":["https://ieeexplore.ieee.org/abstract/document/10543588/"]}
{"year":"2024","title":"Evaluating Natural Monopoly Conditions in the AI Foundation Model Market","authors":["JON SCHMID, T SYTSMA, A SHENK - 2024"],"snippet":"The authors of this report examined the economic and production attributes of pre-trained artificial intelligence (AI) foundation models to answer the following questions: Does the market for foundation models have the characteristics of a natural monopoly, and …","url":["https://www.rand.org/content/dam/rand/pubs/research_reports/RRA3400/RRA3415-1/RAND_RRA3415-1.pdf"]}
{"year":"2024","title":"Evaluating Prediction-Based Theories of Bilingual Comprehension of Spanish/English Codeswitches.","authors":["N Vernooij - 2024"],"snippet":"This dissertation investigates how bilinguals use their two grammars to comprehend written intra-sentential codeswitches. I focus on adjective/noun constructions in Spanish and English where I manipulate the congruence of grammatical word order …","url":["https://deepblue.lib.umich.edu/bitstream/handle/2027.42/194750/vernooij_1.pdf?sequence=1"]}
{"year":"2024","title":"Evaluating Shortest Edit Script Methods for Contextual Lemmatization","authors":["O Toporkov, R Agerri - arXiv preprint arXiv:2403.16968, 2024"],"snippet":"Modern contextual lemmatizers often rely on automatically induced Shortest Edit Scripts (SES), namely, the number of edit operations to transform a word form into its lemma. In fact, different methods of computing SES have been proposed as an …","url":["https://arxiv.org/pdf/2403.16968"]}
{"year":"2024","title":"Evaluating SQL Understanding in Large Language Models","authors":["A Rahaman, A Zheng, M Milani, F Chiang, R Pottinger - arXiv preprint arXiv …, 2024"],"snippet":"… Released by OpenAI in late 2022, GPT3.5 consists of 175 billion parameters and is trained on a large corpus including Common Crawl, Wikipedia, and various books and academic texts. It is designed to handle diverse NLP tasks [3]. GPT4. …","url":["https://arxiv.org/pdf/2410.10680"]}
{"year":"2024","title":"Evaluating the Capabilities of GPT-4 in Full-Stack Web Development: A Practical Approach","authors":["J Sandberg, Y Zhang - 2024"],"snippet":"With the rapid advancements in Artificial Intelligence, leveraging machine learning models for various domains has become increasingly prevalent. This thesis explores the capabilities of OpenAI’s Generative Pre-trained Transformer 4 (GPT-4) within full-stack …","url":["https://www.diva-portal.org/smash/get/diva2:1883159/FULLTEXT01.pdf"]}
{"year":"2024","title":"Evaluating the Effectiveness of Machine Translation in Preserving Metaphorical Expressions from Source Texts to Target Languages","authors":["Л Матякубова - Лингвоспектр, 2024"],"snippet":"Annotation. With the rapid proliferation of Neural Machine Translation (NMT) systems, questions persist about their ability to handle nuanced linguistic phenomena—particularly metaphorical expressions. Metaphors are culturally and contextually embedded …","url":["https://lingvospektr.uz/index.php/lngsp/article/view/192"]}
{"year":"2024","title":"Evaluating the Experience of LGBTQ+ People Using Large Language Model Based Chatbots for Mental Health Support","authors":["Z Ma, Y Mei, Y Long, Z Su, KZ Gajos - arXiv preprint arXiv:2402.09260, 2024"],"snippet":"LGBTQ+ individuals are increasingly turning to chatbots powered by large language models (LLMs) to meet their mental health needs. However, little research has explored whether these chatbots can adequately and safely provide tailored support …","url":["https://arxiv.org/pdf/2402.09260"]}
{"year":"2024","title":"Evaluating the Factuality of Zero-shot Summarizers Across Varied Domains","authors":["S Ramprasad, K Krishna, ZC Lipton, BC Wallace - arXiv preprint arXiv:2402.03509, 2024"],"snippet":"Recent work has shown that large language models (LLMs) are capable of generating summaries zero-shot (ie, without explicit supervision) that, under human assessment, are often comparable or even preferred to manually composed …","url":["https://arxiv.org/pdf/2402.03509"]}
{"year":"2024","title":"Evaluating the Impact of Advanced LLM Techniques on AI-Lecture Tutors for a Robotics Course","authors":["S Kahl, F Löffler, M Maciol, F Ridder, M Schmitz… - arXiv preprint arXiv …, 2024"],"snippet":"This study evaluates the performance of Large Language Models (LLMs) as an Artificial Intelligence-based tutor for a university course. In particular, different advanced techniques are utilized, such as prompt engineering, Retrieval-Augmented-Generation …","url":["https://arxiv.org/pdf/2408.04645"]}
{"year":"2024","title":"EVALUATING THE IMPACT OF ARTIFICIAL INTELLIGENCE ON BUSINESS THROUGH SENTIMENT ANALYSIS.","authors":["IC Marian - Young Economists Journal/Revista Tinerilor …, 2024"],"snippet":"This article investigates the impact of artificial intelligence (AI) on business and economics using the technique of sentiment analysis. This technique uses natural language processing (NLP) to gauge audience attitudes and perceptions. By …","url":["https://search.ebscohost.com/login.aspx?direct=true&profile=ehost&scope=site&authtype=crawler&jrnl=15839982&AN=181594017&h=FYnc5zI1gMLJ3vumNlmOOnBmxAmd8Hrnw%2BKatMeOZhXxoZpB1R3m8IiJkuotZ8x%2Bvxv1KCSNkeYkRQxC3w%2BJsA%3D%3D&crl=c"]}
{"year":"2024","title":"Evaluating the impact of design decisions on passive DNS-based domain rankings","authors":["V Le Pochat, S Fernandez, T Van Goethem…"],"snippet":"… They recommend that researchers select a random sample of websites among Common Crawl hosts. Ruth et al. [6] compared top lists to Cloudflare traffic data, concluding that the Chrome User Experience Report [11] most accurately represents …","url":["https://lepoch.at/files/domain-ranking-design-decisions-tma24.pdf"]}
{"year":"2024","title":"Evaluating the Performance of Topic Modeling Techniques with Human Validation to Support Qualitative Analysis","authors":["JD Romero, MA Feijoo-Garcia, G Nanda, B Newell… - Big Data and Cognitive …, 2024"],"snippet":"Examining the effectiveness of machine learning techniques in analyzing engineering students’ decision-making processes through topic modeling during simulation-based design tasks is crucial for advancing educational methods and …","url":["https://www.mdpi.com/2504-2289/8/10/132"]}
{"year":"2024","title":"Evaluating the Quality of AI-Generated Items for a Certification Exam","authors":["AD Mead, C Zhou - Journal of Applied Testing Technology, 2024"],"snippet":"OpenAI’s GPT-3 model can write multiple-choice exam items. This paper reviewed the literature on automatic item generation and then described the recent history of OpenAI GPT models and their operation, and then described a methodology for …","url":["http://jattjournal.net/index.php/atp/article/download/173204/117130"]}
{"year":"2024","title":"Evaluating Transformers and Linguistic Features integration for Author Profiling tasks in Spanish","authors":["JA García-Díaz, G Beydoun, R Valencia-García - Data & Knowledge Engineering, 2024"],"snippet":"… This model is a training from scratch of RoBERTa, trained on the Spanish texts from mC4, compiled from the public Common Crawl web … This is a multilingual version of RoBERTa, pre-trained with about 2.5 TB of data from the 100 different …","url":["https://www.sciencedirect.com/science/article/pii/S0169023X24000314"]}
{"year":"2024","title":"Evaluating Turkish BERT-based Language Models for Effective Customer Feedback Interpretation in CRM","authors":["C İşcan, MF Özkara, AE Çelik, A Akbulut - 2024 9th International Conference on …, 2024"],"snippet":"… It is a multilingual version of the RoBERTa model which is pre-trained on 2.5TB of filtered CommonCrawl data comprising 100 languages. In this study, we employed a selection of cutting-edge and highly efficient tools that we discovered during our …","url":["https://ieeexplore.ieee.org/abstract/document/10773436/"]}
{"year":"2024","title":"Evaluating Word Embedding Methods for Sentiment Analysis","authors":["K Kraayeveld"],"snippet":"We evaluate the performance of various word embedding models for sentiment prediction. Specifically, we train Word2vec, GloVe, and FastText models on 3.6 million Amazon product reviews and assess their predictive performance compared …","url":["https://thesis.eur.nl/pub/72694/Final-Draft-MSc-Thesis.pdf"]}
{"year":"2024","title":"Evaluation and Adaptation of Neural Language Models for Under-Resourced Languages","authors":["W de Vries - 2024"],"snippet":"Abstract Language models are now commonly used by researchers, industry, and anyone interested. However, language models of all sizes and types are primarily developed for the English language while efforts on other languages lag behind …","url":["https://research.rug.nl/files/993731020/Complete_thesis.pdf"]}
{"year":"2024","title":"Evaluation of AI-generated Responses by Different Artificial Intelligence Chatbots to the Clinical Decision-Making Case-Based Questions in Oral and Maxillofacial …","authors":["A Azadi, F Gorjinejad, H Mohammad-Rahimi, R Tabrizi… - Oral Surgery, Oral Medicine …, 2024"],"snippet":"Objectives This study aims to evaluate the correctness of the generated answers by Google Bard, GPT-3.5, GPT-4, Claude-Instant, and Bing chatbots to decision-making clinical questions in the oral and maxillofacial surgery (OMFS) area. Study Design A …","url":["https://www.sciencedirect.com/science/article/pii/S2212440324000956"]}
{"year":"2024","title":"Evaluation of Geographical Distortions in Language Models: A Crucial Step Towards Equitable Representations","authors":["R Decoupes, R Interdonato, M Roche, M Teisseire… - arXiv preprint arXiv …, 2024"],"snippet":"Language models now constitute essential tools for improving efficiency for many professional tasks such as writing, coding, or learning. For this reason, it is imperative to identify inherent biases. In the field of Natural Language Processing …","url":["https://arxiv.org/pdf/2404.17401"]}
{"year":"2024","title":"Evaluation of word embedding models used for diachronic semantic change analysis","authors":["Y Maslennikova, V Bochkarev - Journal of Physics: Conference Series, 2024"],"snippet":"… As a reference word2vec model, we used pre-trained word vectors that were trained on English versions of Common Crawl dataset using fastText library [14]. fastText is a library for efficient learning of word representations and sentence …","url":["https://iopscience.iop.org/article/10.1088/1742-6596/2701/1/012082/pdf"]}
{"year":"2024","title":"Evaluation-Focused Multidimensional Score for Turkish Abstractive Text Summarization","authors":["NZ Kayalı, Sİ Omurca - Sakarya University Journal of Computer and …, 2024"],"snippet":"… A multilingual variation of the T5 model, which is trained on common crawl-based data and covers 101 different languages, is called mT5 [27]. Our studies used the mT5 model as the second language model after the BERTurk model. …","url":["http://saucis.sakarya.edu.tr/en/download/article-file/4019375"]}
{"year":"2024","title":"Evaluations Using Wikipedia without Data Contamination: From Trusting Articles to Trusting Edit Processes","authors":["LA Kaffee, H Face, I Johnson"],"snippet":"… Even when Wikipedia is not explicitly including in training data, it is a substantial part of Common Crawl1, a massive web dataset frequently used for model training. … 1https://commoncrawl.github.io/cc-crawl-statistics/plots/domains …","url":["https://evaleval.github.io/accepted_papers/EvalEval_24_Kaffee.pdf"]}
{"year":"2024","title":"Event extraction using a Large Language Model","authors":["I Kovac, T Madzarac - Text Analysis and Retrieval 2024 Course Project …"],"snippet":"Event extraction is an important problem of Natural Language Processing, and its goal is to extract events that have happened in the text alongside with its attributes. There are a lot of models specified for this task, but in this paper, we decided to test …","url":["https://www.fer.unizg.hr/_download/repository/TAR-2024-ProjectReports.pdf#page=39"]}
{"year":"2024","title":"Evidence for a digital divide? Measuring DNS dependencies in the context of the indigenous population of Australia","authors":["R Holz, N Nazemi, O Tavallaie, AY Zomaya"],"snippet":"We recently presented a work-in-progress paper at the Workshop on Transparency, Accountability and User Control for a Responsible Internet (TAURIN 2023). Our paper investigates the relationship between the digital divide, Internet transparency …","url":["https://www.ietf.org/slides/slides-biasws-evidence-for-a-digital-divide-measuring-dns-dependencies-in-the-context-of-the-indigenous-population-of-australia-00.pdf"]}
{"year":"2024","title":"EVLM: An Efficient Vision-Language Model for Visual Understanding","authors":["K Chen, D Shen, H Zhong, H Zhong, K Xia, D Xu… - arXiv preprint arXiv …, 2024"],"snippet":"In the field of multi-modal language models, the majority of methods are built on an architecture similar to LLaVA. These models use a single-layer ViT feature as a visual prompt, directly feeding it into the language models alongside textual tokens …","url":["https://arxiv.org/pdf/2407.14177"]}
{"year":"2024","title":"Evolution and Prospects of Foundation Models: From Large Language Models to Large Multimodal Models","authors":["Z Chen, L Xu, H Zheng, L Chen, A Tolba, L Zhao, K Yu… - Computers, Materials and …, 2024"],"snippet":"Since the 1950s, when the Turing Test was introduced, there has been notable progress in machine language intelligence. Language modeling, crucial for AI development, has evolved from statistical to neural models over the last two decades …","url":["https://www.sciencedirect.com/org/science/article/pii/S1546221824005472"]}
{"year":"2024","title":"Evolution of Generative AI","authors":["R Gogula, R Teja Swarup, PRK Reddy, PP Kumar - … the Effects of Generative AI on …, 2024"],"snippet":"… For language models such as GPT-3, the Common Crawl dataset used to train the model has an original size of 45 terabytes before pre-processing. After applying the filtering method, the data is then reduced to a size of 570 gigabytes. Big data …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=-qsnEQAAQBAJ&oi=fnd&pg=PA15&dq=commoncrawl&ots=JdMp-ykpWp&sig=KasoHNXj6bQ60QL1TjEqzxabtzo"]}
{"year":"2024","title":"EXAMINING ACCURACY HETEROGENEITIES IN CLASSIFICATION OF MULTILINGUAL AI-GENERATED TEXT","authors":["R Subramaniam"],"snippet":"Tools for detection of AI-generated texts are used globally, however, the nature of the apparent accuracy disparities between languages must be further observed. This paper aims to examine the nature of these differences through testing OpenAI’s …","url":["https://csitcp.org/paper/13/1312csit21.pdf"]}
{"year":"2024","title":"Experience of Training a 1.7 B-Parameter LLaMa Model From Scratch","authors":["MQ Li, B Fung, SC Huang - arXiv preprint arXiv:2412.13335, 2024"],"snippet":"Pretraining large language models is a complex endeavor influenced by multiple factors, including model architecture, data quality, training continuity, and hardware constraints. In this paper, we share insights gained from the experience of training …","url":["https://arxiv.org/pdf/2412.13335"]}
{"year":"2024","title":"Experimental Evaluation of Possible Feature Combinations for the Detection of Fraudulent Online Shops","authors":["A Janavičiūtė, A Liutkevičius, G Dabužinskas… - Applied Sciences, 2024"],"snippet":"Online shopping has become a common and popular form of shopping, so online attackers try to extract money from customers by creating online shops whose purpose is to compel the buyer to disclose credit card details or to pay money for …","url":["https://www.mdpi.com/2076-3417/14/2/919"]}
{"year":"2024","title":"Expert Phishing Detection System","authors":["A Alsarhan, I Al-Aiash, D Al-Fraihat, M Aljaidi… - 2024 IEEE International …, 2024"],"snippet":"… and Common Crawl datasets. The highest accuracy reported in this work was 83.00%, achieved with the RF classifier. In the study conducted by [16], the authors employed Machine Learning (ML) and Heuristic methods on three datasets—PhishTank …","url":["https://ieeexplore.ieee.org/abstract/document/10617460/"]}
{"year":"2024","title":"Expert-Like Systems Engineering Artifacts? Insights from an Empirical","authors":["M Husain, P Wach, TG Topcu - The Proceedings of the 2024 Conference on Systems …"],"snippet":"The old saga of complex system development continues as the vast majority of government and industry programs continue to result in cost and schedule overruns [1–7]. While numerous researchers and government reports attribute this trend to the ever-increasing …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=OjgWEQAAQBAJ&oi=fnd&pg=PA369&dq=commoncrawl&ots=puTo4zCMjZ&sig=e_YoO4A_tURc9zzgSkR2zrjKvWs"]}
{"year":"2024","title":"Explainable Generative AI (GenXAI): A Survey, Conceptualization, and Research Agenda","authors":["J Schneider - arXiv preprint arXiv:2404.09554, 2024"],"snippet":"Generative AI (GenAI) marked a shift from AI being able to recognize to AI being able to generate solutions for a wide variety of tasks. As the generated solutions and applications become increasingly more complex and multi-faceted, novel needs …","url":["https://arxiv.org/pdf/2404.09554"]}
{"year":"2024","title":"Exploiting Domain-Specific Parallel Data on Multilingual Language Models for Low-resource Language Translation","authors":["S Ranathungaa, S Nayak, STC Huang, Y Mao, T Su…"],"snippet":"Neural Machine Translation (NMT) systems built on multilingual sequenceto-sequence Language Models (msLMs) fail to deliver expected results when the amount of parallel data for a language, as well as the language’s representation in the model …","url":["https://www.researchgate.net/profile/Surangika-Ranathunga/publication/387295947_Exploiting_Domain-Specific_Parallel_Data_on_Multilingual_Language_Models_for_Low-resource_Language_Translation/links/676694c8e74ca64e1f24059b/Exploiting-Domain-Specific-Parallel-Data-on-Multilingual-Language-Models-for-Low-resource-Language-Translation.pdf"]}
{"year":"2024","title":"Exploration of Content-Based Cross-Domain Podcast Recommender Systems","authors":["M Hofmaier - 2024"],"snippet":"Podcasts have become a popular medium in the last decade. The huge amount of data available motivates research on podcast recommender systems to make this data accessible to users. Since interaction-based datasets for podcasts are only …","url":["https://repositum.tuwien.at/bitstream/20.500.12708/205267/1/Hofmaier%20Matthias%20-%202024%20-%20Exploration%20of%20Content-Based%20Cross-Domain%20Podcast...pdf"]}
{"year":"2024","title":"Exploring AI-driven approaches for unstructured document analysis and future horizons","authors":["SV Mahadevkar, S Patil, K Kotecha, LW Soong… - Journal of Big Data, 2024"],"snippet":"In the current industrial landscape, a significant number of sectors are grappling with the challenges posed by unstructured data, which incurs financial losses amounting to millions annually. If harnessed effectively, this data has the potential to …","url":["https://journalofbigdata.springeropen.com/articles/10.1186/s40537-024-00948-z"]}
{"year":"2024","title":"Exploring Automatic Text Simplification for Lithuanian","authors":["J Mandravickaitė, E Rimkiene, D Kalinauskaitė… - Proceedings of the 20th …, 2024"],"snippet":"… To train mT5, the authors introduced a multilingual variant of the C4 dataset called mC4, which comprises textual data in 101 languages drawn from the public Common Crawl web scrape. It makes mT5 model particularly suitable for languages …","url":["https://aclanthology.org/2024.konvens-main.4.pdf"]}
{"year":"2024","title":"Exploring Emergent Phenomena in AI: A Pantheistic Approach to the Underlying Source of Information","authors":["DC Youvan - 2024"],"snippet":"Emergent phenomena in artificial intelligence (AI) systems, where creative, novel, and unexpected outputs arise, have long intrigued researchers. While these behaviors are typically seen as products of complex computation, this paper …","url":["https://www.researchgate.net/profile/Douglas-Youvan/publication/383276553_Exploring_Emergent_Phenomena_in_AI_A_Pantheistic_Approach_to_the_Underlying_Source_of_Information/links/66c6629ac2eaa500230cd57d/Exploring-Emergent-Phenomena-in-AI-A-Pantheistic-Approach-to-the-Underlying-Source-of-Information.pdf"]}
{"year":"2024","title":"Exploring Fine-tuned Generative Models for Keyphrase Selection: A Case Study for Russian","authors":["A Glazkova, D Morozov - arXiv preprint arXiv:2409.10640, 2024"],"snippet":"Keyphrase selection plays a pivotal role within the domain of scholarly texts, facilitating efficient information retrieval, summarization, and indexing. In this work, we explored how to apply fine-tuned generative transformer-based models to the …","url":["https://arxiv.org/pdf/2409.10640"]}
{"year":"2024","title":"Exploring Intermediate Training for Chinese Offensive Language Detection","authors":["W Zhong - 2024"],"snippet":"Offensive language detection (OLD) has become a crucial area of research in recent years. Despite growing interest, the majority of current studies have focused on English, leaving many other languages, like Chinese, relatively unexplored. In this …","url":["https://www.diva-portal.org/smash/get/diva2:1902018/FULLTEXT01.pdf"]}
{"year":"2024","title":"Exploring Korean Medicine professions' perspectives on the applicability of ChatGPT in facial palsy practice: A web-based survey","authors":["JS Lee, SA Kim, T Kim, S Lee, TH Kim, JW Kang - European Journal of Integrative …, 2024"],"snippet":"Introduction Since November 2022, when Chat generative pre-trained transformer (ChatGPT) was released, studies have been conducted to explore its potential use in various text-based areas. In the field of Korean Medicine (KM), studies evaluating the …","url":["https://www.sciencedirect.com/science/article/pii/S187638202400091X"]}
{"year":"2024","title":"Exploring Language Models and Question Answering in Biomedical and Arabic Domains","authors":["S Alrowili - 2024"],"snippet":"Despite the success of the Transformer model and its variations (eg, BERT, ALBERT, ELECTRA, T5) in addressing NLP tasks, similar success is not achieved when these models are applied to specific domains (eg, biomedical) and limited-resources …","url":["https://search.proquest.com/openview/0e40df4b6c2b0bc68303a06d31aa19a8/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
{"year":"2024","title":"Exploring large language models for microstructure evolution in materials","authors":["P Satpute, S Tiwari, M Gupta, S Ghosh - Materials Today Communications, 2024"],"snippet":"… These models are based on massive machine learning (ML) architectures (specifically transformer neural networks [3], [4]) pre-trained on a massive corpus of text data from diverse internet sources like Common Crawl [5] and Wikipedia [6], each …","url":["https://www.sciencedirect.com/science/article/abs/pii/S2352492824015642"]}
{"year":"2024","title":"Exploring LLMs' Capabilities for Error Detection in Dutch L1 and L2 Writing Products","authors":["J Kruijsbergen, S Van Geertruyen, V Hoste… - Computational Linguistics in …, 2024"],"snippet":"This research examines the capabilities of Large Language Models for writing error detection, which can be seen as a first step towards automated writing support. Our work focuses on Dutch writing error detection, targeting two envisaged end-users …","url":["https://www.clinjournal.org/clinj/article/download/179/195"]}
{"year":"2024","title":"Exploring Low-Resource Machine Translation: Case Study of Lao-Vietnamese Translation","authors":["QD Tran - 2024 International Conference on Multimedia Analysis …, 2024"],"snippet":"Despite ongoing research efforts in recent years, machine translation in low-resource settings remains challenging. This paper explores recent methods to enhance low-resource machine translation (LoResMT), especially for both-side low-resource language …","url":["https://ieeexplore.ieee.org/abstract/document/10660932/"]}
{"year":"2024","title":"Exploring Machine Learning for Malware Detection With Feature Selection, Explainable AI, and Generative Adversarial Networks","authors":["DQ Smith Jr - 2023"],"snippet":"This research focuses on the detection of malware in sample datasets using machine learning algorithms. As malware becomes more advanced against detection in the cybersecurity sector, researchers have looked for other methods to …","url":["https://search.proquest.com/openview/3851d57453e23cecb2a424ea1df4e607/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
{"year":"2024","title":"Exploring Multilingual Embeddings for Italian Semantic Search: A Pretrained and Fine-tuned Approach","authors":["N RINALDI"],"snippet":"This thesis explores the application of multilingual embedding models to the semantic search for the Italian language, a critical step toward integrating these technologies into Retrieval-Augmented Generation (RAG) frameworks. The work …","url":["https://thesis.unipd.it/bitstream/20.500.12608/80899/1/Nicol%C3%B2%20Rinaldi%20-%20Exploring%20Multilingual%20Embeddings%20for%20Italian%20Semantic%20Search%20A%20Pretrained%20and%20Fine%20tuned%20Approach.pdf"]}
{"year":"2024","title":"Exploring Recent NLP Advances for Tamil: Word Vectors and Hybrid Deep Learning Architectures","authors":["A Aravinthan, C Eugene - International Journal on Advances in ICT for Emerging …, 2024"],"snippet":"The advancements of deep learning methods and the availability of large corpora and data sets have led to an exponential increase in the performance of Natural Language Processing (NLP) methods resulting in successful NLP applications for …","url":["https://icter.sljol.info/articles/7279/files/670610e96e7c6.pdf"]}
{"year":"2024","title":"Exploring Scaling Laws for Local SGD in Large Language Model Training","authors":["Q He, X Zhuang, Z Wu - arXiv preprint arXiv:2409.13198, 2024"],"snippet":"This paper investigates scaling laws for local SGD in LLM training, a distributed optimization algorithm that facilitates training on loosely connected devices. Through extensive experiments, we show that local SGD achieves competitive results …","url":["https://arxiv.org/pdf/2409.13198"]}
{"year":"2024","title":"Exploring the Abilities of Large Language Models to Solve Proportional Analogies via Knowledge-Enhanced Prompting","authors":["T Wijesiriwardene, R Wickramarachchi, S Vennam… - arXiv preprint arXiv …, 2024"],"snippet":"Making analogies is fundamental to cognition. Proportional analogies, which consist of four terms, are often used to assess linguistic and cognitive abilities. For instance, completing analogies like \"Oxygen is to Gas as is to \" requires identifying the …","url":["https://arxiv.org/pdf/2412.00869"]}
{"year":"2024","title":"Exploring the competence of ChatGPT for customer and patient service management","authors":["A Haleem, M Javaid, RP Singh - Intelligent Pharmacy, 2024"],"snippet":"The modern language generation model ChatGPT, created by Open Artificial Intelligence (AI), is recognised for its capacity to comprehend context and produce pertinent content. This model is built on the transformer architecture, which enables …","url":["https://www.sciencedirect.com/science/article/pii/S2949866X24000480"]}
{"year":"2024","title":"Exploring the Effectiveness of Object-Centric Representations in Visual Question Answering: Comparative Insights with Foundation Models","authors":["AMK Mamaghan, S Papa, KH Johansson, S Bauer… - arXiv preprint arXiv …, 2024"],"snippet":"Object-centric (OC) representations, which represent the state of a visual scene by modeling it as a composition of objects, have the potential to be used in various downstream tasks to achieve systematic compositional generalization and facilitate …","url":["https://arxiv.org/pdf/2407.15589"]}
{"year":"2024","title":"Exploring the Potential of Emerging Digitainability—GPT Reasoning in Energy Management of Kindergartens","authors":["N Jurišević, D Gordić, D Nikolić, A Nešović, R Kowalik - Buildings, 2024"],"snippet":"One of the barriers to the rapid transition of societies toward a more sustainable future is a scarcity of field experts. Members of scientific and professional communities believe that this obstacle could be overcome by supplementing the …","url":["https://www.mdpi.com/2075-5309/14/12/4038"]}
{"year":"2024","title":"Exploring the Reasoning Abilities of Multimodal Large Language Models (MLLMs): A Comprehensive Survey on Emerging Trends in Multimodal Reasoning","authors":["Y Wang, W Chen, X Han, X Lin, H Zhao, Y Liu, B Zhai… - arXiv preprint arXiv …, 2024"],"snippet":"Strong Artificial Intelligence (Strong AI) or Artificial General Intelligence (AGI) with abstract reasoning ability is the goal of next-generation AI. Recent advancements in Large Language Models (LLMs), along with the emerging field of Multimodal Large …","url":["https://arxiv.org/pdf/2401.06805"]}
{"year":"2024","title":"Exploring the Robustness of Task-oriented Dialogue Systems for Colloquial German Varieties","authors":["E Artemova, V Blaschke, B Plank - arXiv preprint arXiv:2402.02078, 2024"],"snippet":"Mainstream cross-lingual task-oriented dialogue (ToD) systems leverage the transfer learning paradigm by training a joint model for intent recognition and slot-filling in English and applying it, zero-shot, to other languages. We address a gap in prior …","url":["https://arxiv.org/pdf/2402.02078"]}
{"year":"2024","title":"Exploring the Role of ChatGPT in Cardiology: A Systematic Review of the Current Literature","authors":["A Sharma, T Medapalli, M Alexandrou, E Brilakis… - Cureus, 2024"],"snippet":"Chat Generative Pre-Trained Transformer (ChatGPT) is a chatbot based on a large language model that has gained public interest since its release in November 2022. This systematic review examines the current literature on the potential applications …","url":["https://www.cureus.com/articles/244400-exploring-the-role-of-chatgpt-in-cardiology-a-systematic-review-of-the-current-literature.pdf"]}
{"year":"2024","title":"Exploring the role of ChatGPT in higher education: opportunities, challenges and ethical considerations","authors":["A Zeb, R Ullah, R Karim - The International Journal of Information and Learning …, 2024"],"snippet":"Purpose This paper aims to examine the opportunities and challenges of using ChatGPT in higher education. Furthermore, it is also discuss the potential risks and plunders of these tools. Design/methodology/approach The paper discuss the use of …","url":["https://www.emerald.com/insight/content/doi/10.1108/IJILT-04-2023-0046/full/html"]}
{"year":"2024","title":"Exploring transformer models in the sentiment analysis task for the under-resource Bengali language","authors":["MN Hoque, U Salma, MJ Uddin, MM Ahamad, S Aktar - Natural Language Processing …, 2024"],"snippet":"In the sentiment analysis (SA) task, we can obtain a positive or negative-typed comment or feedback from an online user or a customer about any object, such as a movie, drama, food, and others. This user’s sentiment may positively impact various …","url":["https://www.sciencedirect.com/science/article/pii/S2949719124000396"]}
{"year":"2024","title":"Exploring very low-resource translation with llms: The university of edinburgh's submission to americasnlp 2024 translation task","authors":["V Iyer, B Malik, W Zhu, P Stepachev, P Chen… - Proceedings of the 4th …, 2024"],"snippet":"This paper describes the University of Edinburgh’s submission to the AmericasNLP 2024 shared task on the translation of Spanish into 11 indigenous American languages. We explore the ability of multilingual Large Language Models (LLMs) to …","url":["https://aclanthology.org/2024.americasnlp-1.25.pdf"]}
{"year":"2024","title":"EXPRESS: AI-Human Hybrids for Marketing Research: Leveraging LLMs as Collaborators","authors":["N Arora, I Chakraborty, Y Nishimura - Journal of Marketing, 2024"],"snippet":"The authors’ central premise is that a human-LLM hybrid approach leads to efficiency and effectiveness gains in the marketing research process. In qualitative research, they show that LLMs can assist in both data generation and analysis; …","url":["https://journals.sagepub.com/doi/abs/10.1177/00222429241276529"]}
{"year":"2024","title":"EXPRESS: Malay Lexicon Project 3: The Impact of Orthographic-Semantic Consistency on Lexical Decision Latencies","authors":["M Maziyah Mohamed, D Jared - Quarterly Journal of Experimental Psychology, 2024"],"snippet":"Theories of word processing propose that readers are sensitive to statistical co-occurrences between spelling and meaning. Orthographic-Semantic Consistency (OSC) measures provide a continuous estimate of the statistical regularities between …","url":["https://journals.sagepub.com/doi/abs/10.1177/17470218241234668"]}
{"year":"2024","title":"Extending LLMs to New Languages: A Case Study of Llama and Persian Adaptation","authors":["SM Sani, P Sadeghi, TT Vu, Y Yaghoobzadeh… - arXiv preprint arXiv …, 2024"],"snippet":"Large language models (LLMs) have made great progress in classification and text generation tasks. However, they are mainly trained on English data and often struggle with low-resource languages. In this study, we explore adding a new …","url":["https://arxiv.org/pdf/2412.13375"]}
{"year":"2024","title":"Extending the Comparative Argumentative Machine: Multilingualism and Stance Detection","authors":["I Nikishina, A Bondarenko, S Zaczek, OL Haag…"],"snippet":"The comparative argumentative machine CAM can retrieve arguments that answer comparative questions—questions that ask which of several to-be-compared options should be favored in some scenario. In this paper, we describe how we equipped …","url":["https://downloads.webis.de/publications/papers/nikishina_2024.pdf"]}
{"year":"2024","title":"Extending Translate-Train for ColBERT-X to African Language CLIR","authors":["E Yang, DJ Lawrie, P McNamee, J Mayfield - arXiv preprint arXiv:2404.08134, 2024"],"snippet":"… We used Common Crawl documents in Afriberta Corpus [6] for the four African languages and collected additional English Common Crawl documents to match the genre. We fine-tune the model for 200,000 update steps using a learning rate of 1×10-5 …","url":["https://arxiv.org/pdf/2404.08134"]}
{"year":"2024","title":"External Attack-Surface of Modern Organizations","authors":["N Gelernter, H Schulmann, M Waidner - Proceedings of the 19th ACM Asia …, 2024"],"snippet":"Navigating the maze of contemporary organizational attack surfaces is paramount in fortifying our defenses against the relentless tide of cyber incidents. However, existing network reconnaissance and security measurements, which enumerate IP …","url":["https://dl.acm.org/doi/abs/10.1145/3634737.3656295"]}
{"year":"2024","title":"Extracting emotion from resource poor language through transfer learning","authors":["A Majeed, U Imtiaz, MA Nseem, M Aleem, W Shahzad… - Multimedia Tools and …, 2024"],"snippet":"… Common Crawl materials in over 100 languages are used to train the algorithm. XLM-Roberta has seen a significant increase in training data since its first release. Several cross-language benchmarks show that XLM-R performs the best. …","url":["https://link.springer.com/article/10.1007/s11042-024-19870-w"]}
{"year":"2024","title":"Extracting intersectional stereotypes from embeddings: Developing and validating the Flexible Intersectional Stereotype Extraction procedure","authors":["TES Charlesworth, K Ghate, A Caliskan, MR Banaji - PNAS Nexus, 2024"],"snippet":"… text corpora, ranging from static GloVe embeddings trained on 840 billion words from the Common Crawl to contextualized BERT embeddings trained on a combination of Wikipedia and Common Crawl text. Additionally, in supplemental …","url":["https://academic.oup.com/pnasnexus/article/3/3/pgae089/7626925"]}
{"year":"2024","title":"Extracting knowledge from polymorphic textual data using graph-based machine learning and transformer-based deep learning techniques","authors":["N Giarelis - 2024"],"snippet":"The aim of this thesis is to develop novel approaches that extract meaningful knowledge from polymorphic (unstructured and structured) textual data. To achieve this, we rely on recent advancements from the areas of Machine Learning (ML) …","url":["https://www.researchgate.net/profile/Nikolaos-Giarelis/publication/387218530_Extracting_knowledge_from_polymorphic_textual_data_using_graph-based_machine_learning_and_transformer-based_deep_learning_techniques/links/676424457784cf161e0b5b83/Extracting-knowledge-from-polymorphic-textual-data-using-graph-based-machine-learning-and-transformer-based-deep-learning-techniques.pdf"]}
{"year":"2024","title":"Extracting Large-Scale Multimodal Datasets From Web Archives","authors":["T Brummerloh"],"snippet":"… In this research, Common Crawl's WARC files are utilized to create a largescale multimodal dataset of text-image pairs. Two Python scripts, formed the core pipeline for extracting data that could be used for training a model to recognize alt tags and …","url":["https://downloads.webis.de/theses/papers/brummerloh_2024.pdf"]}
{"year":"2024","title":"Factuality of Large Language Models in the Year 2024","authors":["Y Wang, M Wang, MA Manzoor, G Georgiev, RJ Das… - arXiv preprint arXiv …, 2024"],"snippet":"Large language models (LLMs), especially when instruction-tuned for chat, have become part of our daily lives, freeing people from the process of searching, extracting, and integrating information from multiple sources by offering a …","url":["https://arxiv.org/pdf/2402.02420"]}
{"year":"2024","title":"Factuality of Large Language Models: A Survey","authors":["Y Wang, M Wang, MA Manzoor, F Liu, G Georgiev… - Proceedings of the 2024 …, 2024"],"snippet":"Large language models (LLMs), especially when instruction-tuned for chat, have become part of our daily lives, freeing people from the process of searching, extracting, and integrating information from multiple sources by offering a …","url":["https://aclanthology.org/2024.emnlp-main.1088.pdf"]}
{"year":"2024","title":"Fair Compensation for Copyrighted Data Used in AI training","authors":["AC Della Giustina"],"snippet":"… LAION sources its data from Common Crawl,106 a nonprofit organization that collects data from the web, creating extensive archives and datasets. Despite … Common Crawl is a nonprofit organization systematically exploring the web …","url":["http://arno.uvt.nl/show.cgi?fid=176944"]}
{"year":"2024","title":"FairDeDup: Detecting and Mitigating Vision-Language Fairness Disparities in Semantic Dataset Deduplication","authors":["E Slyman, S Lee, S Cohen, K Kafle - arXiv preprint arXiv:2404.16123, 2024"],"snippet":"Recent dataset deduplication techniques have demonstrated that content-aware dataset pruning can dramatically reduce the cost of training Vision-Language Pretrained (VLP) models without significant performance losses compared to …","url":["https://arxiv.org/pdf/2404.16123"]}
{"year":"2024","title":"Fairness and Bias in Multimodal AI: A Survey","authors":["T Adewumi, L Alkhaled, N Gurung, G van Boven… - arXiv preprint arXiv …, 2024"],"snippet":"The importance of addressing fairness and bias in artificial intelligence (AI) systems cannot be over-emphasized. Mainstream media has been awashed with news of incidents around stereotypes and bias in many of these systems in recent years. In …","url":["https://arxiv.org/pdf/2406.19097"]}
{"year":"2024","title":"Faithfulness of Natural Language Generation","authors":["P Schmidtová - Proceedings of the 20th Workshop of Young …, 2024"],"snippet":"… With works examining the presence of datasets in CommonCrawl (Li et al., 2024), we cannot even be entirely sure that open-weight models … • Data contamination: to what extent should we examine and worry about dialogue datasets being contained …","url":["https://aclanthology.org/2024.yrrsds-1.8.pdf"]}
{"year":"2024","title":"Fake news detection in low-resource languages: A novel hybrid summarization approach","authors":["J Alghamdi, Y Lin, S Luo - Knowledge-Based Systems, 2024"],"snippet":"… Pre-training encompasses a vast dataset exceeding 2TB of CommonCrawl data. The overarching concept involves mapping any given language to a language-agnostic vector space, ensuring that inputs in various languages converge to corresponding …","url":["https://www.sciencedirect.com/science/article/pii/S0950705124005185"]}
{"year":"2024","title":"Fake News Detection Revisited: An Extensive Review of Theoretical Frameworks, Dataset Assessments, Model Constraints, and Forward-Looking Research Agendas …","authors":["S Harris, HJ Hadi, N Ahmad, MA Alshara - 2024"],"snippet":"The emergence and acceptance of digital technology have caused information pollution and an infodemic on Online Social Networks (OSNs), blogs, and online websites. The malicious broadcast of illegal, objectionable and misleading content …","url":["https://www.researchgate.net/profile/Sheetal-Harris-3/publication/385589013_Fake_News_Detection_Revisited_An_Extensive_Review_of_Theoretical_Frameworks_Dataset_Assessments_Model_Constraints_and_Forward-Looking_Research_Agendas/links/672b9725ecbbde716b5c2418/Fake-News-Detection-Revisited-An-Extensive-Review-of-Theoretical-Frameworks-Dataset-Assessments-Model-Constraints-and-Forward-Looking-Research-Agendas.pdf"]}
{"year":"2024","title":"Falcon Mamba: The First Competitive Attention-free 7B Language Model","authors":["J Zuo, M Velikanov, DE Rhaiem, I Chahed, Y Belkada… - arXiv preprint arXiv …, 2024"],"snippet":"In this technical report, we present Falcon Mamba 7B, a new base large language model based on the novel Mamba architecture. Falcon Mamba 7B is trained on 5.8 trillion tokens with carefully selected data mixtures. As a pure Mamba-based model …","url":["https://arxiv.org/pdf/2410.05355"]}
{"year":"2024","title":"Falcon-UI: Understanding GUI Before Following User Instructions","authors":["H Shen, C Liu, G Li, X Wang, Y Zhou, C Ma, X Ji - arXiv preprint arXiv:2412.09362, 2024"],"snippet":"… After downloading the raw data from Common Crawl, we filter out duplicates, unreachable URLs, and non-English, NSFW websites based on the main content of each page. We apply the puppeteer library2 to simulate a browser environment. To …","url":["https://arxiv.org/pdf/2412.09362"]}
{"year":"2024","title":"Falcon2-11B Technical Report","authors":["Q Malartic, NR Chowdhury, R Cojocaru, M Farooq… - arXiv preprint arXiv …, 2024"],"snippet":"We introduce Falcon2-11B, a foundation model trained on over five trillion tokens, and its multimodal counterpart, Falcon2-11B-vlm, which is a vision-to-text model. We report our findings during the training of the Falcon2-11B which follows a multi-stage …","url":["https://arxiv.org/pdf/2407.14885"]}
{"year":"2024","title":"False memories from nowhere: 2 humans falsely recognize words that are not attested in their vocabulary 3","authors":["D Gatti, M Petilli, M Marchetti, T Vecchi, G Mazzoni…"],"snippet":"Views and opinions expressed are however those of the author (s) only and do not 37 necessarily reflect those of the European Union or the European Research Council 38 Executive Agency. Neither the European Union nor the granting authority …","url":["https://osf.io/8um2f/download"]}
{"year":"2024","title":"Fast and Lightweight Distributed Suffix Array Construction--First Results","authors":["M Haag, F Kurpicz, P Sanders, M Schimek - arXiv preprint arXiv:2412.10160, 2024"],"snippet":"… CommonCrawl (CC). This input consists of websites crawled by the Common Crawl Project. We use the WET files, which contain only the … Furthermore, we removed the meta information added by the Commoncrawl corpus. We used the …","url":["https://arxiv.org/pdf/2412.10160"]}
{"year":"2024","title":"FastDraft: How to Train Your Draft","authors":["O Zafrir, I Margulis, D Shteyman, G Boudoukh - arXiv preprint arXiv:2411.11055, 2024"],"snippet":"Speculative Decoding has gained popularity as an effective technique for accelerating the auto-regressive inference process of Large Language Models (LLMs). However, Speculative Decoding entirely relies on the availability of efficient draft …","url":["https://arxiv.org/pdf/2411.11055"]}
{"year":"2024","title":"Feasibility of Big Data Analytics in Disaster Psychiatry: Impact of Seoul Itaewon Tragedy on Sentiment Distribution on Twitter","authors":["J Kim, M Ki, J Yang, C Na, J Kim, C Han - Social Science & Medicine, 2024"],"snippet":"Numerous studies have highlighted the significant impact of disasters on mental health, often leading to psychiatric disorders among affected individuals. Timely identification of disaster-related mental health problems is crucial to prevent long-term …","url":["https://www.sciencedirect.com/science/article/pii/S0277953624007305"]}
{"year":"2024","title":"Feature-augmented model for multilingual discourse relation classification","authors":["E Metheniti, C Braud, P Muller - Proceedings of the 5th Workshop on Computational …, 2024"],"snippet":"Discourse relation classification within a multilingual, cross-framework setting is a challenging task, and the best-performing systems so far have relied on monolingual and mono-framework approaches. In this paper, we introduce transformer-based …","url":["https://aclanthology.org/2024.codi-1.9.pdf"]}
{"year":"2024","title":"Federated learning for privacy-preserving depression detection with multilingual language models in social media posts","authors":["SS Khalil, NS Tawfik, M Spruit - Patterns, 2024"],"snippet":"The incidences of mental health illnesses, such as suicidal ideation and depression, are increasing, which highlights the urgent need for early detection methods. There is a growing interest in using natural language processing (NLP) models to analyze …","url":["https://www.cell.com/patterns/fulltext/S2666-3899(24)00105-3"]}
{"year":"2024","title":"Few shot clinical entity recognition in three languages: Masked language models outperform LLM prompting","authors":["M Naguib, X Tannier, A Névéol - arXiv preprint arXiv:2402.12801, 2024"],"snippet":"Large Language Models are becoming the go-to solution for many natural language processing tasks, including in specialized domains where their few-shot capacities are expected to yield high performance in low-resource settings. Herein, we aim to …","url":["https://arxiv.org/pdf/2402.12801"]}
{"year":"2024","title":"FicSim: An Ethically Constructed Dataset for Long-Context Semantic Similarity Comparison within Fiction","authors":["N Johnson, A Bertsch, E Strubell"],"snippet":"… We describe our processes for selecting text not included in CommonCrawl scrapes, for obtaining and maintaining author consent for the use of their works, and for constructing pairwise similarity measurements corresponding to different facets of …","url":["https://creativity-ai.github.io/assets/papers/21.pdf"]}
{"year":"2024","title":"Final Thoughts: Digital Humanities Looking at Generative AI","authors":["M Aguiar, S Araújo - Digital Humanities Looking at the World: Exploring …, 2024"],"snippet":"In this chapter, we examine generative artificial intelligence in the context of Digital Humanities. We commence by providing a concise overview of this technology and its prevalent models. Following that, we provide a brief survey of the existing …","url":["https://link.springer.com/chapter/10.1007/978-3-031-48941-9_28"]}
{"year":"2024","title":"Final Words","authors":["M McTear, M Ashurkina - Transforming Conversational AI: Exploring the Power …, 2024"],"snippet":"Conversational AI is a dynamic and fast moving field, and a lot has happened in the six months or so since we began writing this book. We have tried to ensure that what we have covered in the preceding chapters provides a sufficiently general and …","url":["https://link.springer.com/chapter/10.1007/979-8-8688-0110-5_10"]}
{"year":"2024","title":"Findings of the WMT24 general machine translation shared task: the LLM era is here but mt is not solved yet","authors":["T Kocmi, E Avramidis, R Bawden, O Bojar… - Proceedings of the Ninth …, 2024"],"snippet":"This overview paper presents the results of the General Machine Translation Task organised as part of the 2024 Conference on Machine Translation (WMT). In the general MT task, participants were asked to build machine translation systems for …","url":["https://www2.statmt.org/wmt24/pdf/2024.wmt-1.1.pdf"]}
{"year":"2024","title":"Fine grain emotion analysis in Spanish using linguistic features and transformers","authors":["A Salmerón-Ríos, JA García-Díaz, R Pan… - PeerJ Computer Science, 2024"],"snippet":"Mental health issues are a global concern, with a particular focus on the rise of depression. Depression affects millions of people worldwide and is a leading cause of suicide, particularly among young people. Recent surveys indicate an increase in …","url":["https://peerj.com/articles/cs-1992/"]}
{"year":"2024","title":"Fine Tuning LLM for Enterprise: Practical Guidelines and Recommendations","authors":["K VM, H Warrier, Y Gupta - arXiv preprint arXiv:2404.10779, 2024"],"snippet":"… The datasets are massive text corpus like Common crawl, The Pile and code repositories from Github. Further the model can be fine tuned for specific tasks using specialised datasets. One such series of datasets are called Instruction datasets like …","url":["https://arxiv.org/pdf/2404.10779"]}
{"year":"2024","title":"Fine Tuning LLMs for Low Resource Languages","authors":["S Joshi, MS Khan, A Dafe, K Singh, V Zope, T Jhamtani - 2024 5th International …, 2024"],"snippet":"Large Language Models (LLMs) hold immense potential, but their data hunger can limit its performance in processing languages with limited resources. This research study explores the techniques for fine-tuning LLMs specifically for low-resource …","url":["https://ieeexplore.ieee.org/abstract/document/10660753/"]}
{"year":"2024","title":"Fine tuning the large language pegasus model for dialogue summarization","authors":["Sarthak, V Rishiwal, P Yadav, M Yadav, S Gangwar… - International Journal of …, 2024"],"snippet":"Dialogue summarization, a subset of task-oriented Natural Language Processing (NLP), faces challenges in providing concise and informative summaries of conversational data, which is crucial for various real-world applications. This study optimizes the …","url":["https://link.springer.com/article/10.1007/s41870-024-02307-w"]}
{"year":"2024","title":"Fine-Tuned Large Language Models for Symptom Recognition from Spanish Clinical Text","authors":["MA Shaaban, A Akkasi, A Khan, M Komeili, M Yaqub - arXiv preprint arXiv …, 2024"],"snippet":"… XLM-RL (561M parameters) and XLM-RB (279M parameters) are multilingual masked language models, trained on a filtered CommonCrawl dataset of over two terabytes. We leverage BBS and BBES both pretrained on Spanish clinical data …","url":["https://arxiv.org/pdf/2401.15780"]}
{"year":"2024","title":"Fine-Tuned Understanding: Enhancing Social Bot Detection with Transformer-based Classification","authors":["A Sallah, S Agoujil, MA Wani, M Hammad… - IEEE Access, 2024"],"snippet":"… fined common crawl data, XLM-RoBERTa is purposefully crafted as a multilingual version of RoBERTa. The acronym \"XLM\" denotes its capabilities in crosslingual language modeling; 3… It is trained on 2.5 TB of freshly curated, clean …","url":["https://ieeexplore.ieee.org/iel8/6287639/6514899/10630818.pdf"]}
{"year":"2024","title":"Fine-tuning an open source chatbot to translate code from Python to Java using Qlora: translating for more energy efficient code","authors":["J Hakkarainen - 2024"],"snippet":"In recent years large language models (LLM) based tools have become more commonplace with ChatGPT being the precursor to many competing products such as Google Gemini. While the training and finetuning of LLMs has been mostly …","url":["https://lutpub.lut.fi/bitstream/handle/10024/168604/diplomityo_hakkarainen_joonas.pdf?sequence=1&isAllowed=y"]}
{"year":"2024","title":"FINE-TUNING BERT, DISTILBERT, XLM-ROBERTA AND UKR-ROBERTA MODELS FOR SENTIMENT ANALYSIS OF UKRAINIAN LANGUAGE REVIEWS","authors":["M Prytula - Machine learning"],"snippet":"… It is pre-trained on 2.5TB of filtered CommonCrawl data containing 100 languages. The architecture of the XLMRoBERTa base model consists of 12 layers, 12 attention heads with 768 dimensions, and a feed-forward network [19]. This model is trained …","url":["https://jai.in.ua/archive/2024/2024-2-7.pdf"]}
{"year":"2024","title":"Fine-tuning BERT-based Models for Negative Content Identification on Indonesian Tweets","authors":["AF Hidayatullah, K Kalinaki, MM Aslam, RY Zakari…"],"snippet":"Social media platforms like Twitter have become substantial sources of user-generated content, enabling people to easily express their emotions and opinions. However, this freedom has increased the spread of harmful content, such as abusive language …","url":["https://www.researchgate.net/profile/Wasswa-Shafik-2/publication/378272650_Fine-Tuning_BERT-Based_Models_for_Negative_Content_Identification_on_Indonesian_Tweets/links/65d17d8928b7720cecda923e/Fine-Tuning-BERT-Based-Models-for-Negative-Content-Identification-on-Indonesian-Tweets.pdf"]}
{"year":"2024","title":"Fine-tuning foundational models to code diagnoses from veterinary health records","authors":["MR Boguslav, A Kiehl, D Kott, GJ Strecker, T Webb… - arXiv preprint arXiv …, 2024"],"snippet":"Veterinary medical records represent a large data resource for application to veterinary and One Health clinical research efforts. Use of the data is limited by interoperability challenges including inconsistent data formats and data siloing …","url":["https://arxiv.org/pdf/2410.15186"]}
{"year":"2024","title":"Fine-tuning Large Language Models for Multigenerator, Multidomain, and Multilingual Machine-Generated Text Detection","authors":["F Xiong, T Markchom, Z Zheng, S Jung, V Ojha… - arXiv preprint arXiv …, 2024"],"snippet":"SemEval-2024 Task 8 introduces the challenge of identifying machine-generated texts from diverse Large Language Models (LLMs) in various languages and domains. The task comprises three subtasks: binary classification in monolingual …","url":["https://arxiv.org/pdf/2401.12326"]}
{"year":"2024","title":"Fine-tuning large language models: from accuracy enhancement to bias mitigation","authors":["A Lochab - 2024"],"snippet":"As the frontier of artificial intelligence (AI) continues to expand, Large Language Models (LLMs) have emerged as pivotal tools across a broad spectrum of applications. These sophisticated AI systems, powered by vast amounts of data and …","url":["https://rucore.libraries.rutgers.edu/rutgers-lib/72435/PDF/1/play/"]}
{"year":"2024","title":"FINETUNING COMMERCIAL LARGE LANGUAGE MODELS WITH LORA FOR ENHANCED ITALIAN LANGUAGE UNDERSTANDING","authors":["J Hartsuiker, P Torroni, AE Ziri, DF Alise, F Ruggeri"],"snippet":"The world of Artificial intelligence is booming, especially the fields of natural language processing (NLP) and Computer Vision (CV). Recently the chatGPT models from OpenAI have caused another shock-wave. This was a clear sign to the …","url":["https://amslaurea.unibo.it/30534/1/Hartsuiker,%20J.M.%20Master%20Thesis%20-%20Finetuning%20commercial%20Large%20Language%20Models%20with%20LoRA%20for%20enhanced%20Italian%20language%20understanding.pdf"]}
{"year":"2024","title":"Fineweb-Edu-Ar: Machine-translated Corpus to Support Arabic Small Language Models","authors":["S Alrashed, D Khizbullin, DR Pugh - arXiv preprint arXiv:2411.06402, 2024"],"snippet":"… In general, we see two ways to obtain the educational-grade Arabic language dataset: (1) translating the English FineWeb-Edu, and (2) adapting the FineWeb-Edu pipeline for Arabic with subsequent re-running it on CommonCrawl. One notable …","url":["https://arxiv.org/pdf/2411.06402"]}
{"year":"2024","title":"FineWeb-zhtw: Scalable Curation of Traditional Chinese Text Data from the Web","authors":["CW Lin, WH Hsieh, KX Guan, CJ Hsu, CC Kuo, CL Lai… - arXiv preprint arXiv …, 2024"],"snippet":"… We have implemented a comprehensive pipeline to process Common Crawl data, utilizing various filtering techniques at each stage. The process begins with extracting documents from WARC files. Then, filters mentioned in the sections above …","url":["https://arxiv.org/pdf/2411.16387"]}
{"year":"2024","title":"Finite State Automata on Multi-Word Units for Efficient Text-Mining","authors":["A Postiglione - Mathematics, 2024"],"snippet":"Text mining is crucial for analyzing unstructured and semi-structured textual documents. This paper introduces a fast and precise text mining method based on a finite automaton to extract knowledge domains. Unlike simple words, multi-word …","url":["https://www.mdpi.com/2227-7390/12/4/506/pdf"]}
{"year":"2024","title":"FinTral: A Family of GPT-4 Level Multimodal Financial Large Language Models","authors":["G Bhatia, EMB Nagoudi, H Cavusoglu… - arXiv preprint arXiv …, 2024"],"snippet":"We introduce FinTral, a suite of state-of-the-art multimodal large language models (LLMs) built upon the Mistral-7b model and tailored for financial analysis. FinTral integrates textual, numerical, tabular, and image data. We enhance FinTral with domain-specific …","url":["https://arxiv.org/pdf/2402.10986"]}
{"year":"2024","title":"Five questions and answers about artificial intelligence","authors":["A Prieto, B Prieto - arXiv preprint arXiv:2409.15903, 2024"],"snippet":"Rapid advances in Artificial Intelligence (AI) are generating much controversy in society, often without scientific basis. As occurred the development of other emerging technologies, such as the introduction of electricity in the early 20th century …","url":["https://arxiv.org/pdf/2409.15903"]}
{"year":"2024","title":"For Perception Tasks: The Cost of LLM Pretraining by Next-Token Prediction Outweigh its Benefits","authors":["R Balestriero, H Huang - NeurIPS 2024 Workshop: Self-Supervised Learning …"],"snippet":"We question the usefulness of next-token prediction pretraining onto Large Language Models (LLMs)' ability to solve perception tasks, eg, sentiment analysis, spam detection, or toxicity detection. In fact, while companies spend tremendous …","url":["https://openreview.net/pdf?id=wYGBWOjq1Q"]}
{"year":"2024","title":"Foregrounding Artist Opinions: A Survey Study on Transparency, Ownership, and Fairness in AI Generative Art","authors":["J Lovato, J Zimmerman, I Smith, P Dodds, J Karson - arXiv preprint arXiv:2401.15497, 2024"],"snippet":"Generative Artificial Intelligence (AI) tools are used to create art-like outputs and aid in the creative process. While these tools have potential benefits for artists, they also have the potential to harm the art workforce and infringe upon artistic and intellectual …","url":["https://arxiv.org/pdf/2401.15497"]}
{"year":"2024","title":"Foreign Influence by Authoritarian Governments: Introducing New Data and Evidence","authors":["J Springman, FS Adiguzel, MV Chaparro, ZR Lin… - 2024"],"snippet":"The third wave of democratization was accompanied by a spectacular decline in the international influence of authoritarian governments. Culminating with the collapse of the Soviet Union, the ascendance of advanced democracies resulted in pressure …","url":["https://jrspringman.github.io/files/rai_full_paper.pdf"]}
{"year":"2024","title":"Formal Mathematical Reasoning: A New Frontier in AI","authors":["K Yang, G Poesia, J He, W Li, K Lauter, S Chaudhuri… - arXiv preprint arXiv …, 2024"],"snippet":"AI for Mathematics (AI4Math) is not only intriguing intellectually but also crucial for AI-driven discovery in science, engineering, and beyond. Extensive efforts on AI4Math have mirrored techniques in NLP, in particular, training large language models on …","url":["https://arxiv.org/pdf/2412.16075"]}
{"year":"2024","title":"Fostering the Ecosystem of Open Neural Encoders for Portuguese with Albertina PT* Family","authors":["R Santos, J Rodrigues, L Gomes, J Silva, A Branco… - arXiv preprint arXiv …, 2024"],"snippet":"… The OSCAR subset for Portuguese we use is based on November/December 2022 version of Common Crawl, which is an automatic crawl from the web. Despite being a crawl, the final dataset is of relatively good quality due the filtering performed …","url":["https://arxiv.org/pdf/2403.01897"]}
{"year":"2024","title":"Foundation Models for Autonomous Robots in Unstructured Environments","authors":["H Naderi, A Shojaei - arXiv preprint arXiv:2407.14296, 2024"],"snippet":"Automating activities through robots in unstructured environments, such as construction sites, has been a long-standing desire. However, the high degree of unpredictable events in these settings has resulted in far less adoption compared to …","url":["https://arxiv.org/pdf/2407.14296"]}
{"year":"2024","title":"Foundational Large Language Models for Materials Research","authors":["V Mishra, S Singh, D Ahlawat, M Zaki, V Bihani… - arXiv preprint arXiv …, 2024"],"snippet":"Materials discovery and development are critical for addressing global challenges. Yet, the exponential growth in materials science literature comprising vast amounts of textual data has created significant bottlenecks in knowledge extraction, synthesis …","url":["https://arxiv.org/pdf/2412.09560"]}
{"year":"2024","title":"Foundational Segmentation Models and Clinical Data Mining Enable Accurate Computer Vision for Lung Cancer","authors":["NC Swinburne, CB Jackson, AM Pagano, JN Stember… - Journal of Imaging …, 2024"],"snippet":"This study aims to assess the effectiveness of integrating Segment Anything Model (SAM) and its variant MedSAM into the automated mining, object detection, and segmentation (MODS) methodology for developing robust lung cancer detection and …","url":["https://link.springer.com/article/10.1007/s10278-024-01304-6"]}
{"year":"2024","title":"FOX-1 TECHNICAL REPORT","authors":["Z Hu, J Zhang, R Pan, Z Xu, S Avestimehr, C He…"],"snippet":"… We selected the Common Crawl (CC) split from all four datasets, which occupies almost 5T of storage. The SlimPajama-CC ranges from 2019 to … half of the Common Crawl collection data to complete the first stage of pre-training. By initially …","url":["https://www.researchgate.net/profile/Zijian-Hu-2/publication/385619515_Fox-1_Technical_Report/links/672d76f477f274616d626f77/Fox-1-Technical-Report.pdf"]}
{"year":"2024","title":"Frequently asked questions on erectile dysfunction: evaluating artificial intelligence answers with expert mentorship","authors":["M Baturu, M Solakhan, TG Kazaz, O Bayrak - International Journal of Impotence …, 2024"],"snippet":"The present study assessed the accuracy of artificiaI intelligence-generated responses to frequently asked questions on erectile dysfunction. A cross-sectional analysis involved 56 erectile dysfunction-related questions searched on Google …","url":["https://www.nature.com/articles/s41443-024-00898-3"]}
{"year":"2024","title":"From Abstract Syntax to Natural Language Addressing Natural Language Generation Challenges in Arabic Using GFWordnet as Lexical Resources.","authors":["M Zarzoura - 2024"],"snippet":"This thesis explores the development and evaluation of Arabic natural language generation using the Grammatical Framework (GF) within GFPedia. GFPedia is a framework that generates multilingual content using predefined abstract syntax trees …","url":["https://gupea.ub.gu.se/bitstream/handle/2077/84379/From_abstract_syntax_to_natural_languag%20Mohamed%20Zarzoura.pdf?sequence=1&isAllowed=y"]}
{"year":"2024","title":"From archived web corpus to readable data for history research","authors":["S Gebeil, J Thièvre - The Routledge Companion to Transnational Web …, 2024"],"snippet":"… most referenced and most widely used in the community, notably by Common Crawl and ArchiveIt. The WAT format is specifically designed for … In alignment with the practices of Common Crawl and Archive-It (Lohndorf, 2023), our project adopts a …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=RLYyEQAAQBAJ&oi=fnd&pg=PA361&dq=commoncrawl&ots=ebVn40Yl74&sig=SnzreMcAP5sGdOFtAymNob1dsz4"]}
{"year":"2024","title":"From Bytes to Biases: Investigating the Cultural Self-Perception of Large Language Models","authors":["W Messner, T Greene, J Matalone - arXiv preprint arXiv:2312.17256, 2023"],"snippet":"Large language models (LLMs) are able to engage in natural-sounding conversations with humans, showcasing unprecedented capabilities for information retrieval and automated decision support. They have disrupted human-technology …","url":["https://arxiv.org/pdf/2312.17256"]}
{"year":"2024","title":"From Cosine Similarity to Likelihood Ratio: Coupling Representations From Machine Learning (and Other Sources) With Cognitive Models","authors":["GE Cox"],"snippet":"Modern machine learning models yield vector representations that capture similarity relations between complex items like text and images. These representations can help explain and predict how individuals respond to those items in particular tasks …","url":["https://osf.io/v7xuz/download"]}
{"year":"2024","title":"From Data Creator to Data Reuser: Distance Matters","authors":["CL Borgman, PT Groth - arXiv preprint arXiv:2402.07926, 2024"],"snippet":"… Common Crawl, launched in 2007, now spends roughly $200,000 per year to maintain petabytes of openly available web crawl data (Common Crawl, 2023; Roberts, 2023). The use of these data to train large language models has …","url":["https://arxiv.org/pdf/2402.07926"]}
{"year":"2024","title":"From Data Quality to Model Performance: Navigating the Landscape of Deep Learning Model Evaluation","authors":["M Akram, WH Moosa - Deep Learning for Multimedia Processing Applications, 2024"],"snippet":"Deep learning (DL) technologies have revolutionized the analysis of multimedia data, with natural language processing, visual data analytics, and audio recognition being just a few examples of multimedia applications that have effectively utilized DL. This …","url":["https://www.taylorfrancis.com/chapters/edit/10.1201/9781032646268-13/data-quality-model-performance-muhammad-akram-wajid-hassan-moosa-najiba"]}
{"year":"2024","title":"From Development to Dissemination: Social and Ethical Issues with Text-to-Image AI-Generated Art","authors":["SCY Ho"],"snippet":"… Model developed by the Computer Vision & Learning Group (CompVis) lab at Ludwig Maximilian University of Munich was trained with a subset of the LAION-5B dataset [6], comprising of about 2.3 billion CLIP-filtered image-text pairs by parsing …","url":["https://assets.pubpub.org/sv8awfz7/21682640391665.pdf"]}
{"year":"2024","title":"From Discrete to Continuous Classes: A Situational Analysis of Multilingual Web Registers with LLM Annotations","authors":["E Henriksson, A Myntti, S Hellström… - Proceedings of the 4th …, 2024"],"snippet":"In corpus linguistics, registers–language varieties suited to different contexts–have traditionally been defined by their situations of use, yet recent studies reveal significant situational variation within registers. Previous quantitative studies …","url":["https://aclanthology.org/2024.nlp4dh-1.30.pdf"]}
{"year":"2024","title":"From Enclosure to Foreclosure and Beyond: Opening AI's Totalizing Logic","authors":["K Schwerzmann"],"snippet":"This paper reframes the issue of appropriation, extraction, and dispossession through AI—an assemblage of machine learning models trained on big data—in terms of enclosure and foreclosure. While enclosures are the product of a well-studied …","url":["https://philpapers.org/archive/SCHFET-5.pdf"]}
{"year":"2024","title":"From Form (s) to Meaning: Probing the Semantic Depths of Language Models Using Multisense Consistency","authors":["X Ohmer, E Bruni, D Hupkes - arXiv preprint arXiv:2404.12145, 2024"],"snippet":"… We use the current common crawl statistics6 to compute an estimate of how low- or high-resource these languages are in web-based corpora. Of this corpus, English constitutes 46% of the data, German 5.8%, Italian 2.7%, Dutch 2.2%, and Swedish …","url":["https://arxiv.org/pdf/2404.12145"]}
{"year":"2024","title":"From GaLore to WeLore: How Low-Rank Weights Non-uniformly Emerge from Low-Rank Gradients","authors":["A Jaiswal, L Yin, Z Zhang, S Liu, J Zhao, Y Tian… - arXiv preprint arXiv …, 2024"],"snippet":"… The C4 dataset is a massive collection of Common Crawl’s web crawl corpus, meticulously filtered and cleaned to ensure high-quality language modeling and training. For downstream task finetuning of compressed models, we consider a good …","url":["https://arxiv.org/pdf/2407.11239"]}
{"year":"2024","title":"From general LLM to translation: How we dramatically improve translation quality using human evaluation data for LLM finetuning","authors":["D Elshin, N Karpachev, B Gruzdev, I Golovanov… - Proceedings of the Ninth …, 2024"],"snippet":"This paper describes Yandex submission to the WMT2024 General Translation Task. More specifically, we present a novel pipeline designed to build a strong paragraph-level translation engine with an emphasis on video subtitles domain. In particular, we …","url":["https://www2.statmt.org/wmt24/pdf/2024.wmt-1.17.pdf"]}
{"year":"2024","title":"From Graph Theory for Robust Deep Networks to Graph Learning for Multimodal Cancer Analysis","authors":["A Waqas - 2024"],"snippet":"This dissertation explores the intersection of graph theory and deep learning, focusing on enhancing the robustness of deep neural networks (DNNs) and applying these advancements to complex problems like cancer diagnosis and …","url":["https://search.proquest.com/openview/5ac988d46281e72d642326b668c25469/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
{"year":"2024","title":"From ML to LLM: Evaluating the Robustness of Phishing Webpage Detection Models against Adversarial Attacks","authors":["A Kulkarni, V Balachandran, DM Divakaran, T Das - arXiv preprint arXiv:2407.20361, 2024"],"snippet":"Phishing attacks attempt to deceive users into stealing sensitive information, posing a significant cybersecurity threat. Advances in machine learning (ML) and deep learning (DL) have led to the development of numerous phishing webpage detection …","url":["https://arxiv.org/pdf/2407.20361"]}
{"year":"2024","title":"From News to Summaries: Building a Hungarian Corpus for Extractive and Abstractive Summarization","authors":["B Barta, D Lakatos, A Nagy, MK Nyist, J Ács - arXiv preprint arXiv:2404.03555, 2024"],"snippet":"… We use the freely available Common Crawl dataset4 as a basis for constructing the corpus. It contains petabytes of crawled web pages from the past 25 years and it is available on Amazon S3 in WARC format. Retrieval and deduplication of the raw …","url":["https://arxiv.org/pdf/2404.03555"]}
{"year":"2024","title":"From Pixels to Prose: A Large Dataset of Dense Image Captions","authors":["V Singla, K Yue, S Paul, R Shirkavand… - arXiv preprint arXiv …, 2024"],"snippet":"Training large vision-language models requires extensive, high-quality image-text pairs. Existing web-scraped datasets, however, are noisy and lack detailed image descriptions. To bridge this gap, we introduce PixelProse, a comprehensive dataset …","url":["https://arxiv.org/pdf/2406.10328"]}
{"year":"2024","title":"FROM PIXELS TO PROSE: ALarge DATASET OF DENSE IMAGE CAPTIONS","authors":["AL DATASET"],"snippet":"Training large vision-language models requires extensive, high-quality image-text pairs. Existing web-scraped datasets, however, are noisy and lack detailed image descriptions. To bridge this gap, we introduce PixelProse, a comprehensive dataset …","url":["https://openreview.net/pdf?id=UwbX8KOZgK"]}
{"year":"2024","title":"From Populism to Platforms: Antitrust Law and the AI Revolution","authors":["V Menaldo"],"snippet":"This chapter, from my book manuscript “The Political Economy of the Fourth Industrial Revolution,” examines how changes to US antitrust law catalyzed the rise of digital platforms and the Artificial Intelligence (AI) Revolution. It traces the …","url":["https://www.researchgate.net/profile/Victor-Menaldo/publication/383751861_From_Populism_to_Platforms_Antitrust_Law_and_the_AI_Revolution/links/66d8f015b1606e24c2e1a668/From-Populism-to-Platforms-Antitrust-Law-and-the-AI-Revolution.pdf"]}
{"year":"2024","title":"From Rule-Based Models to Deep Learning Transformers Architectures for Natural Language Processing and Sign Language Translation Systems: Survey, Taxonomy …","authors":["N Shahin, L Ismail - arXiv preprint arXiv:2408.14825, 2024"],"snippet":"With the growing Deaf and Hard of Hearing population worldwide and the persistent shortage of certified sign language interpreters, there is a pressing need for an efficient, signs-driven, integrated end-to-end translation system, from sign to gloss to …","url":["https://arxiv.org/pdf/2408.14825"]}
{"year":"2024","title":"From Test-Taking to Test-Making: Examining LLM Authoring of Commonsense Assessment Items","authors":["M Roemmele, AS Gordon"],"snippet":"LLMs can now perform a variety of complex writing tasks. They also excel in answering questions pertaining to natural language inference and commonsense reasoning. Composing these questions is itself a skilled writing task, so in this paper …","url":["https://asgordon.github.io/publications/EMNLP2024.PDF"]}
{"year":"2024","title":"From Text to Transformation: A Comprehensive Review of Large Language Models' Versatility","authors":["P Kaur, GS Kashyap, A Kumar, MT Nafis, S Kumar… - arXiv preprint arXiv …, 2024"],"snippet":"This groundbreaking study explores the expanse of Large Language Models (LLMs), such as Generative Pre-Trained Transformer (GPT) and Bidirectional Encoder Representations from Transformers (BERT) across varied domains ranging from …","url":["https://arxiv.org/pdf/2402.16142"]}
{"year":"2024","title":"From'Showgirls' to'Performers': Fine-tuning with Gender-inclusive Language for Bias Reduction in LLMs","authors":["M Bartl, S Leavy - arXiv preprint arXiv:2407.04434, 2024"],"snippet":"Gender bias is not only prevalent in Large Language Models (LLMs) and their training data, but also firmly ingrained into the structural aspects of language itself. Therefore, adapting linguistic structures within LLM training data to promote gender-inclusivity …","url":["https://arxiv.org/pdf/2407.04434"]}
{"year":"2024","title":"Frozen or Fine-tuned? Analyzing Deep Learning Models and Training Strategies for Optimizing Big Five Personality Traits Prediction from Text","authors":["M Soleimani, HB Kashani - 2024 10th International Conference on Artificial …, 2024"],"snippet":"In today’s digital age, the comprehension and prediction of human personality traits have assumed paramount significance. This study embarks on the task of forecasting the Big Five personality traits through textual data, harnessing the …","url":["https://ieeexplore.ieee.org/abstract/document/10496606/"]}
{"year":"2024","title":"FuLG: 150B Romanian Corpus for Language Model Pretraining","authors":["VA Bădoiu, MV Dumitru, AM Gherghescu, A Agache… - arXiv preprint arXiv …, 2024"],"snippet":"… billion-token Romanian corpus extracted from CommonCrawl. We present our methodology for … , we delve into filtering Romanian content from CommonCrawl, documenting the process and … Second, we document the process of filtering data …","url":["https://arxiv.org/pdf/2407.13657"]}
{"year":"2024","title":"Fully Authentic Visual Question Answering Dataset from Online Communities","authors":["L Yuan, D Gurari"],"snippet":"Visual Question Answering (VQA) entails answering questions about images. We introduce the first VQA dataset in which all contents originate from an authentic use case. Sourced from online question answering community forums, we call it …","url":["https://link.springer.com/content/pdf/10.1007/978-3-031-73195-2_15.pdf"]}
{"year":"2024","title":"Fully Open Source Moxin-7B Technical Report","authors":["P Zhao, X Shen, Z Kong, Y Shen, SE Chang… - arXiv preprint arXiv …, 2024"],"snippet":"… First, resiliparse is employed to extract text from CommonCrawl. Second, deduplication is performed using MinHash [58] within a suffix array pipeline [59, 36] and near-duplicate Bloom filtering, which enhances the exact document and …","url":["https://arxiv.org/pdf/2412.06845"]}
{"year":"2024","title":"Fundus: A Simple-to-Use News Scraper Optimized for High Quality Extractions","authors":["M Dallabetta, C Dobberstein, A Breiding, A Akbik - arXiv preprint arXiv:2403.15279, 2024"],"snippet":"… Specifically, we support the CC-NEWS3 dataset provided by the COMMONCRAWL initiative. At the time of writing, this dataset comprises around 40 terabytes of WARC-formatted data, containing millions of news articles dating back …","url":["https://arxiv.org/pdf/2403.15279"]}
{"year":"2024","title":"Fusing Domain-Specific Content from Large Language Models into Knowledge Graphs for Enhanced Zero Shot Object State Classification","authors":["F Gouidis, K Papantoniou, KPT Patkos, A Argyros… - arXiv preprint arXiv …, 2024"],"snippet":"Domain-specific knowledge can significantly contribute to addressing a wide variety of vision tasks. However, the generation of such knowledge entails considerable human labor and time costs. This study investigates the potential of Large Language …","url":["https://arxiv.org/pdf/2403.12151"]}
{"year":"2024","title":"Fusion of Deep Learning with Advanced and Traditional Embeddings in Sentiment Analysis","authors":["K Kiran, PD Shenoy - 2024 IEEE 9th International Conference for …, 2024"],"snippet":"In todays changing landscape the abundance of unprocessed data plays a vital role. It is crucial to curate this dataset and conduct a thorough analysis of the sentiments it captures. The aim of this research study is to explore learning techniques such as Bi …","url":["https://ieeexplore.ieee.org/abstract/document/10543279/"]}
{"year":"2024","title":"Fusion of Knowledge: Enhancing AI Reasoning Through Language Models and Knowledge Graphs","authors":["KC Mavromatis - 2024"],"snippet":"Large Language Models (LLMs) and Knowledge Graphs (KGs) have rapidly emerged as important areas in Artificial Intelligence (AI). LLMs leverage vast amounts of unstructured text to understand and generate natural language. KGs are …","url":["https://search.proquest.com/openview/f8e8e582390e1325b07508c6bb8b33ff/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
{"year":"2024","title":"Fusion of Visual and Textual Data for Enhanced Semantic Representations","authors":["L Sterling, K Vale, A Martinez - 2024"],"snippet":"Generic text embeddings have demonstrated considerable success across a multitude of applications. However, these embeddings are typically derived by modeling the co-occurrence patterns within text-only corpora, which can limit their …","url":["https://www.preprints.org/manuscript/202409.2066/download/final_file"]}
{"year":"2024","title":"FuxiTranyu: A Multilingual Large Language Model Trained with Balanced Data","authors":["H Sun, R Jin, S Xu, L Pan, M Cui, J Dui, Y Lei, L Yang… - arXiv preprint arXiv …, 2024"],"snippet":"Large language models (LLMs) have demonstrated prowess in a wide range of tasks. However, many LLMs exhibit significant performance discrepancies between highand low-resource languages. To mitigate this challenge, we present FuxiTranyu, an …","url":["https://arxiv.org/pdf/2408.06273"]}
{"year":"2024","title":"Galactica's dis-assemblage: Meta's beta and the omega of post-human science","authors":["N Chartier-Edwards, E Grenier, V Goujon - AI & SOCIETY, 2024"],"snippet":"Released mid-November 2022, Galactica is a set of six large language models (LLMs) of different sizes (from 125 M to 120B parameters) designed by Meta AI to achieve the ultimate ambition of “a single neural network for powering scientific tasks” …","url":["https://link.springer.com/article/10.1007/s00146-024-02088-7"]}
{"year":"2024","title":"GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection","authors":["J Zhao, Z Zhang, B Chen, Z Wang, A Anandkumar… - arXiv preprint arXiv …, 2024"],"snippet":"Training Large Language Models (LLMs) presents significant memory challenges, predominantly due to the growing size of weights and optimizer states. Common memory-reduction approaches, such as low-rank adaptation (LoRA), add a trainable …","url":["https://arxiv.org/html/2403.03507v1"]}
{"year":"2024","title":"GAOKAO-Eval: Does high scores truly reflect strong capabilities in LLMs?","authors":["Z Lei, T Liang, H Hu, J Zhang, Y Zhou, Y Shao, L Li… - arXiv preprint arXiv …, 2024"],"snippet":"Large Language Models (LLMs) are commonly evaluated using human-crafted benchmarks, under the premise that higher scores implicitly reflect stronger human-like performance. However, there is growing concern that LLMs may ``game\" these …","url":["https://arxiv.org/pdf/2412.10056"]}
{"year":"2024","title":"Gauging Novelty in Crowdfunding Projects: A Theory-Driven Text Analysis Approach","authors":["Y Lin, W Boh - 2024"],"snippet":"The explosion of crowdfunding projects has called for new ways to screen for novel projects. Building on the multidimensional nature of novelty, we draw on the literature to propose two measures of project novelty that are theoretically sound and …","url":["https://aisel.aisnet.org/pacis2024/track03_ba/track03_ba/1/"]}
{"year":"2024","title":"GEB-1.3 B: Open Lightweight Large Language Model","authors":["J Wu, Y Zhu, L Shen, X Lu - arXiv preprint arXiv:2406.09900, 2024"],"snippet":"… Data Processing The Common Crawl dataset is crawled from the web and often suffers from quality issues, because of including garbled … Rule Cleaning First, we extract a Chinese corpus from the Common Crawl dataset, by applying specialized …","url":["https://arxiv.org/pdf/2406.09900"]}
{"year":"2024","title":"GemBode and PhiBode: Adapting Small Language Models to Brazilian Portuguese","authors":["GL Garcia, PH Paiola, E Garcia, JR Ribeiro Manesco… - Iberoamerican Congress on …, 2024"],"snippet":"… The Canarim model was obtained by pretraining an LLaMa2-7B model using the Portuguese subset of Common Crawl solely on the language modeling task. Conversely, Bode employs low-rank adaptation (LoRA) to fine-tune and improve the …","url":["https://link.springer.com/chapter/10.1007/978-3-031-76607-7_17"]}
{"year":"2024","title":"GenAI Advertising: Risks of Personalizing Ads with LLMs","authors":["BJ Tang, K Sun, NT Curran, F Schaub, KG Shin - arXiv preprint arXiv:2409.15436, 2024"],"snippet":"Recent advances in large language models have enabled the creation of highly effective chatbots, which may serve as a platform for targeted advertising. This paper investigates the risks of personalizing advertising in chatbots to their users. We …","url":["https://arxiv.org/pdf/2409.15436"]}
{"year":"2024","title":"GenDec: A robust generative Question-decomposition method for Multi-hop reasoning","authors":["J Wu, L Yang, Y Ji, W Huang, BF Karlsson, M Okumura - arXiv preprint arXiv …, 2024"],"snippet":"Multi-hop QA (MHQA) involves step-by-step reasoning to answer complex questions and find multiple relevant supporting facts. However, Existing large language models'(LLMs) reasoning ability in multi-hop question answering remains exploration, which is …","url":["https://arxiv.org/pdf/2402.11166"]}
{"year":"2024","title":"Gender Ambiguity of Chinese Names in the United States","authors":["M Yao - 2024"],"snippet":"… Using the GloVe word embeddings algorithm trained on Common Crawl—a standard English corpus of online text including 840 billion words, I extract associations between Chinese names and five dimensions of gender meanings …","url":["https://etd.ohiolink.edu/acprod/odb_etd/ws/send_file/send?accession=osu1722694309287983&disposition=inline"]}
{"year":"2024","title":"Gender Bias in Natural Gender Language and Grammatical Gender Language within Children's Literature","authors":["KMW Smolinski - 2024"],"snippet":"There has been much research on the connection between language and gender bias but there is little comparing natural gender language, grammatical gender language, and gender bias. This research is important because it can offer an …","url":["https://digitalcommons.liberty.edu/cgi/viewcontent.cgi?article=6353&context=doctoral"]}
{"year":"2024","title":"Gender Bias in Natural Language Processing and Computer Vision: A Comparative Survey","authors":["M Bartl, A Mandal, S Leavy, S Little - ACM Computing Surveys, 2024"],"snippet":"Taking an interdisciplinary approach to surveying issues around gender bias in textual and visual AI, we present literature on gender bias detection and mitigation in NLP, CV, as well as combined visual-linguistic models. We identify conceptual …","url":["https://dl.acm.org/doi/pdf/10.1145/3700438"]}
{"year":"2024","title":"Gender Identity and Representation in the Context of Economic Development in India","authors":["B Pandey - 2024"],"snippet":"… It is a large multi-lingual language model, trained on 2.5TB of filtered CommonCrawl data. It represents some of the most sophisticated pre-trained models prevalently being used in natural language processing for text classification …","url":["https://knowledge.uchicago.edu/record/11912/files/Pandey_Thesis_MACSSEcon.pdf"]}
{"year":"2024","title":"Gendered Grammar or Ingrained Bias? Exploring Gender Bias in Icelandic Language Models","authors":["SR Friðriksdóttir, H Einarsson - Proceedings of the 2024 Joint International …, 2024"],"snippet":"Large language models, trained on vast datasets, exhibit increased output quality in proportion to the amount of data that is used to train them. This data-driven learning process has brought forth a pressing issue where these models may not only reflect …","url":["https://aclanthology.org/2024.lrec-main.671.pdf"]}
{"year":"2024","title":"Gendered Language in Job Advertisements Relates to Gender Sorting in Public Labor Markets: A Multi-Source Analysis","authors":["M Sievert, D Vogel, M Döring"],"snippet":"Increasing gender diversity constitutes a desirable goal for policymakers and recruiters in public organizations. However, contemporary research lacks focus on gender sorting, referring to structural self-selection among job seekers in the public …","url":["https://osf.io/u6z5e/download"]}
{"year":"2024","title":"General OCR Theory: Towards OCR-2.0 via a Unified End-to-end Model","authors":["H Wei, C Liu, J Chen, J Wang, L Kong, Y Xu, Z Ge… - arXiv preprint arXiv …, 2024"],"snippet":"… For the document-level data, we first collect open-source PDF-style files from the Common Crawl and employ the Fitz Python package to extract corresponding dense text content. In such a process, we gain 1.2M full-page PDF-style image-text pairs …","url":["https://arxiv.org/pdf/2409.01704"]}
{"year":"2024","title":"Generating Apparel Images by Using Stable Diffusion with Prompt Recommendation","authors":["XZ Liu, HM Hung, LH Chen - 人工知能学会全国大会論文集 第 38 回 (2024), 2024"],"snippet":"Fashion is a profound expression of personal identity, style, and culture in daily life. Making oneself look attractive, which often equates to being fashionable or stylish, is always a priority for many people. In this paper, we proposed a clothing …","url":["https://www.jstage.jst.go.jp/article/pjsai/JSAI2024/0/JSAI2024_2Q4IS502/_pdf"]}
{"year":"2024","title":"Generating Character Lines in Four-Panel Manga","authors":["M Inaba - Proceedings of the 37th Pacific Asia Conference on …, 2023"],"snippet":"Automatic content generation based on natural language processing is an active research area, especially for story generation. Research on story generation has focused on generating consistent text pertaining to characters’ actions and events; …","url":["https://aclanthology.org/2023.paclic-1.34.pdf"]}
{"year":"2024","title":"Generating Interpretations of Policy Announcements","authors":["A Marfurt, A Thornton, D Sylvan, J Henderson - … of the 4th International Conference on …, 2024"],"snippet":"Recent advances in language modeling have focused on (potentially multiple-choice) question answering, open-ended generation, or math and coding problems. We look at a more nuanced task: the interpretation of statements of political actors. To this end …","url":["https://aclanthology.org/2024.nlp4dh-1.50.pdf"]}
{"year":"2024","title":"Generating Probabilistic Scenario Programs from Natural Language","authors":["K Elmaaroufi, D Shankar, A Cismaru… - arXiv preprint arXiv …, 2024"],"snippet":"… Most of these model’s are fine-tuned variants of a foundational model that was trained on a wider body of text such as Common Crawl. For instance Codex is ”a GPT language model fine-tuned on publicly available code from GitHub” and it’s …","url":["https://arxiv.org/pdf/2405.03709"]}
{"year":"2024","title":"Generation of API Documentation using Large Language Models–Towards Self-explaining APIs","authors":["Y Jorelle - 2024"],"snippet":"Application Programming Interfaces (APIs) play a crucial role in modern software development. They are key in not only in enabling software reuse and adaptation, which greatly increase productivity, but also in facilitating exploration of new …","url":["https://aaltodoc.aalto.fi/bitstreams/b56655a0-32c3-4c19-a816-5bddebf01a6e/download"]}
{"year":"2024","title":"Generative adversarial network-based phishing URL detection with variational autoencoder and transformer","authors":["JK Sasi, A Balakrishnan - Int J Artif Intell, 2024"],"snippet":"Phishing attacks pose a constant threat to online security, necessitating the development of efficient tools for identifying malicious URLs. In this article, we propose a novel approach to detect phishing URLs employing a generative …","url":["https://www.researchgate.net/profile/Jishnu-K-S/publication/380184574_Generative_adversarial_network-based_phishing_URL_detection_with_variational_autoencoder_and_transformer/links/66308f2b06ea3d0b7419acb6/Generative-adversarial-network-based-phishing-URL-detection-with-variational-autoencoder-and-transformer.pdf"]}
{"year":"2024","title":"Generative AI and Business: A Review and Research Agenda","authors":["J Woolley - Oxford Research Encyclopedia of Business and …, 2024"],"snippet":"Generative Artificial Intelligence (Generative AI or GenAI) is an emerging and fast-growing technology with important consequences for workers, businesses, and society. GenAI is a subset of Machine Learning, which is a branch of Artificial Intelligence (AI) …","url":["https://oxfordre.com/business/display/10.1093/acrefore/9780190224851.001.0001/acrefore-9780190224851-e-434"]}
{"year":"2024","title":"Generative AI and future education: a review, theoretical validation, and authors' perspective on challenges and solutions","authors":["WK Monib, A Qazi, RA Apong, MT Azizan, L De Silva… - PeerJ Computer Science, 2024"],"snippet":"Generative AI (Gen AI), exemplified by ChatGPT, has witnessed a remarkable surge in popularity recently. This cutting-edge technology demonstrates an exceptional ability to produce human-like responses and engage in natural language …","url":["https://peerj.com/articles/cs-2105/"]}
{"year":"2024","title":"Generative AI and Large Language Models for Cyber Security: All Insights You Need","authors":["MA Ferrag, F Alwahedi, A Battah, B Cherif, A Mechri… - arXiv preprint arXiv …, 2024"],"snippet":"This paper provides a comprehensive review of the future of cybersecurity through Generative AI and Large Language Models (LLMs). We explore LLM applications across various domains, including hardware design security, intrusion detection …","url":["https://arxiv.org/pdf/2405.12750"]}
{"year":"2024","title":"Generative AI and the Continuing Importance of Information Literacy","authors":["L Svoboda, J Dean - 2024"],"snippet":"GAI models are embedded in a variety of applications. These models are trained using existing information, which is then formatted and delivered within the context of the GAI application. Bias, misand disinformation, and ethical use of information …","url":["https://deepblue.lib.umich.edu/bitstream/handle/2027.42/192763/DeanSvoboda-GenAI-InfoLit-Final.pdf?sequence=1"]}
{"year":"2024","title":"Generative AI Application for Building Industry","authors":["H Wan, J Zhang, Y Chen, W Xu, F Feng - arXiv preprint arXiv:2410.01098, 2024"],"snippet":"This paper investigates the transformative potential of generative AI technologies, particularly large language models (LLMs), within the building industry. By leveraging these advanced AI tools, the study explores their application across key …","url":["https://arxiv.org/pdf/2410.01098"]}
{"year":"2024","title":"Generative AI as a New Platform for Applications Development","authors":["MA Cusumano, VF Farias, R Ramakrishnan - 2024"],"snippet":"… Earlier generations of foundation models trained on text scraped from public databases like Wikipedia and Common Crawl for the first ‘pre-training’ phase and human-created instruction–answer pairs for the ‘instruction tuning’ phase.58 Based …","url":["https://mit-genai.pubpub.org/pub/r8xcl5ol"]}
{"year":"2024","title":"Generative AI for Math: Part I--MathPile: A Billion-Token-Scale Pretraining Corpus for Math","authors":["Z Wang, R Xia, P Liu - arXiv preprint arXiv:2312.17120, 2023"],"snippet":"… expanse of Common Crawl snapshots, a venture we aim to pursue in our future work. … We provide a near-duplicate example found in Common Crawl, as shown in 2 (See Table 8 to … StackExchange that appeared in a document from Common …","url":["https://arxiv.org/pdf/2312.17120"]}
{"year":"2024","title":"Generative AI for Unmanned Vehicle Swarms: Challenges, Applications and Opportunities","authors":["G Liu, N Van Huynh, H Du, DT Hoang, D Niyato, K Zhu… - arXiv preprint arXiv …, 2024"],"snippet":"With recent advances in artificial intelligence (AI) and robotics, unmanned vehicle swarms have received great attention from both academia and industry due to their potential to provide services that are difficult and dangerous to perform by humans …","url":["https://arxiv.org/pdf/2402.18062"]}
{"year":"2024","title":"Generative AI from Theory to Practice: A Case Study of Financial Advice","authors":["AW Lo, J Ross - 2024"],"snippet":"We identify some of the most pressing issues facing the adoption of large language models (LLMs) in practical settings and propose a research agenda to reach the next technological inflection point in generative AI. We focus on three challenges …","url":["https://mit-genai.pubpub.org/pub/l89uu140"]}
{"year":"2024","title":"Generative AI in Education From the Perspective of Students, Educators, and Administrators","authors":["A Ghimire - 2024"],"snippet":"This research explores how advanced artificial intelligence (AI), like the technology that powers tools such as ChatGPT, is changing the way we teach and learn in schools and universities. Imagine AI helping to summarize thick legal documents …","url":["https://digitalcommons.usu.edu/cgi/viewcontent.cgi?article=1119&context=etd2023"]}
{"year":"2024","title":"Generative AI","authors":["A Ibrahim","WR Business, T Taulli"],"snippet":"After almost six years of study, earning two bachelor’s degrees and now completing this master’s, my student journey comes to an end with this thesis, for now. My time at TU Delft has been a journey of both intellectual growth and personal discovery …","url":["https://link.springer.com/content/pdf/10.1007/978-1-4842-9367-6.pdf","https://repository.tudelft.nl/file/File_f005f661-bad5-4dea-a8ec-7647ab02bd99"]}
{"year":"2024","title":"Generative AI, Plagiarism, and Copyright Infringement in Legal Documents","authors":["AB Cyphert - Minnesota Journal of Law, Science & Technology, 2024"],"snippet":"… OpenAI acknowledged in the GPT-3 research paper that GPT-3 was trained on the Common Crawl dataset, “which includes everything from traditional news sites like the New York Times to sites like Reddit.” Cyphert, supra note 1, at 407, citing Liz …","url":["https://scholarship.law.umn.edu/cgi/viewcontent.cgi?article=1564&context=mjlst"]}
{"year":"2024","title":"Generative AI-Augmented Decision-Making for Business Information Systems","authors":["E Kromidha, RM Davison - IFIP International Conference on Human Choice and …, 2024"],"snippet":"… This is only influenced by the data it has been trained on, and its users which is one of its main limitations as ChatGPT was trained on datasets like Wikipedia, BookCorpus for books, and Common Crawl for web content which are mainly in …","url":["https://link.springer.com/chapter/10.1007/978-3-031-67535-5_5"]}
{"year":"2024","title":"Generative AI-Based Text Generation Methods Using Pre-Trained GPT-2 Model","authors":["R Pandey, H Waghela, S Rakshit, A Rangari, A Singh… - arXiv preprint arXiv …, 2024"],"snippet":"This work delved into the realm of automatic text generation, exploring a variety of techniques ranging from traditional deterministic approaches to more modern stochastic methods. Through analysis of greedy search, beam search, top-k …","url":["https://arxiv.org/pdf/2404.01786"]}
{"year":"2024","title":"GENERATIVE AI-POWERED FRAMEWORK","authors":["K VAYADANDE - Deep Learning Model Optimization, Deployment and …, 2024"],"snippet":"Artificial intelligence (AI) tools encompass a diverse array of applications and software designed to simulate intelligent behavior, facilitate decision making, and automate tasks across various domains. These tools leverage artificial intelligence …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=0GIfEQAAQBAJ&oi=fnd&pg=PA311&dq=commoncrawl&ots=Sq5mZxIrq8&sig=Zan6O--inFbGZYWJEnZK3PEnwKE"]}
{"year":"2024","title":"Generative Artificial Intellegence (AI) in Pathology and Medicine: A Deeper Dive","authors":["HH Rashidi, J Pantanowitz, A Chamanzar, B Fennell… - Modern Pathology, 2024"],"snippet":"This review article builds upon the introductory piece in our seven-part series, delving deeper into the transformative potential of generative artificial intelligence (Gen AI) in pathology and medicine. The article explores the applications of Gen AI …","url":["https://www.sciencedirect.com/science/article/pii/S0893395224002679"]}
{"year":"2024","title":"Generative Artificial Intelligence (AI) for the Data Economy: Use Cases in Nursing","authors":["C Tang, Z Chen, J Ma - 2024"],"snippet":"… The core recent AIGC advances stem from training more sophisticated generative models on larger datasets; for example, while the main framework maintains the same as GPT-2, GPT-3’s pre-training data size grows from WebTex (38GB) to …","url":["https://womencourage.acm.org/2024/wp-content/uploads/2024/06/womencourage2024-earlyworks-paper13.pdf"]}
{"year":"2024","title":"GENERATIVE ARTIFICIAL INTELLIGENCE (AI) IN EDUCATION: A CROSS-NATIONAL SURVEY ON UNIVERSITY TEACHERS'PERCEPTIONS ON THE USE OF …","authors":["K Karan, W Bakina"],"snippet":"… A year and three months later, the GPT-3 emerged with the Common Crawl as the main source of its data. The current GPT-4 started in March 2023 with the “unpublished” data source (Wu et al., 2023, p. 1123). …","url":["https://end-educationconference.org/wp-content/uploads/2024/07/202401OP035.pdf"]}
{"year":"2024","title":"Generative Artificial Intelligence and Copyright in the Film and Media Industry","authors":["VA Oberting IV - Washington and Lee Law Review Online, 2024"],"snippet":"The development of generative artificial intelligence (“GAI” or “generative AI”) introduces compelling benefits and capabilities to filmmakers and artists, but also brings complications regarding copyright of creative works. The American film and …","url":["https://scholarlycommons.law.wlu.edu/cgi/viewcontent.cgi?article=1179&context=wlulr-online"]}
{"year":"2024","title":"generative artificial intelligence","authors":["AFJ Costa, FF Cebrian, LC dos Anjos, MS Guedes…","D Carnahan - Digital Health, AI and Generative AI in Healthcare: A …, 2025"],"snippet":"… An example of large databases available and used to train AI models24 is Common Crawl. This is a non-profit organization that regularly crawls and collects data on the web using crawlers, ie automated programs, with the aim of generating …","url":["https://dpo-india.com/Resources/Generative_Artificial_Intelligence_Details/Generative-Artificial-Intelligence-Brazil-ANPD.pdf","https://link.springer.com/chapter/10.1007/978-3-031-83526-1_5"]}
{"year":"2024","title":"Generative Artificial Intelligence-Guided User Studies: An Application for Air Taxi Services","authors":["S Xiao, J Li, T Fushimi, Y Ochiai - arXiv preprint arXiv:2406.12296, 2024"],"snippet":"User studies are crucial for meeting user needs. In user studies, real experimental scenarios and participants are constructed and recruited. However, emerging and unfamiliar studies face limitations, including safety concerns and iterative efficiency …","url":["https://arxiv.org/pdf/2406.12296"]}
{"year":"2024","title":"Generative Artificial Intelligence: Models, Benefits, Dangers and Detection of AI-Generated Text on Specialized Domains","authors":["IN Mitrou - 2024"],"snippet":"… However, Radford et al. found that a large amount of document within the hashed pages of Common Crawl was unintelligible. A new approach could be to simply use a curated subset of Common Crawl, but they also created a web scrape from Reddit …","url":["https://pergamos.lib.uoa.gr/uoa/dl/object/3393769/file.pdf"]}
{"year":"2024","title":"Generative Insights Unveiling AI's Evolution and Algorithms","authors":["D Elavarasi, MS Ramadevi, JK Jayabarathan… - … of Generative AI for …, 2025"],"snippet":"… LLMs are trained on massive datasets such as Common Crawl and the Pile. The terabytes of data comprising these datasets were extracted from billions of publicly accessible websites. On the other hand, Small language models are trained on …","url":["https://www.igi-global.com/chapter/generative-insights-unveiling-ais-evolution-and-algorithms/357133"]}
{"year":"2024","title":"Generative Knowledge Management for Financial Inclusion Through Financial Literacy: A Systematic Review.","authors":["S Vadari, C Malladi - IUP Journal of Knowledge Management, 2024"],"snippet":"… OpenAI utilized an openly available corpus of webpages called Common Crawl, which in turn derives from a bot that crawls the entire Internet. This Common Crawl dataset contains billions of webpages and is one of the colossal textual datasets …","url":["https://search.ebscohost.com/login.aspx?direct=true&profile=ehost&scope=site&authtype=crawler&jrnl=25834592&AN=175575074&h=sCel50fK50xEllhIJpNI7DkOR%2BVRtNQcL6GAPBohcUUqh69TZ2AXa6cLuU8G8cSdXlqrcR2ViJzZZ2Q1%2FABnIQ%3D%3D&crl=c"]}
{"year":"2024","title":"Generic Embedding-Based Lexicons for Transparent and Reproducible Text Scoring","authors":["C Moez - arXiv preprint arXiv:2411.00964, 2024"],"snippet":"… I use is trained on Common Crawl, a large collection of web-scraped text. (Please note that GloVe is also available in versions estimated on Common Crawl text, and on Twitter data). The two vocabularies are initially 400,000 English words in size (GloVe) …","url":["https://arxiv.org/pdf/2411.00964"]}
{"year":"2024","title":"Generics are puzzling. Can language models find the missing piece?","authors":["G Cilleruelo, E Allaway, B Haddow, A Birch - … of the 31st International Conference on …, 2025","GC Calderón, E Allaway, B Haddow, A Birch - arXiv preprint arXiv:2412.11318, 2024"],"snippet":"… DOLMA is a cleaner version of Common Crawl and may have been used in the training data for popular language models (eg, MISTRAL). Therefore, we include recent Reddit comments to validate our findings on data the models have not been …","url":["https://aclanthology.org/2025.coling-main.438.pdf","https://arxiv.org/pdf/2412.11318"]}
{"year":"2024","title":"GeniL: A Multilingual Dataset on Generalizing Language","authors":["AM Davani, S Gubbi, S Dev, S Dave, V Prabhakaran - arXiv preprint arXiv …, 2024"],"snippet":"… For each language, we queried the Multilingual Common Crawl (mC4) language corpus to collect naturally occurring sentences that contain both the terms in the tuples present in SGM. To ensure a diverse representation of different associations …","url":["https://arxiv.org/pdf/2404.05866"]}
{"year":"2024","title":"Geohumanities 2.0","authors":["M Böhlen - On the Logics of Planetary Computing"],"snippet":"The last chapter discusses why smaller AI systems are becoming increasingly important in AI. I look at existing foundation models in AI and discuss the unease many researchers express in the homogenization of AI due to monopolies on ever …","url":["https://www.taylorfrancis.com/chapters/edit/10.4324/9781003519690-9/geohumanities-2-0-marc-b%C3%B6hlen"]}
{"year":"2024","title":"German Text Embedding Clustering Benchmark","authors":["S Wehrli, B Arnrich, C Irrgang - arXiv preprint arXiv:2401.02709, 2024"],"snippet":"This work introduces a benchmark assessing the performance of clustering German text embeddings in different domains. This benchmark is driven by the increasing use of clustering neural text embeddings in tasks that require the grouping of texts (such …","url":["https://arxiv.org/pdf/2401.02709"]}
{"year":"2024","title":"GFWeb: Measuring the Great Firewall's Web Censorship at Scale","authors":["NP Hoang, J Dalek, M Crete-Nishihata, N Christin…"],"snippet":"… Aggregating the ranking information provided by the Tranco list [62] and the Common Crawl dataset [1], we analyze the popularity of the base censored domains discovered by GFWeb for HTTP(S) filters in comparison to the GFWatch (DNS filter) …","url":["https://www3.cs.stonybrook.edu/~mikepo/papers/gfweb.sec24.pdf"]}
{"year":"2024","title":"Ghost Sentence: A Tool for Everyday Users to Copyright Data from Large Language Models","authors":["S Zhao, L Zhu, R Quan, Y Yang - arXiv preprint arXiv:2403.15740, 2024"],"snippet":"Web user data plays a central role in the ecosystem of pre-trained large language models (LLMs) and their fine-tuned variants. Billions of data are crawled from the web and fed to LLMs. How can \\textit{\\textbf{everyday web users}} confirm if LLMs …","url":["https://arxiv.org/html/2403.15740v1"]}
{"year":"2024","title":"Global MMLU: Understanding and Addressing Cultural and Linguistic Biases in Multilingual Evaluation","authors":["S Singh, A Romanou, C Fourrier, DI Adelani, JG Ngui… - arXiv preprint arXiv …, 2024"],"snippet":"Cultural biases in multilingual datasets pose significant challenges for their effectiveness as global benchmarks. These biases stem not only from language but also from the cultural knowledge required to interpret questions, reducing the …","url":["https://arxiv.org/pdf/2412.03304"]}
{"year":"2024","title":"GlotCC: An Open Broad-Coverage CommonCrawl Corpus and Pipeline for Minority Languages","authors":["AH Kargaran, F Yvon, H Schütze - arXiv preprint arXiv:2410.23825, 2024"],"snippet":"… In this paper, we adopt the Ungoliant pipeline [3] for extracting text from CommonCrawl. To address the limitations of current LID models (hash collisions and limited language coverage), we develop a new LID model, GlotLID v3.0, an …","url":["https://arxiv.org/pdf/2410.23825"]}
{"year":"2024","title":"Goldfish: Monolingual Language Models for 350 Languages","authors":["TA Chang, C Arnett, Z Tu, BK Bergen - arXiv preprint arXiv:2408.10441, 2024"],"snippet":"For many low-resource languages, the only available language models are large multilingual models trained on many languages simultaneously. However, using FLORES perplexity as a metric, we find that these models perform worse than …","url":["https://arxiv.org/pdf/2408.10441"]}
{"year":"2024","title":"GPT‐3‐and DALL‐E‐Powered Applications: A Complete Survey","authors":["K Vayadande, CB Pednekar, PA Khune… - How Machine Learning is …, 2024"],"snippet":"In the new millennium, the advancement of language and image processing technologies has witnessed remarkable progress, and various applications have demonstrated promising results by utilizing sophisticated models such as GPT‐3 …","url":["https://onlinelibrary.wiley.com/doi/abs/10.1002/9781394214167.ch19"]}
{"year":"2024","title":"GPThingSim: A IoT Simulator Based GPT Models Over an Edge-Cloud Environments","authors":["MF Khalfi, MN Tabbiche - International Journal of Networked and Distributed …, 2025"],"snippet":"… It was trained on an even larger dataset, benefiting from sources such as Common Crawl and 3 billion Wikipedia tokens [4]. While GPT\\(-\\)3.5 (GPT Turbo) only accepted inputs in the form of text, GPT-4 can also receive and even interpret …","url":["https://link.springer.com/article/10.1007/s44227-024-00045-w"]}
{"year":"2024","title":"GPTs: Concerns, Limitations and (Some) Responses","authors":["M Frické"],"snippet":"… The ones of these that are large and containing substantial source material from the Internet (eg from Common Crawl) will have some harms of representation bias. Then, if the training data has bias then so too will LLMs. To address this, there seem …","url":["https://ischool.arizona.edu/sites/ischool.arizona.edu/files/2024-04/Fricke%CC%81%20Information%20on%20Tap.pdf"]}
{"year":"2024","title":"Grammatical Redundancy in Scales: Using the “ConGRe” Process to Create Better Measures","authors":["L Alley, I Kadolkar, A Gupta, JM Cortina, KP Winsler - Journal of Management, 2024"],"snippet":"As theoretical models become more complex, there is more pressure to use less time-consuming methods generally, and shorter scales specifically. Although reliability is related to scale length, reliability cutoffs are easily met, even in very short scales, by writing or …","url":["https://journals.sagepub.com/doi/abs/10.1177/01492063241291542"]}
{"year":"2024","title":"Grammatical versus Spelling Error Correction: An Investigation into the Responsiveness of Transformer-Based Language Models Using BART and MarianMT","authors":["R Raju, PB Pati, SA Gandheesh, GS Sannala… - Journal of Information & …, 2024"],"snippet":"Text continues to remain a relevant form of representation for information. Text documents are created either in digital native platforms or through the conversion of other media files such as images and speech. While the digital native text is …","url":["https://www.worldscientific.com/doi/abs/10.1142/S0219649224500370"]}
{"year":"2024","title":"Grammatical vs Spelling Error Correction: An Investigation into the Responsiveness of Transformer-based Language Models using BART and MarianMT","authors":["R Raju, PB Pati, SA Gandheesh, GS Sannala, S KS - arXiv preprint arXiv:2403.16655, 2024"],"snippet":"… C4 Dataset is an Open-Source dataset obtained with Common Crawl web scrape [30]. This dataset contains millions of collected sentences along with their target sentences. The collected statements, referred to as input sentences in this work …","url":["https://arxiv.org/pdf/2403.16655"]}
{"year":"2024","title":"GRANITE 3.0 LANGUAGE MODELS","authors":["IBM Granite Team"],"snippet":"This report presents Granite 3.0, a new set of lightweight, state-of-the-art, open foundation models ranging in scale from 400 million to 8 billion active parameters. Equipped with native support of multilingual, coding, function calling, and strong …","url":["https://www.rivista.ai/wp-content/uploads/2024/10/paper-1.pdf"]}
{"year":"2024","title":"Granite Code Models: A Family of Open Foundation Models for Code Intelligence","authors":["M Mishra, M Stallone, G Zhang, Y Shen, A Prasad… - arXiv preprint arXiv …, 2024"],"snippet":"Large Language Models (LLMs) trained on code are revolutionizing the software development process. Increasingly, code LLMs are being integrated into software development environments to improve the productivity of human programmers, and …","url":["https://arxiv.org/pdf/2405.04324"]}
{"year":"2024","title":"Granularity is crucial when applying differential privacy to text: An investigation for neural machine translation","authors":["DNL Vu, T Igamberdiev, I Habernal - arXiv preprint arXiv:2407.18789, 2024"],"snippet":"… The computation of b is carried out using Common Crawl11 monolingual datasets. For each language and contextual embedding model, one million candidate-reference pairs are created by grouping two random sentences. Due to the random pairing …","url":["https://arxiv.org/pdf/2407.18789"]}
{"year":"2024","title":"Graph-Based Captioning: Enhancing Visual Descriptions by Interconnecting Region Captions","authors":["YG Hsieh, CY Hsieh, SY Yeh, L Béthune, HP Ansari… - arXiv preprint arXiv …, 2024"],"snippet":"… In a similar vein, Meta-CLIP [68] reproduces the processing of the seminal CLIP paper [50] on a subset of the Common Crawl dataset, … to filter data and remove duplicates, while DFN [17] uses filtering networks trained on high quality data to …","url":["https://arxiv.org/pdf/2407.06723"]}
{"year":"2024","title":"Grass: Compute Efficient Low-Memory LLM Training with Structured Sparse Gradients","authors":["A Muhamed, O Li, D Woodruff, M Diab, V Smith - arXiv preprint arXiv:2406.17660, 2024"],"snippet":"Large language model (LLM) training and finetuning are often bottlenecked by limited GPU memory. While existing projection-based optimization methods address this by projecting gradients into a lower-dimensional subspace to reduce optimizer …","url":["https://arxiv.org/pdf/2406.17660"]}
{"year":"2024","title":"GreekT5: Sequence-to-Sequence Models for Greek News Summarization","authors":["N Giarelis, C Mastrokostas, N Karacapilidis - IFIP International Conference on …, 2024"],"snippet":"… mBART was pre-trained for multiple languages using the CC25 dataset [15], which contains documents from 25 different languages from Common Crawl. The authors have also published an updated mBART model, which supports 50 natural …","url":["https://link.springer.com/chapter/10.1007/978-3-031-63215-0_5"]}
{"year":"2024","title":"Ground Every Sentence: Improving Retrieval-Augmented LLMs with Interleaved Reference-Claim Generation","authors":["S Xia, X Wang, J Liang, Y Zhang, W Zhou, J Deng, F Yu… - arXiv preprint arXiv …, 2024"],"snippet":"Retrieval-Augmented Generation (RAG) has been widely adopted to enhance Large Language Models (LLMs) in knowledge-intensive tasks. Recently, Attributed Text Generation (ATG) has attracted growing attention, which provides citations to …","url":["https://arxiv.org/pdf/2407.01796"]}
{"year":"2024","title":"Grounded Content Automation: Generation and Verification of Wikipedia in Low-Resouce languages.","authors":["S SHIVANSH - 2024"],"snippet":"In this thesis, we work towards improving the representation of low-resource languages in the digital world by easing the access and participation of these communities to reliable information hubs like Wikipedia. Although the internet has …","url":["https://web2py.iiit.ac.in/research_centres/publications/download/mastersthesis.pdf.8720b84f976e3c95.5f5f7372632e706466.pdf"]}
{"year":"2024","title":"Grounding Language in Images and Videos","authors":["A Sadhu - 2024"],"snippet":"While machine learning research has traditionally explored image, video and text understanding as separate fields, the surge in multi-modal content in today’s digital landscape underscores the importance of computation models that adeptly navigate …","url":["https://search.proquest.com/openview/bb7957834f5a8985e5befdaa711be7b0/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
{"year":"2024","title":"Growing Smaller Language Models Using Knowledge Distillation from Larger Models","authors":["M Featherstone, E Cuthbertson, D Appleyard, S Gittins"],"snippet":"… Publicly available datasets, such as The Pile and Common Crawl, were employed to ensure a comprehensive and representative sample of language usage across various domains. Data preprocessing involved several crucial steps …","url":["https://osf.io/54p96/download"]}
{"year":"2024","title":"Hacker News new| past| comments| ask| show| jobs| submit login","authors":["I also just had a GPTism"],"snippet":"I don't think these dichotomies in quality are going to go away. It's the exact same thing in every neural net domain. Self driving is probably the most sophisticated domain besides chat, and there too it's the exact same problem. They can drive a …","url":["https://news.ycombinator.com/item?id=36012360"]}
{"year":"2024","title":"Hallucinating (or poorly fed) LLMs? The problem of data accuracy","authors":["E Stringhi - i-lex, 2023"],"snippet":"… This is the case of “Common Crawl”, which consists in a massive collection of web pages and … To give a picture, the Common Crawl dataset constitutes nearly a trillion words. … were publicly available online and memorised in the Common …","url":["https://i-lex.unibo.it/article/download/18877/17434"]}
{"year":"2024","title":"Handling imbalanced textual data: an attention-based data augmentation approach","authors":["AK Sah, M Abulaish - International Journal of Data Science and Analytics, 2024"],"snippet":"In this paper, we present an attention-based data augmentation (ADA) approach to address the issue of poor performance of classification algorithms on imbalanced text datasets. The proposed approach begins by ranking the vocabulary of the …","url":["https://link.springer.com/article/10.1007/s41060-024-00674-y"]}
{"year":"2024","title":"Handwritten Text Recognition for Historical Documents using Visual Language Models and GANs","authors":["ST Aguilar - 2024"],"snippet":"In this study, we focus on Handwriting Text Recognition (HTR) on Medieval and Early Modern documentary manuscripts (10th-16th centuries) using Vision Language models (VLM). We leverage the TrOCR architecture and integrate domain-specific …","url":["https://hal.science/hal-04716654/document"]}
{"year":"2024","title":"Harder Tasks Need More Experts: Dynamic Routing in MoE Models","authors":["Q Huang, Z An, N Zhuang, M Tao, C Zhang, Y Jin, K Xu… - arXiv preprint arXiv …, 2024"],"snippet":"In this paper, we introduce a novel dynamic expert selection framework for Mixture of Experts (MoE) models, aiming to enhance computational efficiency and model performance by adjusting the number of activated experts based on input difficulty …","url":["https://arxiv.org/html/2403.07652v1"]}
{"year":"2024","title":"Hardware Phi-1.5 B: A Large Language Model Encodes Hardware Domain Specific Knowledge","authors":["W Fu, S Li, Y Zhao, H Ma, R Dutta, X Zhang, K Yang…"],"snippet":"… The first segment includes data from specialized platforms such as Arxiv , Books, Wikipedia, and StackExchange; the second segment is derived from broader internet content via CommonCrawl and C4. Table II provides a comprehensive …","url":["https://ece.k-state.edu/research/hardware-security/papers/ASP_DAC_PreTrainLM_2024_CR.pdf"]}
{"year":"2024","title":"Harmony in the Australian Domain Space","authors":["X Gong, PX McCarthy, MA Rizoiu, P Boldi - arXiv preprint arXiv:2404.10006, 2024"],"snippet":"… Though not focused on localized networks, the extensive and all-encompassing web graph from Common Crawl utilized in our study enables the extraction of implicit information on a broader scale. … We utilize the datasets mainly from …","url":["https://arxiv.org/pdf/2404.10006"]}
{"year":"2024","title":"Harnessing AI for Writing Development: Exploring Emerging Multilinguals' ChatGPT Usage Patterns","authors":["S Kim - 2024"],"snippet":"Since the release of advanced Large Language Models (LLMs) like ChatGPT in the winter of 2022, educators have been challenged to integrate AI in educational contexts without adequate preparation. This multimethod study aims to provide …","url":["https://etd.ohiolink.edu/acprod/odb_etd/ws/send_file/send?accession=osu1732498316837348&disposition=inline"]}
{"year":"2024","title":"Harnessing Artificial Intelligence in Bariatric Surgery: Comparative Analysis of ChatGPT-4, Bing, and Bard in Generating Clinician-Level Bariatric Surgery …","authors":["Y Lee, T Shin, L Tessier, A Javidan, J Jung, D Hong… - Surgery for Obesity and Related …"],"snippet":"Background The formulation of clinical recommendations pertaining to bariatric surgery is essential in guiding healthcare professionals. However, the extensive and continuously evolving body of literature in bariatric surgery presents considerable …","url":["https://www.soard.org/article/S1550-7289(24)00118-7/fulltext"]}
{"year":"2024","title":"Harnessing generative AI for overcoming labeled data challenges in social media NLP","authors":["CR Liyanage - 2023"],"snippet":"With the introduction of Transformers and Large Language Models, the field of NLP has significantly evolved. Generative AI, a prominent transformer-based technology for crafting human-like content, has proven powerful skills across numerous NLP …","url":["https://knowledgecommons.lakeheadu.ca/bitstream/handle/2453/5275/LiyanageC2023m-1a.pdf?sequence=1&isAllowed=y"]}
{"year":"2024","title":"Harnessing Small AI Model Collaboration and Debate Mechanisms in 6G Networks: Distributed Architectures and Layered Privacy Protection","authors":["C Han, T Yang, X Sun, Z Cui - ICC 2024-IEEE International Conference on …, 2024"],"snippet":"… was used for classification tasks, while OpenSubtitles and CommonCrawl were used for text classification tasks. Our primary evaluation metrics revolve around model accuracy, convergence speed, and computational and communication …","url":["https://ieeexplore.ieee.org/abstract/document/10622972/"]}
{"year":"2024","title":"Harnessing the Intrinsic Knowledge of Pretrained Language Models for Challenging Text Classification Settings","authors":["L Gao - arXiv preprint arXiv:2408.15650, 2024"],"snippet":"… For features that require embedding words, we use the 300-dimensional GloVe word embeddings [100] pretrained on the 42 billion token Common Crawl corpus. The GloVe embeddings are provided in decreasing order by frequency, and some …","url":["https://arxiv.org/pdf/2408.15650"]}
{"year":"2024","title":"Harnessing the Power of Language Models for Intelligent Digital Health Services","authors":["S Garima, M Swapnil, S Shashank - 2024 ITU Kaleidoscope: Innovation and Digital …, 2024"],"snippet":"This research proposes a novel framework that integrates state-of-the-art large language models (LLMs) with curated medical knowledge bases to enable personalized, reliable, and user-centric digital health services. The architecture …","url":["https://ieeexplore.ieee.org/abstract/document/10772761/"]}
{"year":"2024","title":"Harnessing the Power of Metadata for Enhanced Question Retrieval in Community Question Answering","authors":["S Ghasemi, A Shakery - IEEE Access, 2024"],"snippet":"… GPT-3 was trained on an open source dataset called ‘CommonCrawl’ and other texts from OpenAI such as Wikipedia entries. GPT-4 is the newest version of OpenAI’s language model systems. In this article, we fine-tune GPT-2 and GPT-3 pretrained …","url":["https://ieeexplore.ieee.org/iel7/6287639/10380310/10525684.pdf"]}
{"year":"2024","title":"Harnessing Transfer Learning from Swahili: Advancing Solutions for Comorian Dialects","authors":["NA Mohamed, Z Erraji, A Bahafid, I Benelallam - arXiv preprint arXiv:2412.12143, 2024"],"snippet":"… This model is trained on mC46, a multilingual dataset comprising texts in 101 languages sourced from CommonCrawl. mT5 excels across various NLP tasks, demonstrating state-of-the-art performance on multiple benchmark datasets. A …","url":["https://arxiv.org/pdf/2412.12143"]}
{"year":"2024","title":"Harnessing Webpage UIs for Text-Rich Visual Understanding","authors":["J Liu, T Ou, Y Song, Y Qu, W Lam, C Xiong, W Chen… - arXiv preprint arXiv …, 2024"],"snippet":"Text-rich visual understanding-the ability to process environments where dense textual content is integrated with visuals-is crucial for multimodal large language models (MLLMs) to interact effectively with structured environments. To enhance this …","url":["https://arxiv.org/pdf/2410.13824"]}
{"year":"2024","title":"Hate speech detection in low-resourced Indian languages: An analysis of transformer-based monolingual and multilingual models with cross-lingual experiments","authors":["K Ghosh, A Senapati - Natural Language Processing"],"snippet":"Warning: This paper is based on hate speech detection and may contain examples of abusive/ offensive phrases.Cyberbullying, online harassment, etc., via offensive comments are pervasive across different social media platforms like ™Twitter, ™Facebook …","url":["https://www.cambridge.org/core/services/aop-cambridge-core/content/view/BEAEA3C0B81561D7B52E097D67A87A48/S2977042424000281a.pdf/hate-speech-detection-in-low-resourced-indian-languages-an-analysis-of-transformer-based-monolingual-and-multilingual-models-with-cross-lingual-experiments.pdf"]}
{"year":"2024","title":"HCI International 2024 Posters: 26th International Conference on Human-Computer Interaction, HCII 2024, Washington, DC, USA, June 29–July 4, 2024, Proceedings …","authors":["C Stephanidis - 2024"],"snippet":"Preliminary scientific results, professional news, or work in progress, described in the form of short research papers (4–11 pages long), constitute a popular submission type among the International Conference on Human-Computer …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=aMULEQAAQBAJ&oi=fnd&pg=PR5&dq=commoncrawl&ots=hRNpPdcSEp&sig=R0smc7pGlEGxpECYA1HDV-wXEBA"]}
{"year":"2024","title":"HDeFC: Hierarchical Secure Fuzzy Deduplication Based on Fog Computing","authors":["Z Tang, S Zeng, S Han, J Liu, M He - IEEE Internet of Things Journal, 2024"],"snippet":"Secure deduplication not only optimizes cloud storage but also prevents data leakage. However, traditional schemes are with high computation and communication costs to deal with large-scale multimedia data. To address this …","url":["https://ieeexplore.ieee.org/abstract/document/10816493/"]}
{"year":"2024","title":"Headline Generation for Indian Languages","authors":["L MADASU - 2024"],"snippet":"… mT5: We conducted experiments on our dataset by fine-tuning the pre-trained mT5 [35] model, a multilingual variant of T5 [25], which was originally trained on the common crawl dataset, encompassing 101 languages. We use mT5-small model for …","url":["https://web2py.iiit.ac.in/research_centres/publications/download/mastersthesis.pdf.bf953219e4899a8e.4c6f6b6573684d61646173755f4d535f5468657369735f46696e616c2e706466.pdf"]}
{"year":"2024","title":"Health Misinformation in Social Networks: A Survey of IT Approaches","authors":["V Papanikou, P Papadakos, T Karamanidou… - arXiv preprint arXiv …, 2024"],"snippet":"In this paper, we present a comprehensive survey on the pervasive issue of medical misinformation in social networks from the perspective of information technology. The survey aims at providing a systematic review of related research and helping …","url":["https://arxiv.org/pdf/2410.18670"]}
{"year":"2024","title":"HGT: Leveraging Heterogeneous Graph-enhanced Large Language Models for Few-shot Complex Table Understanding","authors":["R Jin, Y Li, G Qi, N Hu, YF Li, J Chen, J Wang, Y Chen… - arXiv preprint arXiv …, 2024"],"snippet":"Table understanding (TU) has achieved promising advancements, but it faces the challenges of the scarcity of manually labeled tables and the presence of complex table structures.To address these challenges, we propose HGT, a framework with a …","url":["https://arxiv.org/pdf/2403.19723"]}
{"year":"2024","title":"Hidden Capabilities and Counterintuitive Limits in Large Language Models","authors":["P West - 2024"],"snippet":"As massive language models like GPT-4 dominate NLP and AI, extreme-scale has become a clear and frequent theme for success. My research envisions a world where alternative approaches, efficient methods working on small to medium-scale …","url":["https://search.proquest.com/openview/84c5eeef93d415759682c6d4863d0b8e/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
{"year":"2024","title":"Hierarchical Multimodal Pre-training for Visually Rich Webpage Understanding","authors":["H Xu, L Chen, Z Zhao, D Ma, R Cao, Z Zhu, K Yu - arXiv preprint arXiv:2402.18262, 2024"],"snippet":"… Common Crawl is a publicly available web crawl dataset that collects webpages from the internet. Instead of using the source code, we collect webpage links from Common Crawl. We traverse all links in a dataset snapshot 4 and categorize and …","url":["https://arxiv.org/pdf/2402.18262"]}
{"year":"2024","title":"High Performance Computing Web Search System Based on Computerized Big Data","authors":["J Ma - Informatica, 2024"],"snippet":"… In addition, this paper builds an experimental environment on Microsoft Azure cloud platform and tests it with Common Crawl dataset. Finally, this paper evaluates the performance of the system by three indicators: response time, accuracy and …","url":["https://www.informatica.si/index.php/informatica/article/view/6776"]}
{"year":"2024","title":"Higher Education's Generative Artificial Intelligence Paradox: The Meaning of Chatbot Mania","authors":["J Rudolph, MF Ismail, S Popenici - Journal of University Teaching and Learning …, 2024"],"snippet":"Higher education is currently under a significant transformation due to the emergence of generative artificial intelligence (GenAI) technologies, the hype surrounding GenAI and the increasing influence of educational technology business …","url":["https://www.researchgate.net/profile/Stefan-Popenici/publication/379956424_Higher_Education's_Generative_Artificial_Intelligence_Paradox_The_Meaning_of_Chatbot_Mania/links/66237af9f7d3fc2874703875/Higher-Educations-Generative-Artificial-Intelligence-Paradox-The-Meaning-of-Chatbot-Mania.pdf"]}
{"year":"2024","title":"HindiLLM: Large Language Model for Hindi","authors":["S Chouhan, SB Nath, A Dutta - International Conference on Pattern Recognition, 2025"],"snippet":"The advancements in the Large Language Model (LLM) have helped in solving several problems related to language processing. Most of the researches have focused on the English language only, because of its popularity and abundance on …","url":["https://link.springer.com/chapter/10.1007/978-3-031-78172-8_17"]}
{"year":"2024","title":"Historical Dutch Spelling Normalization with Pretrained Language Models","authors":["A Wolters, A Van Cranenburgh - Computational Linguistics in the Netherlands …, 2024"],"snippet":"… These texts are from the common crawl corpus, which contains petabytes of data scraped from the internet. Further pretraining on in-domain data can make the model more suited for the downstream task it will be finetuned for, and since our task …","url":["https://www.clinjournal.org/clinj/article/download/178/194"]}
{"year":"2024","title":"Historical German Text Normalization Using Type-and Token-Based Language Modeling","authors":["A Ehrmanntraut - arXiv preprint arXiv:2409.02841, 2024"],"snippet":"Historic variations of spelling poses a challenge for full-text search or natural language processing on historical digitized texts. To minimize the gap between the historic orthography and contemporary spelling, usually an automatic orthographic …","url":["https://arxiv.org/pdf/2409.02841"]}
{"year":"2024","title":"History, Development, and Principles of Large Language Models-An Introductory Survey","authors":["Z Chu, S Ni, Z Wang, X Feng, C Li, X Hu, R Xu, M Yang… - arXiv preprint arXiv …, 2024"],"snippet":"Language models serve as a cornerstone in natural language processing (NLP), utilizing mathematical methods to generalize language laws and knowledge for prediction and generation. Over extensive research spanning decades, language …","url":["https://arxiv.org/pdf/2402.06853"]}
{"year":"2024","title":"History, development, and principles of large language models: an introductory survey","authors":["Z Wang, Z Chu, TV Doan, S Ni, M Yang, W Zhang - AI and Ethics, 2024"],"snippet":"Abstract Language models serve as a cornerstone in natural language processing, utilizing mathematical methods to generalize language laws and knowledge for prediction and generation. Over extensive research spanning decades, language …","url":["https://link.springer.com/article/10.1007/s43681-024-00583-7"]}
{"year":"2024","title":"HJ-Ky-0.1: an Evaluation Dataset for Kyrgyz Word Embeddings","authors":["A Alekseev, G Kabaeva - arXiv preprint arXiv:2411.10724, 2024"],"snippet":"… Our experiments also showed that fastText embeddings trained on the Leipzig Corpus outperform those trained on CommonCrawl, highlighting the importance of clean, high-quality text data for training. These findings suggest that the HJ-Ky-0.1 …","url":["https://arxiv.org/pdf/2411.10724"]}
{"year":"2024","title":"HMoE: Heterogeneous Mixture of Experts for Language Modeling","authors":["A Wang, X Sun, R Xie, S Li, J Zhu, Z Yang, P Zhao… - arXiv preprint arXiv …, 2024"],"snippet":"Mixture of Experts (MoE) offers remarkable performance and computational efficiency by selectively activating subsets of model parameters. Traditionally, MoE models use homogeneous experts, each with identical capacity. However, varying …","url":["https://arxiv.org/pdf/2408.10681"]}
{"year":"2024","title":"Ho to Read a Generative AI Image System: Diffusion models as a techno-social entanglement","authors":["E Salvaggio"],"snippet":"… The first approach to resource extraction is the data commons of the world wide web, which is extracted through Common Crawl into datasets. However, there is also an environmental extraction: it is estimated that 700,000 litres of water were …","url":["https://rsdsymposium.org/wp-content/uploads/2024/04/How-to-Read-a-Generative-AI-Image-System-1.pdf"]}
{"year":"2024","title":"Holographic Embeddings for Text and Graphs A Master's Thesis Presented to The Faculty of the Graduate School of Arts and Sciences","authors":["T Obiso - 2024"],"snippet":"… Static word embeddings such as word2vec, Global Vectors for Word Representation (GloVe), and fastText are trained on large amounts of natural language text sources like Common Crawl and Wikipedia dumps. These models …","url":["https://scholarworks.brandeis.edu/view/pdfCoverPage?instCode=01BRAND_INST&filePid=13511842530001921&download=true"]}
{"year":"2024","title":"Homonym Sense Disambiguation in the Georgian Language","authors":["D Melikidze, A Gamkrelidze - arXiv preprint arXiv:2405.00710, 2024"],"snippet":"This research proposes a novel approach to the Word Sense Disambiguation (WSD) task in the Georgian language, based on supervised fine-tuning of a pre-trained Large Language Model (LLM) on a dataset formed by filtering the Georgian …","url":["https://arxiv.org/pdf/2405.00710"]}
{"year":"2024","title":"HOPE: Your Mental Health Companion","authors":["DP Gawade, NA Tank - Recent Advances in Artificial Intelligence and Smart …","RA Borgalli, JP Suryawanshi, DP Gawade, NA Tank… - Recent Advances in Artificial …"],"snippet":"… Common Crawl dataset [11] now containing almost a trillion words. It has been discovered, however, that unfiltered or minimally filtered copies of Common Crawl … train language models, including filtering a version of Common Crawl based on …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=IVojEQAAQBAJ&oi=fnd&pg=PA107&dq=commoncrawl&ots=BEPrP9rrDi&sig=D7r46f_QZ2LMHgCyQ_iqEzsGYpo","https://link.springer.com/content/pdf/10.1007/978-981-97-3485-6.pdf#page=117"]}
{"year":"2024","title":"How Chinese are Chinese Language Models? The Puzzling Lack of Language Policy in China's LLMs","authors":["AW Wen-Yi, UES Jo, LJ Lin, D Mimno - arXiv preprint arXiv:2407.09652, 2024"],"snippet":"… Additionally, similar to the training of international models, sources of pretrained data rely heavily on web pages, with three reports specifically mentioning Common Crawl as their primary data source… Common Crawl 8 (80%), encyclopedia, books …","url":["https://arxiv.org/pdf/2407.09652"]}
{"year":"2024","title":"How Do We Learn What We Cannot Say?","authors":["D Yakubov - 2024"],"snippet":"The contributions of this thesis are two-fold. First, this thesis presents UDTube, an easily usable software developed to perform morphological analysis in a multi-task fashion. This work shows the strong performance of UDTube versus the current state-of-the-art …","url":["https://academicworks.cuny.edu/cgi/viewcontent.cgi?article=6726&context=gc_etds"]}
{"year":"2024","title":"How Does Code Pretraining Affect Language Model Task Performance?","authors":["J Petty, S van Steenkiste, T Linzen - arXiv preprint arXiv:2409.04556, 2024"],"snippet":"Large language models are increasingly trained on corpora containing both natural language and non-linguistic data like source code. Aside from aiding programming-related tasks, anecdotal evidence suggests that including code in pretraining corpora may …","url":["https://arxiv.org/pdf/2409.04556"]}
{"year":"2024","title":"How Effective are State Space Models for Machine Translation?","authors":["H Pitorro, P Vasylenko, M Treviso, AFT Martins - arXiv preprint arXiv:2407.05489, 2024"],"snippet":"… In order to obtain a small high-quality subset for training, we exclude ParaCrawl and CommonCrawl samples from the original dataset and clean the remaining data. Our cleaning process includes three steps. First, we identify and remove samples in …","url":["https://arxiv.org/pdf/2407.05489"]}
{"year":"2024","title":"How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suites","authors":["Z Chen, W Wang, H Tian, S Ye, Z Gao, E Cui, W Tong… - arXiv preprint arXiv …, 2024"],"snippet":"In this report, we introduce InternVL 1.5, an open-source multimodal large language model (MLLM) to bridge the capability gap between open-source and proprietary commercial models in multimodal understanding. We introduce three simple …","url":["https://arxiv.org/pdf/2404.16821"]}
{"year":"2024","title":"How far can bias go?--Tracing bias from pretraining data to alignment","authors":["M Thaler, A Köksal, A Leidinger, A Korhonen… - arXiv preprint arXiv …, 2024"],"snippet":"As LLMs are increasingly integrated into user-facing applications, addressing biases that perpetuate societal inequalities is crucial. While much work has gone into measuring or mitigating biases in these models, fewer studies have investigated …","url":["https://arxiv.org/pdf/2411.19240"]}
{"year":"2024","title":"How Gender Interacts with Political Values: A Case Study on Czech BERT Models","authors":["AA Ali, J Libovický - arXiv preprint arXiv:2403.13514, 2024"],"snippet":"Neural language models, which reach state-of-the-art results on most natural language processing tasks, are trained on large text corpora that inevitably contain value-burdened content and often capture undesirable biases, which the models …","url":["https://arxiv.org/pdf/2403.13514"]}
{"year":"2024","title":"How Large Corpora Sizes Influence the Distribution of Low Frequency Text n-grams","authors":["JF Silva, JC Cunha - Pacific-Asia Conference on Knowledge Discovery and …, 2024"],"snippet":"The prediction of the numbers of distinct word n-grams and their frequency distributions in text corpora is important in domains like information processing and language modelling. With big data corpora, there is an increased application …","url":["https://link.springer.com/chapter/10.1007/978-981-97-2259-4_16"]}
{"year":"2024","title":"How Lexical is Bilingual Lexicon Induction?","authors":["H Kohli, H Feng, N Dronen, C McCarter, S Moeini… - arXiv preprint arXiv …, 2024"],"snippet":"… derived from Common Crawl and Wikipedia. The plot visualizes the Spearman’s Rank correlation of term frequencies between each of the source (by row) and target (by column) language pairs in the 5k vocabularies in the XLING corpus derived from …","url":["https://arxiv.org/pdf/2404.04221"]}
{"year":"2024","title":"How many news websites block AI crawlers?","authors":["R Fletcher - 2024"],"snippet":"In this factsheet we describe the proportion of news websites in ten countries that block AI (artificial intelligence) crawlers. We find that, (i) by the end 2023, 48% of the most widely used news websites across ten countries were blocking OpenAI’s (ChatGPT) …","url":["https://ora.ox.ac.uk/objects/uuid:6b0653e7-4a3b-4448-b0bd-1bdbd55aa61e/files/s3j333388m"]}
{"year":"2024","title":"How Many Van Goghs Does It Take to Van Gogh? Finding the Imitation Threshold","authors":["S Verma, R Rassin, AM Das, G Bhatt, P Seshadri… - Neurips Safe Generative AI …"],"snippet":"… These datasets consist of semi-curated image-text pairs scraped from Common Crawl, 22 which leads to the inclusion of explicit, copyrighted, and licensed material [4, 9, 17, 20, 56]. Training 23 models on such images may be problematic because text-to-image …","url":["https://openreview.net/pdf?id=VYXYFftsOn"]}
{"year":"2024","title":"How Much are LLMs Contaminated? A Comprehensive Survey and the LLMSanitize Library","authors":["M Ravaut, B Ding, F Jiao, H Chen, X Li, R Zhao, C Qin… - arXiv preprint arXiv …, 2024"],"snippet":"… This includes policies and protocols for data privacy, consent, and use that help prevent the incorporation of contaminated data from unethical sources and the contamination of widely used pre-training data sources (eg, CommonCrawl) …","url":["https://arxiv.org/pdf/2404.00699"]}
{"year":"2024","title":"How much semantic information is available in large language model tokens?","authors":["DA Haslett, ZG Cai"],"snippet":"… We first regressed MMLU score on the percentage of the Common Crawl that a language makes up and whether it uses the Latin alphabet… is a significant predictor when added to the model that includes Common Crawl percentage and …","url":["https://osf.io/nhwdz/download"]}
{"year":"2024","title":"How to Synthesize Text Data without Model Collapse?","authors":["X Zhu, D Cheng, H Li, K Zhang, E Hua, X Lv, N Ding… - arXiv preprint arXiv …, 2024"],"snippet":"Model collapse in synthetic data indicates that iterative training on self-generated data leads to a gradual decline in performance. With the proliferation of AI models, synthetic data will fundamentally reshape the web data ecosystem. Future GPT-$\\{n\\} …","url":["https://arxiv.org/pdf/2412.14689"]}
{"year":"2024","title":"How to Train Data-Efficient LLMs","authors":["N Sachdeva, B Coleman, WC Kang, J Ni, L Hong… - arXiv preprint arXiv …, 2024"],"snippet":"The training of large language models (LLMs) is expensive. In this paper, we study data-efficient approaches for pre-training LLMs, ie, techniques that aim to optimize the Pareto frontier of model quality and training resource/data consumption. We …","url":["https://arxiv.org/pdf/2402.09668"]}
{"year":"2024","title":"How to Train Long-Context Language Models (Effectively)","authors":["T Gao, A Wettig, H Yen, D Chen - arXiv preprint arXiv:2410.02660, 2024"],"snippet":"We study continued training and supervised fine-tuning (SFT) of a language model (LM) to make effective use of long-context information. We first establish a reliable evaluation protocol to guide model development -- Instead of perplexity or simple …","url":["https://arxiv.org/pdf/2410.02660"]}
{"year":"2024","title":"HPLT's First Release of Data and Models","authors":["N Arefyev, M Aulamo, P Chen, O de Gibert, B Haddow… - 2024"],"snippet":"… Datasets For the first release, we processed 1.85 petabytes of the Internet Archive and CommonCrawl to create monolingual and parallel corpora. We release them under the permissive CC0 licence1 through our project website2, OPUS3, and Hugging …","url":["https://pinzhenchen.github.io/paper/2024-hplt-project.pdf"]}
{"year":"2024","title":"Human vs. Machine: A Comparative Study on the Detection of AI-Generated Content","authors":["A Boutadjine, F Harrag, K Shaalan - ACM Transactions on Asian and Low-Resource …, 2024"],"snippet":"… It is a large multi-lingual language model, trained on 2.5TB of filtered CommonCrawl data on one hundred languages including Arabic. The transfer learning process involves a meticulous fine-tuning procedure that was diligently …","url":["https://dl.acm.org/doi/pdf/10.1145/3708889"]}
{"year":"2024","title":"Human-Centered Interaction in Virtual Worlds: A New Era of Generative Artificial Intelligence and Metaverse","authors":["Y Wang, L Wang, KL Siau - International Journal of Human–Computer Interaction, 2024"],"snippet":"The metaverse has emerged as an exciting new paradigm for human-computer interaction (HCI) and virtual collaboration. This paper presents a comprehensive review of the metaverse to address the gap in the existing literature where there is a …","url":["https://www.tandfonline.com/doi/abs/10.1080/10447318.2024.2316376"]}
{"year":"2024","title":"Human-Centered Natural Language Processing for Countering Misinformation","authors":["A Kazemi - 2024"],"snippet":"As curbing the spread of online misinformation has proven to be challenging, we look to artificial intelligence (AI) and natural language technology for helping individuals and society counter and limit it. Despite current advances, state-of-the-art …","url":["https://deepblue.lib.umich.edu/bitstream/handle/2027.42/193271/ashkank_1.pdf?sequence=1"]}
{"year":"2024","title":"Humkinar: Construction of a Large Scale Web Repository and Information System for Low Resource Urdu Language","authors":["MA Mehmood, B Tahir - IEEE Access, 2024"],"snippet":"… first Common Crawl Corpus (CCC) filter leverages the open-source Common Crawl repository to filter Urdu language webpages. Common Crawl… From August 2018 onward releases, Common Crawl also provides the meta information …","url":["https://ieeexplore.ieee.org/iel8/6287639/6514899/10666659.pdf"]}
{"year":"2024","title":"Hybrid Bilingual Question-Answering System with Human-Level Naturalness Text-to-Speech Extension","authors":["MT Phạm, PGT Lê - 2024"],"snippet":"This project introduces a robust bilingual question-answering and natural Text-to-Speech (TTS) system, primarily designed to support both Vietnamese and English languages. Leveraging pre-trained Large Language Models (LLMs), the system enables …","url":["http://103.160.76.76/bitstream/123456789/4104/1/1398_SP24AI08_GSP03_SP24AI08_TrungNQ46_VinhTH.pdf"]}
{"year":"2024","title":"Hybrid semantic models for building smart and robust home robots","authors":["A Pal - 2023"],"snippet":"The creation of home robots that can aid human beings in daily mundane chores has been a long-standing goal of robotics research. Some common indoor tasks that service robots can help with include retrieving objects from different locations …","url":["https://escholarship.org/content/qt92w4x2f1/qt92w4x2f1.pdf"]}
{"year":"2024","title":"Hybrid Tokenization Strategy for Turkish Abstractive Text Summarization","authors":["NZ Kayalı, Sİ Omurca - 2024 8th International Artificial Intelligence and Data …, 2024"],"snippet":"Text summarization is a significant topic in natural language processing. Tokenization approaches are important in this regard as they underpin text recognition and processing. The aim of this paper is to research the efficiency of …","url":["https://ieeexplore.ieee.org/abstract/document/10711036/"]}
{"year":"2024","title":"Hydra: Bidirectional State Space Models Through Generalized Matrix Mixers","authors":["S Hwang, A Lahoti, T Dao, A Gu - arXiv preprint arXiv:2407.09941, 2024"],"snippet":"A wide array of sequence models are built on a framework modeled after Transformers, comprising alternating sequence mixer and channel mixer layers. This paper studies a unifying matrix mixer view of sequence mixers that can be …","url":["https://arxiv.org/pdf/2407.09941"]}
{"year":"2024","title":"HYPE: Hyperbolic Entailment Filtering for Underspecified Images and Texts","authors":["W Kim, S Chun, T Kim, D Han, S Yun - arXiv preprint arXiv:2404.17507, 2024"],"snippet":"In an era where the volume of data drives the effectiveness of self-supervised learning, the specificity and clarity of data semantics play a crucial role in model training. Addressing this, we introduce HYPerbolic Entailment filtering (HYPE), a …","url":["https://arxiv.org/pdf/2404.17507"]}
{"year":"2024","title":"Hypertext Entity Extraction in Webpage","authors":["Y Yang, T Liu, B Shao, H Zhao, L Shou, M Gong… - arXiv preprint arXiv …, 2024"],"snippet":"… Common Crawl5 is a widely used large-scale dataset for IE. However, they all overlook rich hypertext features and contain too much noise. Moreover, their annotations are often determined by rules or automated tools, lacking accurate manual annotations. …","url":["https://arxiv.org/html/2403.01698v1"]}
{"year":"2024","title":"I'm In! A Comparative Analysis of Business Pitch Competition","authors":["E Barron, I Bernatovic, LE Ruiz - DIANA INTERNATIONAL RESEARCH …, 2023"],"snippet":"Methods Based on a perceived theoretical gap in research, entrepreneurship scholars have called for increased research to understand how institutions (including governments and academia), influence the construction of intersectional …","url":["https://pure.udem.edu.mx/files/73675582/Conference_Proceedings_Diana_International_Research_Conference_2023_PDF_.pdf"]}
{"year":"2024","title":"Identification of patients' smoking status using an explainable AI approach: a Danish electronic health records case study","authors":["A Ebrahimi, MBH Henriksen, CL Brasen, O Hilberg… - BMC Medical Research …, 2024"],"snippet":"Smoking is a critical risk factor responsible for over eight million annual deaths worldwide. It is essential to obtain information on smoking habits to advance research and implement preventive measures such as screening of high-risk …","url":["https://bmcmedresmethodol.biomedcentral.com/articles/10.1186/s12874-024-02231-4"]}
{"year":"2024","title":"Identification of Trolling Memes in Kannada and Tulu-Under-resourced Dravidian Languages","authors":["A Hegde, SH Lakshmaiah - 2024"],"snippet":"… Trained on a diverse dataset comprising Common Crawl and Wikipedia content across 157 languages, fastText employs Continuous Bag-of-Words (CBOW) with position weights, generating embeddings in a low-dimensional space of size 300 [44] …","url":["https://www.researchsquare.com/article/rs-4663307/latest.pdf"]}
{"year":"2024","title":"Identifying DNS Scanners from a TLD Perspective","authors":["P Huppert - 2024"],"snippet":"… Presumably popular ones include extracting domain names from public TLS certificate registrations using CT logs as well as using any kind of public list, for example from Common Crawl. CT logs are not directly related to the DNS ecosystem …","url":["https://www.sidnlabs.nl/downloads/2aEkyKM1TuH9U94X5422WK/40f3483a6e953d421d0d237f446ffe78/Master_Thesis_Pascal_Huppert.pdf"]}
{"year":"2024","title":"Identifying the sources of ideological bias in GPT models through linguistic variation in output","authors":["C Walker, JC Timoneda - arXiv preprint arXiv:2409.06043, 2024"],"snippet":"Extant work shows that generative AI models such as GPT-3.5 and 4 perpetuate social stereotypes and biases. One concerning but less explored source of bias is ideology. Do GPT models take ideological stances on politically sensitive topics? In …","url":["https://arxiv.org/pdf/2409.06043"]}
{"year":"2024","title":"Identifying Threats on Social Media to Spot Offensive Behavior","authors":["AT Hridi, S Abdullah, MAI Hasnath, RH Adiba, S Proma… - 2024 IEEE 12th …, 2024"],"snippet":"In the modern age, with the help of social media, communication has become available for everyone. Offensive text is broadly used in social media to humiliate or threaten someone. Offensive text like a bully, trolling, threats, and sexual …","url":["https://ieeexplore.ieee.org/abstract/document/10705230/"]}
{"year":"2024","title":"iDRAMA-rumble-2024: A Dataset of Podcasts from Rumble Spanning 2020 to 2022","authors":["U Balci, J Patel, B Balci, J Blackburn - 2024"],"snippet":"Rumble has emerged as a prominent platform hosting controversial figures facing restrictions on YouTube. Despite this, the academic community’s engagement with Rumble has been minimal. To help researchers address this gap, we introduce a …","url":["https://workshop-proceedings.icwsm.org/pdf/2024_07.pdf"]}
{"year":"2024","title":"If You Don't Understand It, Don't Use It: Eliminating Trojans with Filters Between Layers","authors":["A Hernandez - arXiv preprint arXiv:2407.06411, 2024"],"snippet":"… In this model an LLM is pre-trained on a large web corpus such as Common Crawl, the model server tunes the model and inserts it into a (business) mission-critical system, and the model user uses this system. This system can be a chat-bot, code-completion …","url":["https://arxiv.org/pdf/2407.06411"]}
{"year":"2024","title":"IGOT: Information Gain Optimized Tokenizer on Domain Adaptive Pretraining","authors":["D Feng, Y Zhang, Z Xu - arXiv preprint arXiv:2405.09857, 2024"],"snippet":"Pretrained Large Language Models (LLM) such as ChatGPT, Claude, etc. have demonstrated strong capabilities in various fields of natural language generation. However, there are still many problems when using LLM in specialized domain-specific …","url":["https://arxiv.org/pdf/2405.09857"]}
{"year":"2024","title":"Imitation Attacks: Extracting and Exploiting Model Capabilities","authors":["Z Cai"],"snippet":"… • Nepali→English: We query the Nepali Language Wikipedia (approximately 100,000 sentences) and around two million sentences from Nepali Common Crawl We train Transformer Big models on both datasets. In this attack, we replace certain …","url":["https://www.cs.nthu.edu.tw/~ychung/homework/Advanced%20OS/2024-10-10-Report.pdf"]}
{"year":"2024","title":"Impact of COVID-19 Pandemic on Social Determinants of Health Issues of Marginalized Black and Asian Communities: A Social Media Analysis Empowered by …","authors":["C Whitfield, Y Liu, M Anwar - Journal of Racial and Ethnic Health Disparities, 2024"],"snippet":"Purpose This study aims to understand the impact of the COVID-19 pandemic on social determinants of health (SDOH) of marginalized racial/ethnic US population groups, specifically African Americans and Asians, by leveraging natural language …","url":["https://link.springer.com/article/10.1007/s40615-024-01996-0"]}
{"year":"2024","title":"Improve the Accuracy and Efficiency of Large Language Models via Dynamic Token Compression and Adaptive Layer Pruning","authors":["F Potkins, O Langton, V Smirnov, C Gallacher… - 2024"],"snippet":"… Experimental Setup The experiments utilized diverse and widely adopted datasets, such as WikiText and Common Crawl, chosen for their extensive coverage of linguistic features and varied textual content. These datasets allowed for a rigorous …","url":["https://www.techrxiv.org/doi/pdf/10.36227/techrxiv.173030653.35636983"]}
{"year":"2024","title":"Improved methodology for longitudinal Web analytics using Common Crawl","authors":["HS Thompson - 16th ACM Web Science Conference 2024, 2024"],"snippet":"Common Crawl is a multi-petabyte longitudinal dataset containing over 100 billion web pages which is widely used as a source of language data for sequence model training and in web science research. Each of its constituent archives is on the order …","url":["https://www.research.ed.ac.uk/en/publications/improved-methodology-for-longitudinal-web-analytics-using-common-"]}
{"year":"2024","title":"Improving and Understanding Clarifying Question Generation in Conversational Search","authors":["D Ortega, S Söhnel, NT Vu - International Conference on Text, Speech, and …, 2024"],"snippet":"Conversational information-seeking systems (CISs), such as chatbots and virtual personal assistants, encounter difficulty when processing ambiguous user requests (URs) and generate an accurate response, especially when multiple search results match …","url":["https://link.springer.com/chapter/10.1007/978-3-031-70566-3_20"]}
{"year":"2024","title":"Improving Arithmetical Reasoning of Language Models","authors":["M Kadlčík - 2024"],"snippet":"This work focuses on improving language models for solving math word problems. First, we clean and transform existing datasets to create Calc-X, a standardized collection of 300,000 math problems with step-by-step solutions. We demonstrate …","url":["https://is.muni.cz/th/vd9wm/Improving_Arithmetical_Reasoning_of_Language_Models-3.pdf"]}
{"year":"2024","title":"Improving Bengali and Hindi Large Language Models","authors":["A Shahriar, D Barbosa - Proceedings of the 2024 Joint International Conference …, 2024"],"snippet":"Despite being widely spoken worldwide, Bengali and Hindi are low-resource languages. The state-of-the-art in modeling such languages uses BERT and the Wordpiece tokenizer. We observed that the Wordpiece tokenizer often breaks words …","url":["https://aclanthology.org/2024.lrec-main.764.pdf"]}
{"year":"2024","title":"Improving Consumer Health Search with Field-Level Learning-to-Rank Techniques","authors":["H Yang, T Gonçalves - Information, 2024"],"snippet":"In the area of consumer health search (CHS), there is an increasing concern about returning topically relevant and understandable health information to the user. Besides being used to rank topically relevant documents, Learning to Rank (LTR) …","url":["https://www.mdpi.com/2078-2489/15/11/695"]}
{"year":"2024","title":"Improving Cross-lingual Representation for Semantic Retrieval with Code-switching","authors":["M Maimaiti, Y Zheng, J Zhang, F Huang, Y Zhang… - arXiv preprint arXiv …, 2024"],"snippet":"Semantic Retrieval (SR) has become an indispensable part of the FAQ system in the task-oriented question-answering (QA) dialogue scenario. The demands for a cross-lingual smart-customer-service system for an e-commerce platform or some particular …","url":["https://arxiv.org/html/2403.01364v1"]}
{"year":"2024","title":"Improving Parameter-Efficient Cross-Lingual Transfer for Low-Resource Languages","authors":["M Parovic - 2024"],"snippet":"… The success of the XLM-R can largely be attributed to the quality and size of its training corpora the model is pretrained on more than two terabytes of the filtered Common Crawl data. Notable differences in comparison with mBERT (beyond much …","url":["https://www.repository.cam.ac.uk/bitstreams/54a4cd81-9767-4cdb-9957-2b075c822338/download"]}
{"year":"2024","title":"Improving Pretraining Data Using Perplexity Correlations","authors":["T Thrush, C Potts, T Hashimoto - arXiv preprint arXiv:2409.05816, 2024"],"snippet":"Quality pretraining data is often seen as the key to high-performance language models. However, progress in understanding pretraining data has been slow due to the costly pretraining runs required for data selection experiments. We present a …","url":["https://arxiv.org/pdf/2409.05816"]}
{"year":"2024","title":"Improving the Consistency in Cross-Lingual Cross-Modal Retrieval with 1-to-K Contrastive Learning","authors":["Z Nie, R Zhang, Z Feng, H Huang, X Liu - arXiv preprint arXiv:2406.18254, 2024"],"snippet":"… For instance, XLM-R, CCR𝑘 ’s cross-lingual encoder, is trained on the 2.5TB CommonCrawl Corpus encompassing 100 languages. Discrepancies in data sizes between high-resource and low-resource languages within this corpus, like the …","url":["https://arxiv.org/pdf/2406.18254"]}
{"year":"2024","title":"INCLURE: a Dataset and Toolkit for Inclusive French Translation","authors":["P Lerner, C Grouin - The 17th Workshop on Building and Using …, 2024"],"snippet":"… Indeed, this corpus mostly contains transcripts of political speeches, whose oral style differs from the text typically found in OSCAR/CommonCrawl. Exceptions are six examples used to illustrate the use of the inclusive neutralization process …","url":["https://hal.science/hal-04531938/document"]}
{"year":"2024","title":"Incorporating Geo-Diverse Knowledge into Prompting for Increased Geographical Robustness in Object Recognition","authors":["K Buettner, S Malakouti, XL Li, A Kovashka - arXiv preprint arXiv:2401.01482, 2024"],"snippet":"Existing object recognition models have been shown to lack robustness in diverse geographical scenarios due to significant domain shifts in design and context. Class representations need to be adapted to more accurately reflect an object concept …","url":["https://arxiv.org/pdf/2401.01482"]}
{"year":"2024","title":"Incorporating Human Judgment in AI-Assisted Content Development: The HEAT Heuristic","authors":["G Verhulsdonck, J Weible, DM Stambler, T Howard… - Technical Communication, 2024"],"snippet":"Purpose: As technical and professional communicators (TPCs) use AI to develop content, inaccuracies due to AI limitations are introduced; it is vital TPCs evaluate AI-generated content to improve accuracy and human-centeredness. In this article, we present a …","url":["https://www.ingentaconnect.com/contentone/stc/tc/2024/00000071/00000003/art00006"]}
{"year":"2024","title":"Incremental and Flexible Extraction of Parallel Corpus from the Web","authors":["X Liu, Y Zhen, D Li - 2024 3rd International Conference on Artificial …, 2024"],"snippet":"… To avoid duplication of work and to prove the need for incremental extraction, we perform parallel sentence extraction based on the most recent archives of Common Crawl in 2023, and select Chinese and other representative languages as …","url":["https://ieeexplore.ieee.org/abstract/document/10730639/"]}
{"year":"2024","title":"IndiBias: A Benchmark Dataset to Measure Social Biases in Language Models for Indian Context","authors":["NR Sahoo, PP Kulkarni, N Asad, A Ahmad, T Goyal… - arXiv preprint arXiv …, 2024"],"snippet":"The pervasive influence of social biases in language data has sparked the need for benchmark datasets that capture and evaluate these biases in Large Language Models (LLMs). Existing efforts predominantly focus on English language and the …","url":["https://arxiv.org/pdf/2403.20147"]}
{"year":"2024","title":"INDIC QA BENCHMARK: A Multilingual Benchmark to Evaluate Question Answering capability of LLMs for Indic Languages","authors":["AK Singh, R Murthy, J Sen, G Ramakrishnan - arXiv preprint arXiv:2407.13522, 2024"],"snippet":"… To address this, we sampled numerous Wikipedia and Common Crawl pages, focusing on paragraphs rich in cultural nuances and domain diversity. Using these paragraphs, we employed large language models (LLMs) to generate QA pairs, thus …","url":["https://arxiv.org/pdf/2407.13522"]}
{"year":"2024","title":"IndicLLMSuite: A Blueprint for Creating Pre-training and Fine-Tuning Datasets for Indian Languages","authors":["MSUR Khan, P Mehta, A Sankar, U Kumaravelan… - arXiv preprint arXiv …, 2024"],"snippet":"Despite the considerable advancements in English LLMs, the progress in building comparable models for other languages has been hindered due to the scarcity of tailored resources. Our work aims to bridge this divide by introducing an expansive …","url":["https://arxiv.org/pdf/2403.06350"]}
{"year":"2024","title":"Indiscriminate Data Poisoning Attacks on Pre-trained Feature Extractors","authors":["Y Lu, MYR Yang, G Kamath, Y Yu - arXiv preprint arXiv:2402.12626, 2024"],"snippet":"… To collect such large-scale datasets, practitioners usually extract the desired data by crawling on the internet (eg, web pages using Common Crawl1). However, using outsourced data raises an imminent security risk (Kumar et al. 2020; Nelson et al …","url":["https://arxiv.org/html/2402.12626v1"]}
{"year":"2024","title":"Individual-vs. Multiple-Objective Strategies for Targeted Sentiment Analysis in Finances Using the Spanish MTSA 2023 Corpus","authors":["R Pan, JA García-Díaz, R Valencia-García - Electronics, 2024"],"snippet":"… complexity; (vi) RoBERTuito [22], a pretrained language model for user-generated content in Spanish, trained following RoBERTa guidelines on 500 million tweets; and (vii) XLM-RoBERTa [17], a multilingual version of RoBERTa, trained with data …","url":["https://www.mdpi.com/2079-9292/13/4/717/pdf"]}
{"year":"2024","title":"IndoBerea: Evolving Semantic Search in Theological Context","authors":["FVP Samosir, S Mendrofa - 2023 Eighth International Conference on Informatics …, 2023"],"snippet":"This paper presents IndoBerea, a semantic search model pre-trained on an Indonesian Bible dataset and based on SentenceTransformers and IndoBERT. It aims to enhance theological research by providing contextually relevant verses in …","url":["https://ieeexplore.ieee.org/abstract/document/10382053/"]}
{"year":"2024","title":"Indonesian Health Question Multi-Class Classification Based on Deep Learning","authors":["WO Vihikan, INP Trisna - Journal of Information Systems and Informatics, 2024"],"snippet":"… It has been trained on Indonesian Common Crawl and Wikipedia with a vector dimension of 300. A combination of RNN and CNN methods are also implemented, it is called BiLSTM-CNN and BiGRU-CNN. These two methods are connecting …","url":["http://www.journal-isi.org/index.php/isi/article/download/838/423"]}
{"year":"2024","title":"INDUS: Effective and Efficient Language Models for Scientific Applications","authors":["B Bhattacharjee, A Trivedi, M Muraoka… - arXiv preprint arXiv …, 2024"],"snippet":"Large language models (LLMs) trained on general domain corpora showed remarkable results on natural language processing (NLP) tasks. However, previous research demonstrated LLMs trained using domain-focused corpora perform better …","url":["https://arxiv.org/pdf/2405.10725"]}
{"year":"2024","title":"Inference optimization of Large Language Models on RISC-V HPC platforms","authors":["DJ PAGLIARI - 2024"],"snippet":"Over the past decade, there have been significant improvements in Artificial Intelligence (AI), more particularly in the area of natural language processing (NLP) thanks to the emergence of Large Language Models (LLMs). These models are …","url":["https://webthesis.biblio.polito.it/33331/1/tesi.pdf"]}
{"year":"2024","title":"Inference-Based No-Learning Approach on Pre-Trained BERT Model Retrieval","authors":["HL Pham, R Mibayashi, T Yamamoto, MP Kato… - 2024 IEEE International …, 2024"],"snippet":"In recent years, the practice of leveraging pre-trained machine learning models for specific tasks has gained traction. Instead of training models from the ground up, it is now common to fine-tune existing pre-trained models. However, users have the …","url":["https://ieeexplore.ieee.org/abstract/document/10488314/"]}
{"year":"2024","title":"Inferring the Phylogeny of Large Language Models and Predicting their Performances in Benchmarks","authors":["N Yax, PY Oudeyer, S Palminteri - arXiv preprint arXiv:2404.04671, 2024"],"snippet":"This paper introduces PhyloLM, a method applying phylogenetic algorithms to Large Language Models to explore their finetuning relationships, and predict their performance characteristics. By leveraging the phylogenetic distance metric, we …","url":["https://arxiv.org/html/2404.04671v1"]}
{"year":"2024","title":"InfiMM-WebMath-40B: Advancing Multimodal Pre-Training for Enhanced Mathematical Reasoning","authors":["X Han, Y Jian, X Hu, H Liu, Y Wang, Q Fan, Y Ai… - arXiv preprint arXiv …, 2024"],"snippet":"… CommonCrawl [15] repository, preserving full multimodal web documents with interleaved images and text. We start with 44 snapshots of CommonCrawl … To achieve this, we apply language filtering to the CommonCrawl repositories, which …","url":["https://arxiv.org/pdf/2409.12568"]}
{"year":"2024","title":"Information Retrieval Chatbot on Military Policies and Standards","authors":["C Gunasekara, A Sharafeldin, M Triff, Z Kabir…"],"snippet":"In the Canadian Armed Forces (CAF), navigating through extensive policies and standards can be a challenging task. To address the need for streamlined access to these vital documents, this paper explores the usage of artificial intelligence (AI) and …","url":["https://www.scitepress.org/Papers/2024/123512/123512.pdf"]}
{"year":"2024","title":"Information Retrieval with Dense and Sparse Representations","authors":["YS Chuang - 2024"],"snippet":"… However, they use 1TB of the training data from Common Crawl dumps while our model only use 115MB of the Wikipedia data for pretraining. We put their scores in Table 2.2 for reference. In SimCSE, the authors propose to use MLM as an auxiliary …","url":["https://dspace.mit.edu/bitstream/handle/1721.1/153774/chuang-yungsung-sm-eecs-2024-thesis.pdf?sequence=1&isAllowed=y"]}
{"year":"2024","title":"Infusing Prompts with Syntax and Semantics","authors":["AB Labate, FG Cozman - arXiv preprint arXiv:2412.06107, 2024"],"snippet":"Despite impressive success, language models often generate outputs with flawed linguistic structure. We analyze the effect of directly infusing various kinds of syntactic and semantic information into large language models. To demonstrate the …","url":["https://arxiv.org/pdf/2412.06107"]}
{"year":"2024","title":"Initial exploration into sarcasm and irony through machine translation","authors":["ZL Chia, M Ptaszynski, M Karpinska, J Eronen, F Masui - Natural Language …, 2024"],"snippet":"In this paper, we investigate sarcasm and irony as seen through a novel perspective of machine translation. We employ various techniques for translation, comparing both manually and automatically translated datasets of irony and sarcasm. We first …","url":["https://www.sciencedirect.com/science/article/pii/S2949719124000542"]}
{"year":"2024","title":"InjectBench: An Indirect Prompt Injection Benchmarking Framework","authors":["NKS Kong - 2024"],"snippet":"… Many datasets such as CommonCrawl cover a much wider distribution of the types of website online compared to the few datasets we have selected. However, we have chosen to use the following datasets to better understand and emphasize …","url":["https://vtechworks.lib.vt.edu/bitstreams/20f563f7-5926-4df6-949f-21c1f25e157e/download"]}
{"year":"2024","title":"Innovative Use of Self-Attention-Based Ensemble Deep Learning for Suicide Risk Detection in Social Media Posts","authors":["HS Choi, J Yang - Applied Sciences, 2024"],"snippet":"… Specifically, we employed the extensive corpus variant, known as “Common Crawl (840 B tokens, 2.2 M vocab, cased, 300 d vectors)”, which encompasses an impressive 840 billion tokens, a vocabulary of 2.2 million cased terms, and provides …","url":["https://www.mdpi.com/2076-3417/14/2/893"]}
{"year":"2024","title":"Inquiring the'oracle'. An empirical study on how artificial intelligence literacy and prompt engineering influence the use of LLMs and GAI in higher education","authors":["V Rossi - 2024"],"snippet":"The release of ChatGPT by OpenAl on November 2022 marked a significant paradigm shift in the landscape of human-artificial intelligence interaction (HAII); for it signified the accessibility of generative artificial intelligence (GAI) and, in particular …","url":["http://dspace.unive.it/bitstream/handle/10579/27493/875729-1281387.pdf?sequence=2"]}
{"year":"2024","title":"Inside the Black Box: Detecting Data Leakage in Pre-trained Language Encoders","authors":["Y Xin, Z Li, N Yu, D Chen, M Fritz, M Backes, Y Zhang - arXiv preprint arXiv …, 2024"],"snippet":"Despite being prevalent in the general field of Natural Language Processing (NLP), pre-trained language models inherently carry privacy and copyright concerns due to their nature of training on large-scale web-scraped data. In this paper, we pioneer a …","url":["https://arxiv.org/pdf/2408.11046"]}
{"year":"2024","title":"Inspecting and Measuring Fairness of unlabeled Image Datasets","authors":["R Görge, M Mock, M Akila - 2024 IEEE 40th International Conference on Data …, 2024"],"snippet":"Bias in training data can lead to algorithmic unfairness in machine learning tasks. Therefore, a general requirement for trustworthy AI is that data should be representative and free of bias. There are several approaches to measure fairness …","url":["https://ieeexplore.ieee.org/abstract/document/10555073/"]}
{"year":"2024","title":"Institutional challenges","authors":["F Geeraert, K de Wild, M Rockembach, J Winters… - The Routledge Companion …, 2024"],"snippet":"Collections of archived web content can be a connecting factor between GLAM institutions. There is a large variety in the kinds of collections these institutions manage. However, with the increasing awareness about the importance of web …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=RLYyEQAAQBAJ&oi=fnd&pg=PA352&dq=commoncrawl&ots=ebVn40Yl74&sig=cubLNeEZmfE-LNMicAgZ4g0HIYk"]}
{"year":"2024","title":"Instruction-tuned Language Models are Better Knowledge Learners","authors":["Z Jiang, Z Sun, W Shi, P Rodriguez, C Zhou, G Neubig… - arXiv preprint arXiv …, 2024"],"snippet":"… However, its scope is limited to Wikipedia, which restricts the trained models’ adaptability to other sources like web pages from Common Crawl or scientific documents from arXiv. We focus on eliciting factual knowledge with instruction-tuning …","url":["https://arxiv.org/pdf/2402.12847"]}
{"year":"2024","title":"Integrating Generative AI Literacy into the Information Retrieval Course at a university in Canada: towards critical evaluation of online search results","authors":["L Kleinveldt"],"snippet":"… • Trained on information (billions of words) on the open web prior to 2021 • Among other open sources, dataset comes from Common Crawl (crawls the web) and Wikipedia • Length of answers limited - between 500 and 700 words, “leaving …","url":["https://bibliotecas.uchile.cl/congreso/programa/ponencias/dia_3/8_Presentation_Integrating_Generative_AI_Literacy.pdf"]}
{"year":"2024","title":"Intelligent Pharmacy","authors":["A Haleem, M Javaid, RP Singh"],"snippet":"The modern language generation model ChatGPT, created by Open Artificial Intelligence (AI), is recognised for its capacity to comprehend context and produce pertinent content. This model is built on the transformer architecture, which enables …","url":["https://www.researchgate.net/profile/Mohd-Javaid/publication/379261748_Exploring_the_competence_of_ChatGPT_for_customer_and_patient_service_management/links/660e825af5a5de0a9ffb6418/Exploring-the-competence-of-ChatGPT-for-customer-and-patient-service-management.pdf"]}
{"year":"2024","title":"Intelligent Phishing Website Detection Model Powered by Deep Learning Techniques","authors":["U Chetachi, O Henry, OA Agbugba - Asian Journal of Research in Computer …, 2024"],"snippet":"… Approximately one million authentic and fraudulent URLs were employed in the dataset gathered from PhishTank and Common Crawl. Over 10,000 images and one million URLs were used in training for the CNN classifier and LSTM to create the …","url":["http://science.sdpublishers.org/id/eprint/2498/1/Chetachi1762023AJRCOS111125.pdf"]}
{"year":"2024","title":"Intelligent question answering for water conservancy project inspection driven by knowledge graph and large language model collaboration","authors":["Y Yang, S Chen, Y Zhu, X Liu, S Pan, X Wang - LHB, 2024"],"snippet":"Engineering inspection is of great significance to ensure the safe operation of the project. However, the unclear query statements of the detectors pose a challenge to the intelligent question answering task. Existing knowledge graph-based question-answering …","url":["https://www.tandfonline.com/doi/pdf/10.1080/27678490.2024.2397337"]}
{"year":"2024","title":"Interacting Large Language Model Agents. Interpretable Models and Social Learning","authors":["A Jain, V Krishnamurthy - arXiv preprint arXiv:2411.01271, 2024"],"snippet":"This paper develops theory and algorithms for interacting large language model agents (LLMAs) using methods from statistical signal processing and microeconomics. While both fields are mature, their application to decision-making …","url":["https://arxiv.org/pdf/2411.01271"]}
{"year":"2024","title":"Intercity relationships between 293 Chinese cities quantified based on toponym co-occurrence","authors":["W Tongjing, Z Yin, Z Bao, E Meijers - Cybergeo: European Journal of Geography, 2024"],"snippet":"… 14The primary dataset of this study was obtained from the Common Crawl, a web archive that has periodically crawled the Internet since … We used the entire Common Crawl text archive from April 2019 for processing and conducting …","url":["https://journals.openedition.org/cybergeo/40721"]}
{"year":"2024","title":"International Journal of Cognitive Computing in Engineering","authors":["JF Ruma, TT Mayeesha, RM Rahman"],"snippet":"… MC4 dataset contains 101 language variants drawn from the Common Crawl web scrape. MT5 did not deviates much from the original T5 model and attempted to extend the capacities of the T5 to multilingual settings. T5 is a pre-trained language …","url":["https://www.researchgate.net/profile/Tahsin-Mayeesha-2/publication/373997715_Transformer_based_Answer-Aware_Bengali_Question_Generation/links/65b4bfe81bed776ae307bf9f/Transformer-based-Answer-Aware-Bengali-Question-Generation.pdf"]}
{"year":"2024","title":"Internet-scale Topic Modeling using Large Language Models","authors":["R Kajoluoto - 2024"],"snippet":"… This proportion is estimated from the Common Crawl dataset’s statistics [28]. In short, the model should have an excellent understanding of English, an adequate understanding of languages such as German and Spanish, and be satisfactory at …","url":["https://aaltodoc.aalto.fi/bitstreams/b63ce9d3-a01a-48a1-8ff7-831c872fde9d/download"]}
{"year":"2024","title":"InternLM-Math: Open Math Large Language Models Toward Verifiable Reasoning","authors":["H Ying, S Zhang, L Li, Z Zhou, Y Shao, Z Fei, Y Ma… - arXiv preprint arXiv …, 2024"],"snippet":"The math abilities of large language models can represent their abstract reasoning ability. In this paper, we introduce and open-source our math reasoning LLMs InternLM-Math which is continue pre-trained from InternLM2. We unify chain-of-thought …","url":["https://arxiv.org/pdf/2402.06332"]}
{"year":"2024","title":"InternLM2 Technical Report","authors":["Z Cai, M Cao, H Chen, K Chen, K Chen, X Chen… - arXiv preprint arXiv …, 2024"],"snippet":"… Our web page data mainly comes from Common Crawl1. Firstly, we need to decompress the original Warc format files and use Trafilatura (… The entire filtering process eliminates a large proportion of Web page data (Common Crawl) and Patent …","url":["https://arxiv.org/pdf/2403.17297"]}
{"year":"2024","title":"Interpretable Syntactic Representations Enable Hierarchical Word Vectors","authors":["B Silwal - arXiv preprint arXiv:2411.08384, 2024"],"snippet":"The distributed representations currently used are dense and uninterpretable, leading to interpretations that themselves are relative, overcomplete, and hard to interpret. We propose a method that transforms these word vectors into reduced …","url":["https://arxiv.org/pdf/2411.08384?"]}
{"year":"2024","title":"Interpretable Tensor Fusion","authors":["S Varshneya, A Ledent, P Liznerski, A Balinskyy… - arXiv preprint arXiv …, 2024"],"snippet":"Conventional machine learning methods are predominantly designed to predict outcomes based on a single data type. However, practical applications may encompass data of diverse types, such as text, images, and audio. We introduce …","url":["https://arxiv.org/pdf/2405.04671"]}
{"year":"2024","title":"Interpreting Themes from Educational Stories","authors":["Y Zhang, FA González, T Solorio - arXiv preprint arXiv:2404.05250, 2024"],"snippet":"Reading comprehension continues to be a crucial research focus in the NLP community. Recent advances in Machine Reading Comprehension (MRC) have mostly centered on literal comprehension, referring to the surface-level …","url":["https://arxiv.org/pdf/2404.05250"]}
{"year":"2024","title":"Interrupted time series analysis of clickbait on worldwide news websites, 2016-2023","authors":["A McCutcheon, C Brogly - arXiv preprint arXiv:2408.06376, 2024"],"snippet":"… This research provides an analysis of clickbait at the scale of the web on primarily English-language news sites from the Common Crawl. In this analysis, 3 of 5 selected newsgenerating events produced significant terms that suggest major …","url":["https://arxiv.org/pdf/2408.06376"]}
{"year":"2024","title":"Intersecting Register and Genre: Understanding the Contents of Web-Crawled Corpora","authors":["A Myntti, L Repo, E Freyermuth, A Kanner, V Laippala… - Proceedings of the 4th …, 2024"],"snippet":"Web-scale corpora present valuable research opportunities but often lack detailed metadata, making them challenging to use in linguistics and social sciences. This study tackles this problem by exploring automatic methods to classify web corpora …","url":["https://aclanthology.org/2024.nlp4dh-1.38.pdf"]}
{"year":"2024","title":"Intersectional Male-Centric and White-Centric Biases in Collective Concepts","authors":["AH Bailey, A Williams, A Poddar, A Cimpian - 2024"],"snippet":"… Here we used NLP tools (specifically, static word embeddings trained on the Common Crawl corpus) to investigate collective understanding of three fundamental concepts: PERSON, WOMAN, and MAN.These three concepts organize much of …","url":["https://osf.io/72pg5/download"]}
{"year":"2024","title":"Introducing the Djinni Recruitment Dataset: A Corpus of Anonymized CVs and Job Postings","authors":["N Drushchak, M Romanyshyn - Proceedings of the Third Ukrainian Natural …, 2024"],"snippet":"This paper introduces the Djinni Recruitment Dataset, a large-scale open-source corpus of candidate profiles and job descriptions. With over 150,000 jobs and 230,000 candidates, the dataset includes samples in English and Ukrainian, thereby …","url":["https://aclanthology.org/2024.unlp-1.2.pdf"]}
{"year":"2024","title":"Invasion of ChatGPT and LLMs in Review and Writing Spaces: A Revolution or Radical","authors":["A Hadap, V Khatri - Scientific Publishing Ecosystem"],"snippet":"Though AI flourished before 1970s but in the last five years, the invasion of artificial intelligence (AI) tools, such as ChatGPT and Large Language Model (LLMs), has received much attention in scientific research writing. These AI tools assist the …","url":["https://link.springer.com/content/pdf/10.1007/978-981-97-4060-4.pdf#page=280"]}
{"year":"2024","title":"Inverting Gradient Attacks Naturally Makes Data Poisons: An Availability Attack on Neural Networks","authors":["W Bouaziz, EM El-Mhamdi, N Usunier - arXiv preprint arXiv:2410.21453, 2024"],"snippet":"… an analysis of undesirable content in the common crawl corpus. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 2 …","url":["https://arxiv.org/pdf/2410.21453"]}
{"year":"2024","title":"Investigating Complex Answer Attribution Approaches with Large Language Models","authors":["L Mülln"],"snippet":"This master’s thesis explores the attribution of answers in complex question-answering scenarios utilizing large language models (LLMs). The research aims to assess and enhance the traceability of answers back to their source documents, a critical aspect …","url":["https://wwwmatthes.in.tum.de/file/833ntsa6pimy/Sebis-Public-Website/Student-Theses-Guided-Research/Current-Theses-Guided-Researches/Master-s-Thesis-Luca-Muelln/240315_LMuelln_Thesis_Final_Print_Version.pdf"]}
{"year":"2024","title":"Investigating Conversational Agents to Support Secondary School Computer Science Exploratory Search","authors":["M Frazier - 2024"],"snippet":"Online educational resources (eg, curricula, tutorials, documentation, Q&A sites) increasingly serve as key sources for secondary school students learning Computer Science Principles (CSP). A big obstacle to using these resources is finding …","url":["https://search.proquest.com/openview/4b6eedb5cf6b8f8760c66f92266dc243/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
{"year":"2024","title":"Investigating Gender Bias in Turkish Language Models","authors":["O Caglidil, M Ostendorff, G Rehm - arXiv preprint arXiv:2404.11726, 2024"],"snippet":"… an analysis of undesirable content in the common crawl corpus. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 2 …","url":["https://arxiv.org/pdf/2404.11726"]}
{"year":"2024","title":"Investigating the Classification of radicalisation phases of Dutch social media messages upon physical threats","authors":["D Newar - 2024"],"snippet":"The increase of social media platforms such as Twitter and Telegram has transformed communication, enhanced free speech, but also facilitated the spread of harmful content. This rise in online threats against Dutch politicians highlights the …","url":["https://studenttheses.uu.nl/bitstream/handle/20.500.12932/47224/MSc%20Thesis%20Applied%20Data%20Science%20Dean%20Newar.pdf?sequence=1"]}
{"year":"2024","title":"Investigating the impact of pretraining corpora on the performance of Arabic BERT models","authors":["AS Alammary - The Journal of Supercomputing, 2025"],"snippet":"… Akin to Multilingual BERT, the model underwent pretraining using 2.5 terabytes of data from Wikipedia and Common Crawl. The Arabic pretraining corpus is in MSA and comprises 2869 tokens, totaling approximately 28 gigabytes of data. The base …","url":["https://link.springer.com/article/10.1007/s11227-024-06698-2"]}
{"year":"2024","title":"Investigating the pre-training bias in low-resource abstractive summarization","authors":["D Chernyshev, B Dobrov - IEEE Access, 2024"],"snippet":"Recent advances in low-resource abstractive summarization were largely made through the adoption of specialized pre-training, pseudo-summarization, that integrates the content selection knowledge through various centrality-based …","url":["https://ieeexplore.ieee.org/iel7/6287639/6514899/10474365.pdf"]}
{"year":"2024","title":"Investigating Word Embedding Techniques for Extracting Disease, Gene, and Chemical Relationships from Biomedical Texts","authors":["SS Pradeep - 2024"],"snippet":"This thesis investigates word embedding models, including PubMedBERT, BioBERT, SkipGram, CBOW, and GloVe, in the context of Literature-Based Discovery (LBD) within biomedical research, with a specific focus on cancer-related entities. Firstly, I …","url":["https://dalspace.library.dal.ca/bitstream/handle/10222/84633/SushumnaSPradeep2024.pdf?sequence=1&isAllowed=y"]}
{"year":"2024","title":"IPA Transcription of Bengali Texts","authors":["K Fatema, FD Haider, NF Turpa, T Azmal, S Ahmed… - arXiv preprint arXiv …, 2024"],"snippet":"The International Phonetic Alphabet (IPA) serves to systematize phonemes in language, enabling precise textual representation of pronunciation. In Bengali phonology and phonetics, ongoing scholarly deliberations persist concerning the …","url":["https://arxiv.org/pdf/2403.20084"]}
{"year":"2024","title":"IrokoBench: A New Benchmark for African Languages in the Age of Large Language Models","authors":["DI Adelani, J Ojo, IA Azime, JY Zhuang, JO Alabi, X He… - arXiv preprint arXiv …, 2024"],"snippet":"Despite the widespread adoption of Large language models (LLMs), their remarkable capabilities remain limited to a few high-resource languages. Additionally, many low-resource languages (eg African languages) are often …","url":["https://arxiv.org/pdf/2406.03368"]}
{"year":"2024","title":"Is AI changing learning and assessment as we know it? Evidence from a ChatGPT experiment and a conceptual framework","authors":["O Kolade, A Owoseni, A Egbetokun - Heliyon, 2024"],"snippet":"ChatGPT, a state-of-the-art chatbot built upon Open AI's generative pre-trained transformer, has generated a major public interest and caused quite a stir in the higher education sector, where reactions have ranged from excitement to …","url":["https://www.sciencedirect.com/science/article/pii/S2405844024019844"]}
{"year":"2024","title":"Is Artificial Intelligence the Future of Collective Memory?","authors":["S Gensburger, F Clavert - Memory Studies Review, 2024"],"snippet":"… ai tools are first and foremost memory products, as, at least for connectionist ai, they rely on the notion of training which implies the use of datasets – such as CommonCrawl, a sort of archive of the web – which are a product of human activities …","url":["https://brill.com/view/journals/mesr/1/2/article-p195_001.xml"]}
{"year":"2024","title":"Is C4 Dataset Optimal for Pruning? An Investigation of Calibration Data for LLM Pruning","authors":["A Bandari, L Yin, CY Hsieh, AK Jaiswal, T Chen… - arXiv preprint arXiv …, 2024"],"snippet":"Network pruning has emerged as a potential solution to make LLMs cheaper to deploy. However, existing LLM pruning approaches universally rely on the C4 dataset as the calibration data for calculating pruning scores, leaving its optimality …","url":["https://arxiv.org/pdf/2410.07461"]}
{"year":"2024","title":"Is ChatGPT taking over the language classroom? How language ideologies of large language models impact teaching and learning","authors":["M Lau - Working papers in Applied Linguistics and Linguistics …, 2024"],"snippet":"… Thus, using datasets such as the Common Crawl can lead to the over-representation of English and the perspectives of English-speaking content … This means that LLMs that use Common Crawl for training, such as ChatGPT, may perform with …","url":["https://wally.journals.yorku.ca/index.php/default/article/download/36/34"]}
{"year":"2024","title":"Is Google Getting Worse? A Longitudinal Investigation of SEO Spam in Search Engines","authors":["J Bevendorff, M Wiegmann, M Potthast, B Stein"],"snippet":"Many users of web search engines have been complaining in recent years about the supposedly decreasing quality of search results. This is often attributed to an increasing amount of search-engineoptimized but low-quality content. Evidence for …","url":["https://downloads.webis.de/publications/papers/bevendorff_2024a.pdf"]}
{"year":"2024","title":"Is Translation All You Need? A Study on Solving Multilingual Tasks with Large Language Models","authors":["C Liu, W Zhang, Y Zhao, AT Luu, L Bing - arXiv preprint arXiv:2403.10258, 2024"],"snippet":"… We categorize languages larger than 1% frequency in Common Crawl2 as high-resource languages (ie, de, ru, fr, zh, es, ja, it and vi), and the rest as low-resource languages. We exclude English since we want to evaluate the efficient prompting strategy for …","url":["https://arxiv.org/pdf/2403.10258"]}
{"year":"2024","title":"It is Time to Develop an Auditing Framework to Promote Value Aware Chatbots","authors":["Y Wang, L Singh - arXiv preprint arXiv:2409.01539, 2024"],"snippet":"… According to OpenAI, 60% of the training data come from Common Crawl, a large data set consisting of web pages, extracted metadata and text since 2008. Another 22% of data are from WebText2, containing all Reddit posts until December 2017 …","url":["https://arxiv.org/pdf/2409.01539"]}
{"year":"2024","title":"It's About Time: Incorporating Temporality in Retrieval Augmented Language Models","authors":["A Gade, J Jetcheva - arXiv preprint arXiv:2401.13222, 2024"],"snippet":"… Additionally both models are fine-tuned jointly as a Fusion-in-Decoder [3] on common-crawl data using Wikipedia as a document index. The authors showed that Atlas performs well out-of-box and can be adapted to different tasks such as question-answering …","url":["https://arxiv.org/pdf/2401.13222"]}
{"year":"2024","title":"IUST at ClimateActivism 2024: Towards Optimal Stance Detection: A Systematic Study of Architectural Choices and Data Cleaning Techniques","authors":["G Mahmoudi, S Eetemadi - Proceedings of the 7th Workshop on Challenges and …, 2024"],"snippet":"This work presents a systematic search of various model architecture configurations and data cleaning methods. The study evaluates the impact of data cleaning methods on the obtained results. Additionally, we demonstrate that a combination of …","url":["https://aclanthology.org/2024.case-1.24.pdf"]}
{"year":"2024","title":"J. Mitrović, M. Granitzer, University of Passau, Passau, Germany","authors":["M Dinzinger, S Zerhoudi - 6th International Open Search Symposium# …, 2024"],"snippet":"… In addition to crawling, OWLer has ingested parts of publicly available dumps of Common Crawl to fill our crawl space with a broad range of seed URLs and provide a continuous output of crawled web documents despite the discontinuous …","url":["https://elib.dlr.de/210749/1/172-176-PB.pdf#page=19"]}
{"year":"2024","title":"Jack of All Trades, Master of Some, a Multi-Purpose Transformer Agent","authors":["Q Gallouédec, E Beeching, C Romac, E Dellandréa - arXiv preprint arXiv:2402.09844, 2024"],"snippet":"The search for a general model that can operate seamlessly across multiple domains remains a key goal in machine learning research. The prevailing methodology in Reinforcement Learning (RL) typically limits models to a single task …","url":["https://arxiv.org/pdf/2402.09844"]}
{"year":"2024","title":"Japanese Pointer Network based Entity Linker for Wikidata","authors":["Y Sawamura, T Morita, S Egami, T Ugai, K Fukuda - 2023"],"snippet":"… Pre-trained fastText is a model trained on Common Crawl and Wikipedia and provides pre-computed vectors for a word. The length of the POS Tags was changed from 36 to 18. The other five embeddings, namely Entity Embedding, Text Match …","url":["https://ijckg2023.knowledge-graph.jp/pages/proc/paper_18.pdf"]}
{"year":"2024","title":"JetMoE: Reaching Llama2 Performance with 0.1 M Dollars","authors":["Y Shen, Z Guo, T Cai, Z Qin - arXiv preprint arXiv:2404.07413, 2024"],"snippet":"Large Language Models (LLMs) have achieved remarkable results, but their increasing resource demand has become a major obstacle to the development of powerful and accessible super-human intelligence. This report introduces JetMoE-8B …","url":["https://arxiv.org/pdf/2404.07413"]}
{"year":"2024","title":"Jina CLIP: Your CLIP Model Is Also Your Text Retriever","authors":["A Koukounas, G Mastrapas, M Günther, B Wang… - arXiv preprint arXiv …, 2024","H Xiao, G Mastrapas, B Wang - Multi-modal Foundation Model meets Embodied AI …"],"snippet":"Contrastive Language-Image Pretraining (CLIP) is widely used to train models to align images and texts in a common embedding space by mapping them to fixed-sized vectors. These models are key to multimodal information retrieval and related tasks …","url":["https://arxiv.org/pdf/2405.20204","https://openreview.net/pdf?id=lSDkG98goM"]}
{"year":"2024","title":"JiuZhang3. 0: Efficiently Improving Mathematical Reasoning by Training Small Data Synthesis Models","authors":["K Zhou, B Zhang, J Wang, Z Chen, WX Zhao, J Sha… - arXiv preprint arXiv …, 2024"],"snippet":"Mathematical reasoning is an important capability of large language models~(LLMs) for real-world applications. To enhance this capability, existing work either collects large-scale math-related texts for pre-training, or relies on stronger LLMs (\\eg GPT-4) …","url":["https://arxiv.org/pdf/2405.14365"]}
{"year":"2024","title":"JLBert: Japanese Light BERT for Cross-Domain Short Text Classification","authors":["C Kayal, S Chattopadhyay, A Gupta, S Abrol, A Gugol - Proceedings of the 2024 Joint …, 2024"],"snippet":"… Second, there are limited models that have been trained on diverse datasets beyond Wikipedia and Common Crawl, limiting experimentation with other forms of text data. Moreover, with the English language being the focus of research interest …","url":["https://aclanthology.org/2024.lrec-main.833.pdf"]}
{"year":"2024","title":"JOANNA ZYLINSKA: Diffused Seeing","authors":["J ZYLINSKA"],"snippet":"This article examines the transformation of the relationship between seeing and understanding in humans and machines by the technologies of machine learning known as ‘generative AI’. Taking Stable Diffusion as the main case study, while also …","url":["https://mediatheoryjournal.org/2024/09/30/joanna-zylinska-diffused-seeing/"]}
{"year":"2024","title":"Journal of Business Academy","authors":["E GEÇİCİ - Hakem Kurulu"],"snippet":"This study examines in detail the potential of artificial intelligence (AI)-assisted ChatGPT in the field of accounting education and the opportunities and challenges that this utilisation may bring. ChatGPT can benefit by reducing error rates and …","url":["https://www.isakder.org/2024/vol.5_issue2_full_issue.pdf#page=8"]}
{"year":"2024","title":"Juru: Legal Brazilian Large Language Model from Reputable Sources","authors":["RM Junior, R Pires, R Romero, R Nogueira - arXiv preprint arXiv:2403.18140, 2024"],"snippet":"The high computational cost associated with pretraining large language models limits their research. Two strategies have emerged to address this issue: domain specialization and pretraining with high-quality data. To explore these strategies, we …","url":["https://arxiv.org/pdf/2403.18140"]}
{"year":"2024","title":"Just Rewrite It Again: A Post-Processing Method for Enhanced Semantic Similarity and Privacy Preservation of Differentially Private Rewritten Text","authors":["S Meisenbacher, F Matthes - arXiv preprint arXiv:2405.19831, 2024"],"snippet":"The study of Differential Privacy (DP) in Natural Language Processing often views the task of text privatization as a $\\textit{rewriting}$ task, in which sensitive input texts are rewritten to hide explicit or implicit private information. In order to evaluate the …","url":["https://arxiv.org/pdf/2405.19831"]}
{"year":"2024","title":"JusticeAI: A Large Language Models Inspired Collaborative & Cross-Domain Multimodal System for Automatic Judicial Rulings in Smart Courts","authors":["NA Samee, M Alabdulhafith, SMAH Shah, A Rizwan - IEEE Access, 2024"],"snippet":"… For GloVe embedding’s, which are static, we employed embedding’s pre-trained on large-scale datasets such as the Common Crawl or Wikipedia + Gig word corpus. For the dynamic embedding’s from BERT, ALBERT, RoBERTa, and Distilled BERT …","url":["https://ieeexplore.ieee.org/iel8/6287639/6514899/10743188.pdf"]}
{"year":"2024","title":"KazQAD: Kazakh Open-Domain Question Answering Dataset","authors":["R Yeshpanov, P Efimov, L Boytsov, A Shalkarbayuli… - arXiv preprint arXiv …, 2024"],"snippet":"… Kaz-RoBERTa6 is a monolingual model trained on a collection of Kazakh texts from Common Crawl, the Leipzig Corpora Collection, the … XLM-R was pre-trained on a larger multilingual corpus derived from Common Crawl, in which Kazakh is …","url":["https://arxiv.org/pdf/2404.04487"]}
{"year":"2024","title":"KazSAnDRA: Kazakh Sentiment Analysis Dataset of Reviews and Attitudes","authors":["R Yeshpanov, HA Varol - arXiv preprint arXiv:2403.19335, 2024"],"snippet":"This paper presents KazSAnDRA, a dataset developed for Kazakh sentiment analysis that is the first and largest publicly available dataset of its kind. KazSAnDRA comprises an extensive collection of 180,064 reviews obtained from various sources …","url":["https://arxiv.org/pdf/2403.19335"]}
{"year":"2024","title":"KDPII: A New Korean Dialogic Dataset for the Deidentification of Personally Identifiable Information","authors":["L Fei, Y Kang, S Park, Y Jang, J Lee, H Kim - IEEE Access, 2024"],"snippet":"… Using this framework, they examined the \"Common Crawl's web crawl corpus,\" a frequently utilized resource for training LMs, to determine whether it contains high-risk personal information. They also compared various detection methods, including …","url":["https://ieeexplore.ieee.org/iel8/6287639/6514899/10681073.pdf"]}
{"year":"2024","title":"Keeping Humans in the Loop: Human-Centered Automated Annotation with Generative AI","authors":["N Pangakis, S Wolken - arXiv preprint arXiv:2409.09467, 2024"],"snippet":"… Because LLMs are trained on huge volumes of text data, using digital resources such as the Common Crawl, they are able to “memorize” publicly available information during the training process. This issue is compounded due to the fact …","url":["https://arxiv.org/pdf/2409.09467"]}
{"year":"2024","title":"KEPA-CRF: Knowledge expansion prototypical amortized conditional random field for few-shot event detection","authors":["R Wu, L Yu, S Tian, J Long, T Zhou, B Wang - Journal of Intelligent & Fuzzy Systems"],"snippet":"Event Detection (ED) has long struggled with the ambiguous definition of event categories, making it challenging to accurately classify events. Previous endeavors aimed to tackle this problem by constructing prototypes for specific event categories …","url":["https://content.iospress.com/articles/journal-of-intelligent-and-fuzzy-systems/ifs234368"]}
{"year":"2024","title":"Kernel Least Squares Transformations for Cross-Lingual Semantic Spaces","authors":["A Mištera, T Brychcín - International Conference on Text, Speech, and …, 2024"],"snippet":"The rapid development in the field of natural language processing (NLP) and the increasing complexity of linguistic tasks demand the use of efficient and effective methods. Cross-lingual linear transformations between semantic spaces play a …","url":["https://link.springer.com/chapter/10.1007/978-3-031-70563-2_18"]}
{"year":"2024","title":"Key Algorithms for Keyphrase Generation: Instruction-Based LLMs for Russian Scientific Keyphrases","authors":["A Glazkova, D Morozov, T Garipov - arXiv preprint arXiv:2410.18040, 2024"],"snippet":"Keyphrase selection is a challenging task in natural language processing that has a wide range of applications. Adapting existing supervised and unsupervised solutions for the Russian language faces several limitations due to the rich …","url":["https://arxiv.org/pdf/2410.18040"]}
{"year":"2024","title":"Key ingredients for effective zero-shot cross-lingual knowledge transfer in generative tasks","authors":["N Chirkova, V Nikoulina - arXiv preprint arXiv:2402.12279, 2024"],"snippet":"… For Intermediate tuning we finetune models for 100k steps on the CommonCrawl data uniformly sampled across all target languages and English, with the batch size of 5k tokens and the LR chosen to optimize fluency of model generations, inspected …","url":["https://arxiv.org/pdf/2402.12279"]}
{"year":"2024","title":"Knowledge Distillation with Applications to Interpretable Arabic Sentiment Analysis","authors":["A Diwali, K Saeedi, K Dashtipour, M Gogate, A Hussain - 2024"],"snippet":"… These embeddings, trained on Common Crawl and Wikipedia data, were constructed using the CBOW model with position weights. The embeddings consist of 300-dimensional vectors featuring character n-grams of length 5, a context …","url":["https://www.researchsquare.com/article/rs-5356825/latest.pdf"]}
{"year":"2024","title":"Knowledge Graph as Pre-training Corpus for Structural Reasoning via Multi-hop Linearization","authors":["W Kim, H Jung, W Kim - IEEE Access, 2024"],"snippet":"Large language models have demonstrated exceptional performance across various natural language processing tasks. However, their reliance on unstructured text corpora for pre-training limits their effectiveness in tasks requiring structured …","url":["https://ieeexplore.ieee.org/iel8/6287639/6514899/10817607.pdf"]}
{"year":"2024","title":"Knowledge Induced Transformer Network for Causality Prediction","authors":["T Dasgupta, M Sinha, A Naskar - Companion Proceedings of the ACM on Web …, 2024"],"snippet":"… The CausalBank dataset3 contains 314 million pairs of cause-effect statements scraped from the Common Crawl corpus using causal lexical patterns. Baselines: Most of the earlier work on causality detection is based on identifying cause, effect …","url":["https://dl.acm.org/doi/abs/10.1145/3589335.3651531"]}
{"year":"2024","title":"Knowledge Sources","authors":["M Jiang, BY Lin, S Wang, Y Xu, W Yu, C Zhu - Knowledge-augmented Methods for …, 2024"],"snippet":"… To be more specific, the dataset includes Pile-CommonCrawl (227.12G, web crawling data), PubMed Central (90.27G, biomedical articles), Books (100.96G, a mix of fiction and nonfiction books), OpenWebText (262.77G, content from Reddit) …","url":["https://link.springer.com/chapter/10.1007/978-981-97-0747-8_2"]}
{"year":"2024","title":"Knowledge Transfer from Vision Foundation Models for Efficient Training of Small Task-specific Models","authors":["R Vemulapalli, H Pouransari, F Faghri, S Mehta… - Forty-first International Conference …"],"snippet":"… 2023) which contains 1.28B images filtered from Common Crawl (web-crawled data). We take 10 randomly augmented crops from each image and create a gallery of 12.8B images. See Appendix B.2 for additional details about this gallery set and …","url":["https://openreview.net/pdf?id=OKYfaYQlML"]}
{"year":"2024","title":"Knowledge-augmented Methods for Natural Language Processing","authors":["M Jiang"],"snippet":"Ever since language was invented and used, humans have leveraged this powerful tool to pass down experience over generations. These kinds of knowledge summarize precious findings and inspiring ideas, which constitute the human …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=tlsAEQAAQBAJ&oi=fnd&pg=PR5&dq=commoncrawl&ots=XzQIdUcgNg&sig=EzGLwwhZB2mo602CaK_dytKIWaY"]}
{"year":"2024","title":"Knowledge-Enhanced Neural Networks for Machine Reading Comprehension","authors":["TB Mihaylov - 2024"],"snippet":"Machine Reading Comprehension is a language understanding task where a system is expected to read a given passage of text and typically answer questions about it. When humans assess the task of reading comprehension, in addition to the …","url":["https://archiv.ub.uni-heidelberg.de/volltextserver/34352/1/Thesis_Todor_Mihaylov_Camera_Ready.pdf"]}
{"year":"2024","title":"KOMPYUTER LINGVISTIKASIDA TA'MINOT MASALASI VA SINONIM BIRLIKLARNING LINGVISTIK TA'MINOTI","authors":["N SOTVOLDIYEVA - News of UzMU journal, 2024"],"snippet":"… Lingvistik ma'lumotlar konsorsiumi (LDC) va Common Crawl[8] loyihasi kabi ochiq hamkorlik tashabbuslari lingvistik resurslarning mavjudligiga sezilarli hissa qo'shdi. Bu hamkorlik resurslar almashinuvini targ‘ib qiladi, ortiqchalikni kamaytiradi va …","url":["https://journalsnuu.uz/index.php/1/article/download/803/266"]}
{"year":"2024","title":"Krishiq-BERT: A Few-Shot Setting BERT Model to Answer Agricultural-Related Questions in the Kannada Language","authors":["P Ajawan, V Desai, S Kale, S Patil - Journal of The Institution of Engineers (India) …, 2024"],"snippet":"… corpora for 11 languages from two language families obtained primarily by sourcing articles from news crawls [3], and OSCAR (Open Super-large Crawled ALMAnaCH coRpus), a huge multilingual corpus procured by language …","url":["https://link.springer.com/article/10.1007/s40031-023-00952-6"]}
{"year":"2024","title":"KVP10k: A Comprehensive Dataset for Key-Value Pair Extraction in Business Documents","authors":["O Naparstek, R Pony, I Shapira, FA Dahood, O Azulai… - arXiv preprint arXiv …, 2024"],"snippet":"… : extensive web data from Common Crawl and a collection of images from publicfiles.fcc.gov. From Common Crawl, we employed a systematic … A schematic describing the data acquisition process for the common crawl data is shown in Fig.2 …","url":["https://arxiv.org/pdf/2405.00505"]}
{"year":"2024","title":"L3i++ at SemEval-2024 Task 8: Can Fine-tuned Large Language Model Detect Multigenerator, Multidomain, and Multilingual Black-Box Machine-Generated Text?","authors":["HTH Tran, TN Nguyen, A Doucet, S Pollak - … of the 18th International Workshop on …, 2024"],"snippet":"… Meanwhile, XLM-R is a multilingual version of RoBERTa that was pretrained on 2.5TB of filtered CommonCrawl data containing 100 languages. These models are also suggested as the baseline methods from SemEval2024 Task 8 organizers. …","url":["https://aclanthology.org/2024.semeval-1.3.pdf"]}
{"year":"2024","title":"Labadain-30k+: A Monolingual Tetun Document-Level Audited Dataset","authors":["G de Jesus, S Nunes - Proceedings of the 3rd Annual Meeting of the Special …, 2024"],"snippet":"This paper introduces Labadain-30k+, a monolingual dataset comprising 33.6 k documents in Tetun, a low-resource language spoken in Timor-Leste. The dataset was acquired through web crawling and augmented with Wikipedia documents …","url":["https://aclanthology.org/2024.sigul-1.22.pdf"]}
{"year":"2024","title":"Label-dependent semantic associations for existing concepts","authors":["A Petrenco, F Günther"],"snippet":"In a series of studies, we examined whether a label assigned to a cue concept (political event or its actor) modulates(a) its semantic associations (semantic effects) and (b) valence of the associations and attitude judgments (valence effects). We introduced …","url":["https://www.researchgate.net/profile/Aliona-Petrenco/publication/382464047_Label-dependent_semantic_associations_for_existing_concepts/links/669f7ae127b00e0ca43c1ae3/Label-dependent-semantic-associations-for-existing-concepts.pdf"]}
{"year":"2024","title":"Ladder: A Model-Agnostic Framework Boosting LLM-based Machine Translation to the Next Level","authors":["Z Feng, R Chen, Y Zhang, Z Meng, Z Liu - arXiv preprint arXiv:2406.15741, 2024"],"snippet":"General-purpose Large Language Models (LLMs) like GPT-4 have achieved remarkable advancements in machine translation (MT) by leveraging extensive web content. On the other hand, translation-specific LLMs are built by pre-training on …","url":["https://arxiv.org/pdf/2406.15741"]}
{"year":"2024","title":"Language as a Lens: A Hybrid Text Summarization and Sentiment Analysis Approach for Multiclass Stock Return Prediction","authors":["F Balaneji - Intelligent Systems Conference, 2024"],"snippet":"This research explores the application of text summarization and sentiment analysis techniques in the multiclass classification of hourly stock price returns, studying six companies from the Dow Jones Index between 2017 and the first quarter of 2020 …","url":["https://link.springer.com/chapter/10.1007/978-3-031-66336-9_31"]}
{"year":"2024","title":"Language as a Lens: A Hybrid Text Summarization and Sentiment Analysis Approach for Multiclass Stock Return","authors":["F Balaneji - Intelligent Systems and Applications: Proceedings of …"],"snippet":"This research explores the application of text summarization and sentiment analysis techniques in the multiclass classification of hourly stock price returns, studying six companies from the Dow Jones Index between 2017 and the first quarter of 2020 …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=KkgXEQAAQBAJ&oi=fnd&pg=PA429&dq=commoncrawl&ots=edhnlELBx3&sig=Kr0kGkAID2Gy79rLocQXLifojyM"]}
{"year":"2024","title":"Language Model Frame Filling for Low Resource Languages","authors":["L Zong"],"snippet":"Acceptability judgment tasks are key tools used in the understanding of the grammar of languages by linguists. A typical way to construct these tasks is to use semantic frames. We provide evidence that the fill-mask objective for language models (LMs) …","url":["https://leonzong.com/papers/csc247_final.pdf"]}
{"year":"2024","title":"Language Model-Driven Data Pruning Enables Efficient Active Learning","authors":["AH Azeemi, IA Qazi, AA Raza - arXiv preprint arXiv:2410.04275, 2024"],"snippet":"Active learning (AL) optimizes data labeling efficiency by selecting the most informative instances for annotation. A key component in this procedure is an acquisition function that guides the selection process and identifies the suitable …","url":["https://arxiv.org/pdf/2410.04275"]}
{"year":"2024","title":"Language Models Fine-Tuning for Automatic Format Reconstruction of SEC Financial Filings","authors":["G Lombardo, G Trimigno, M Pellegrino, S Cagnoni - IEEE Access, 2024"],"snippet":"The analysis of financial reports is a crucial task for investors and regulators, especially the mandatory annual reports (10-K) required by the SEC (Securities and Exchange Commission) that provide crucial information about a public company in …","url":["https://ieeexplore.ieee.org/iel7/6287639/6514899/10445214.pdf"]}
{"year":"2024","title":"Language Models for Online Depression Detection: A Review and Benchmark Analysis on Remote Interviews","authors":["R Qin, R Cook, K Yang, A Abbasi, D Dobolyi, S Seyedi… - ACM Transactions on …, 2024"],"snippet":"… The project primarily uses data from the English CommonCrawl (67%) but also includes other public data sources including Wikipedia, GitHub, and ArXiv. LLaMA’s ability to outperform GPT-3 on the RACE Reading Comprehension benchmark …","url":["https://dl.acm.org/doi/pdf/10.1145/3673906"]}
{"year":"2024","title":"Language Models on a Diet: Cost-Efficient Development of Encoders for Closely-Related Languages via Additional Pretraining","authors":["N Ljubešić, V Suchomel, P Rupnik, T Kuzman… - arXiv preprint arXiv …, 2024"],"snippet":"The world of language models is going through turbulent times, better and ever larger models are coming out at an unprecedented speed. However, we argue that, especially for the scientific community, encoder models of up to 1 billion parameters …","url":["https://arxiv.org/pdf/2404.05428"]}
{"year":"2024","title":"Language Models Pre-training","authors":["U Kamath, K Keenan, G Somers, S Sorenson - Large Language Models: A Deep Dive …, 2024"],"snippet":"… The Common Crawl data is the most notable publicly available web scrape. … They demonstrated that these sources improved downstream performance over models trained on less diverse corpora such as Common Crawl. Taking this idea …","url":["https://link.springer.com/content/pdf/10.1007/978-3-031-65647-7_2.pdf"]}
{"year":"2024","title":"Language models scale reliably with over-training and on downstream tasks","authors":["SY Gadre, G Smyrnis, V Shankar, S Gururangan… - arXiv preprint arXiv …, 2024"],"snippet":"Scaling laws are useful guides for developing language models, but there are still gaps between current scaling studies and how language models are ultimately trained and evaluated. For instance, scaling is usually studied in the compute-optimal …","url":["https://arxiv.org/pdf/2403.08540"]}
{"year":"2024","title":"Large Concept Models: Language Modeling in a Sentence Representation Space","authors":["LCM The, L Barrault, PA Duquenne, M Elbayad… - arXiv preprint arXiv …, 2024"],"snippet":"LLMs have revolutionized the field of artificial intelligence and have emerged as the de-facto tool for many tasks. The current established technology of LLMs is to process input and generate output at the token level. This is in sharp contrast to …","url":["https://arxiv.org/pdf/2412.08821"]}
{"year":"2024","title":"Large Language Model Powered In-House Question Answering Assistant","authors":["G Şahin, K Varol, BK Pak - 2024 Innovations in Intelligent Systems and …, 2024"],"snippet":"Large language models are widely used in many natural language processing applications today. Automatic question answering is one of the areas where language models are frequently used. In this study, a question answering system …","url":["https://ieeexplore.ieee.org/abstract/document/10757102/"]}
{"year":"2024","title":"Large Language Model-Based Chatbots in Higher Education","authors":["D Yigci, M Eryilmaz, AK Yetisen, S Tasoglu, A Ozcan - Advanced Intelligent Systems, 2024"],"snippet":"Large language models (LLMs) are artificial intelligence (AI) platforms capable of analyzing and mimicking natural language processing. Leveraging deep learning, LLM capabilities have been advanced significantly, giving rise to generative …","url":["https://onlinelibrary.wiley.com/doi/pdf/10.1002/aisy.202400429"]}
{"year":"2024","title":"Large Language Models (LLMs) on Tabular Data: Predic-tion, Generation, and Understanding-A Survey","authors":["X Fang, W Xu, FA Tan, J Zhang, Z Hu, Y Qi… - arXiv preprint arXiv …, 2024"],"snippet":"Recent breakthroughs in large language modeling have facilitated rigorous exploration of their application in diverse tasks related to tabular data modeling, such as prediction, tabular data synthesis, question answering, and table …","url":["https://stewarthu.com/papers/LLM-on-tabular-data.pdf"]}
{"year":"2024","title":"Large Language Models and Rule-Based Approaches in Domain-Specific Communication","authors":["D Halvoník, J Kapusta - IEEE Access, 2024"],"snippet":"Currently, we are once again experiencing a frenzy related to artificial intelligence. Generative Pre-trained Transformers (GPT) models are highly effective at various natural language processing tasks. Different varieties of GPT models are widely …","url":["https://ieeexplore.ieee.org/iel8/6287639/6514899/10620177.pdf"]}
{"year":"2024","title":"Large Language Models and Sentiment Analysis in Financial Markets: A Review, Datasets and Case Study","authors":["C Liu, A Arulappan, R Naha, A Mahanti… - IEEE Access, 2024"],"snippet":"This paper comprehensively examines Large Language Models (LLMs) in sentiment analysis, specifically focusing on financial markets and exploring the correlation between news sentiment and Bitcoin prices. We systematically categorize various …","url":["https://ieeexplore.ieee.org/iel8/6287639/6514899/10638546.pdf"]}
{"year":"2024","title":"Large Language Models and the Disappearing Private Sphere","authors":["A Cappello, M Dada, V Grigoreva, R Khan, C Stinson… - 2024"],"snippet":"… The higher quality datasets are sampled more often during training, but the Reddit approved contents of CommonCrawl still … of CommonCrawl contains fan fiction, video game chats, conspiracy theories, pornography, junk advertising, and …","url":["https://etlab.cs.queensu.ca/files/2024/04/OPC_Final_Report_2023.pdf"]}
{"year":"2024","title":"Large Language Models aren't all that you need","authors":["KV Holla, C Kumar, A Singh - arXiv preprint arXiv:2401.00698, 2024"],"snippet":"This paper describes the architecture and systems built towards solving the SemEval 2023 Task 2: MultiCoNER II (Multilingual Complex Named Entity Recognition) [1]. We evaluate two approaches (a) a traditional Conditional Random …","url":["https://arxiv.org/pdf/2401.00698"]}
{"year":"2024","title":"LARGE LANGUAGE MODELS AS AN AID FOR SOFTWARE DEVELOPMENT USING GRAPHICAL PROGRAMMING LANGUAGE.","authors":["V Tiljander - 2023"],"snippet":"… In pre-training, the model is trained with the Common Crawl dataset, internet books, and Python code, summing up to 400B tokens. After the model is pre-trained, the phase preference model pre-training comes, and after that, the preference model …","url":["https://trepo.tuni.fi/bitstream/handle/10024/153734/TiljanderVille.pdf?sequence=2"]}
{"year":"2024","title":"Large Language Models As Genetic Counselors: AI-DRIVEN TOOLS FOR HEALTH MANAGEMENT","authors":["Z Majeed - 2024"],"snippet":"This thesis, in collaboration with Arkus-AI, explores the development of an AI-driven genetic counselor designed to enhance genetic counseling services at Eiira. By utilizing advanced large language models, this project aims to improve the quality …","url":["https://www.diva-portal.org/smash/get/diva2:1888227/FULLTEXT01.pdf"]}
{"year":"2024","title":"Large Language Models As Genetic Counselors: Personalized AI Driven Tool for Health Management","authors":["Z Majeed - 2024"],"snippet":"This thesis, in collaboration with Arkus-AI, explores the development of an AI-driven genetic counselor designed to enhance genetic counseling services at Eiira. By utilizing advanced large language models, this project aims to improve the quality …","url":["https://www.diva-portal.org/smash/get/diva2:1887688/FULLTEXT01.pdf"]}
{"year":"2024","title":"Large language models as oracles for instantiating ontologies with domain-specific knowledge","authors":["G Ciatto, A Agiollo, M Magnini, A Omicini - arXiv preprint arXiv:2404.04108, 2024"],"snippet":"… Models following the RoBERTa [30] approach were trained on (i) the same datasets as BERT, plus (ii) a sample of the CommonCrawl4 News dataset (a dump of news … 4https://commoncrawl.org 5https://mistral.ai/news/mixtral-of-experts …","url":["https://arxiv.org/html/2404.04108v1"]}
{"year":"2024","title":"Large Language Models Can Not Perform Well in Understanding and Manipulating Natural Language at Both Character and Word Levels?","authors":["Y Zhang, Z He - Findings of the Association for Computational …, 2024"],"snippet":"Despite their promising performance across various tasks, recent studies reveal that Large language models (LLMs) still exhibit significant deficiencies in handling several word-level and character-level tasks, eg, word unscrambling and sentence …","url":["https://aclanthology.org/2024.findings-emnlp.691.pdf"]}
{"year":"2024","title":"Large Language Models for Biomedical Text Simplification: Promising But Not There Yet","authors":["Z Li, S Belkadi, N Micheletti, L Han, MSG Nenadic"],"snippet":"… the common crawl corpus and filtered to keep only natural text and de-duplication processing. They extracted 750GB of clean English data to feed into the model for multi-task pretraining. Different masking strategies are integrated into the T5 model …","url":["https://www.researchgate.net/profile/Lifeng-Han-3/publication/383335863_Investigating_Large_Language_Models_and_Control_Mechanisms_to_Improve_Text_Readability_of_Biomedical_Abstracts/links/66cc693dc2eaa50023188c60/Investigating-Large-Language-Models-and-Control-Mechanisms-to-Improve-Text-Readability-of-Biomedical-Abstracts.pdf"]}
{"year":"2024","title":"Large language models for biomedicine: foundations, opportunities, challenges, and best practices","authors":["SS Sahoo, JM Plasek, H Xu, Ö Uzuner, T Cohen… - Journal of the American …, 2024"],"snippet":"… In the pre-training phase, generic training data, such as the Common Crawl dataset or social media posts, are used for unsupervised learning.With further training on prompt-response pairs (such as the Alpaca dataset developed at Stanford23) …","url":["https://academic.oup.com/jamia/advance-article/doi/10.1093/jamia/ocae074/7657768"]}
{"year":"2024","title":"Large Language Models for Forecasting and Anomaly Detection: A Systematic Literature Review","authors":["J Su, C Jiang, X Jin, Y Qiao, T Xiao, H Ma, R Wei… - arXiv preprint arXiv …, 2024"],"snippet":"… The training data for GPT-3 includes the Common Crawl dataset for lower quality, as well as the WebText2 dataset for higher quality, as well as the Books1, Books2, and Wikipedia datasets for higher quality [148]. GPT-3 assigns different weights to …","url":["https://arxiv.org/pdf/2402.10350"]}
{"year":"2024","title":"Large Language Models for Human-Machine Collaborative Particle Accelerator Tuning through Natural Language","authors":["J Kaiser, A Eichler, A Lauscher - arXiv preprint arXiv:2405.08888, 2024"],"snippet":"Autonomous tuning of particle accelerators is an active and challenging field of research with the goal of enabling novel accelerator technologies cutting-edge high-impact applications, such as physics discovery, cancer research and material sciences. A …","url":["https://arxiv.org/pdf/2405.08888"]}
{"year":"2024","title":"Large Language Models for identification of medical data in unstructured records","authors":["P Petkov, E Markov, L Tomov"],"snippet":"… Sources for the training data include web pages extracted by CommonCrawl, opensource GitHub repositories, Wikipedia in twenty languages, Project Gutenberg books in the public domain, LaTeX source code of scientific articles in ArXiv and …","url":["https://www.researchgate.net/profile/Latchezar-Tomov/publication/379754048_Large_Language_Models_for_identification_of_medical_data_in_unstructured_records/links/661927fff7d3fc28744fc7cf/Large-Language-Models-for-identification-of-medical-data-in-unstructured-records.pdf"]}
{"year":"2024","title":"Large Language Models for Relevance Judgement in Table Retrieval","authors":["N Grote - 2024"],"snippet":"… The tables come from the English subset of the Web Data Commons (WDC) table corpus 2015, which contains 50.8M HTML tables from the July 2015 Common Crawl The creators of the WTR collection further filtered the collection by identifying entities …","url":["https://publiscologne.th-koeln.de/files/2485/BA_Grote_Nils.pdf"]}
{"year":"2024","title":"Large Language Models for Reliable Information Extraction","authors":["L Baliunas"],"snippet":"This project addresses the ongoing challenge of achieving reliable Information Extraction (IE), particularly in domains which require near-perfect precision. ELICIT (Butcher et al., 2023) introduced a novel approach that combines the processing speed of …","url":["https://www.mlmi.eng.cam.ac.uk/files/2022_-_2023_dissertations/large_language_models_for_reliable_information_extraction.pdf"]}
{"year":"2024","title":"Large Language Models for Software Engineering: A Systematic Mapping Study","authors":["MK Görmez, M Yılmaz, PM Clarke - European Conference on Software Process …, 2024"],"snippet":"In this research, we aim to conduct a systematic mapping study on Large Language Models (LLMs) for Software Engineering (SE). The significantly enhanced capabilities of LLMs have led to their use in many fields, including the important …","url":["https://link.springer.com/chapter/10.1007/978-3-031-71139-8_5"]}
{"year":"2024","title":"LARGE LANGUAGE MODELS FOR TEXT CLASSIFICATION: FROM ZERO-SHOT LEARNING TO INSTRUCTION-TUNING","authors":["Y Chae, T Davidson - 2024"],"snippet":"Advances in large language models (LLMs) have transformed the field of natural language processing and have enormous potential for social scientific analysis. We explore the application of LLMs to supervised text classification. As a case study, we …","url":["https://files.osf.io/v1/resources/sthwk/providers/osfstorage/64e61d8f9dbc3f068f681622?format=pdf&action=download&direct&version=3"]}
{"year":"2024","title":"LARGE LANGUAGE MODELS IN ECONOMICS","authors":["E Ash, S Hansen, Y Muvdi"],"snippet":"This chapter explores the transformative impact of large language models (LLMs) on text analysis in economics. We trace the evolution from traditional methods like bag-of-words to advanced models such as BERT and GPT, highlighting how these models …","url":["https://elliottash.com/wp-content/uploads/2024/10/Ash-Hansen-Large-Language-Models-Economics.pdf"]}
{"year":"2024","title":"Large language models in healthcare: from a systematic review on medical examinations to a comparative analysis on fundamentals of robotic surgery online test","authors":["A Moglia, K Georgiou, P Cerveri, L Mainardi… - Artificial Intelligence Review, 2024"],"snippet":"Large language models (LLMs) have the intrinsic potential to acquire medical knowledge. Several studies assessing LLMs on medical examinations have been published. However, there is no reported evidence on tests related to robot-assisted …","url":["https://link.springer.com/article/10.1007/s10462-024-10849-5"]}
{"year":"2024","title":"Large Language Models on Tabular Data--A Survey","authors":["X Fang, W Xu, FA Tan, J Zhang, Z Hu, Y Qi… - arXiv preprint arXiv …, 2024"],"snippet":"Recent breakthroughs in large language modeling have facilitated rigorous exploration of their application in diverse tasks related to tabular data modeling, such as prediction, tabular data synthesis, question answering, and table …","url":["https://arxiv.org/pdf/2402.17944"]}
{"year":"2024","title":"Large Language Models Understand Layouts","authors":["W Li, M Duan, D An, Y Shao - arXiv preprint arXiv:2407.05750, 2024"],"snippet":"… We find that GLM, Llama, and GPT-3 all use datasets such as CommonCrawl, Wikipedia, and Books (Pile includes CommonCrawl, Wikipedia, and Books) in their pretraining. CommonCrawl is a large-scale, unstructured, multilingual web dataset …","url":["https://arxiv.org/pdf/2407.05750"]}
{"year":"2024","title":"Large Language Models, scientific knowledge and factuality: A framework to streamline human expert evaluation","authors":["M Wysocka, O Wysocki, M Delmas, V Mutel, A Freitas - Journal of Biomedical …, 2024"],"snippet":"Objective: The paper introduces a framework for the evaluation of the encoding of factual scientific knowledge, designed to streamline the manual evaluation process typically conducted by domain experts. Inferring over and extracting information from …","url":["https://www.sciencedirect.com/science/article/pii/S1532046424001424"]}
{"year":"2024","title":"Large Language Models: A Case Study on Corporate Values and Transformative Technologies","authors":["S Burre - 2024"],"snippet":"Design (VSD) a technique that provides theories and methods to systematically “account for human values… throughout the design process”(Value Sensitive Design Lab, nd). This paper employs VSD as a theoretical lens to dissect the dual challenges of …","url":["https://sidhardhburre.com/STS4600/final.pdf"]}
{"year":"2024","title":"Large Language Models: A Deep Dive","authors":["U Kamath, K Keenan, G Somers, S Sorenson"],"snippet":"In the panorama of technological evolution, Large Language Models (LLMs) have emerged as a cornerstone, transforming our interaction with information, reshaping industries, and redefining the boundaries of artificial intelligence. As we stand on the …","url":["https://link.springer.com/content/pdf/10.1007/978-3-031-65647-7.pdf"]}
{"year":"2024","title":"Large Language Models: A Survey","authors":["S Minaee, T Mikolov, N Nikzad, M Chenaghlu… - arXiv preprint arXiv …, 2024"],"snippet":"… Common Crawlbased dataset consisting of texts in 101 languages. … CommonCrawl. They also released an extract of 600 billion tokens from our REFINEDWEB dataset, and 1.3/7.5B parameters language models trained on it. 27 …","url":["https://arxiv.org/pdf/2402.06196"]}
{"year":"2024","title":"Large Language Models: An Introduction","authors":["U Kamath, K Keenan, G Somers, S Sorenson - Large Language Models: A Deep Dive …, 2024"],"snippet":"This chapter begins with a discussion of the historical context and progression of natural language processing. Beginning with the origins of human linguistic capabilities, this chapter explains the gradual transition to computational language …","url":["https://link.springer.com/content/pdf/10.1007/978-3-031-65647-7_1.pdf"]}
{"year":"2024","title":"Large Language Models: Ethics and Norms in the European Union","authors":["M Ciullo - 2024 IEEE International Conference on Metrology for …, 2024"],"snippet":"This paper investigates the ethical-legal issues underlying the implementation of Large Language Models, in the aftermath of the European Union Parliament's approval of the Artificial Intelligence Regulation. In very recent years, there has been …","url":["https://ieeexplore.ieee.org/abstract/document/10795986/"]}
{"year":"2024","title":"Large Malaysian Language Model Based on Mistral for Enhanced Local Language Understanding","authors":["H Zolkepli, A Razak, K Adha, A Nazhan - arXiv preprint arXiv:2401.13565, 2024"],"snippet":"… An analysis of the widely utilized Common Crawl dataset reveals a mere 0.0742% contribution from the Malay language based on CCMAIN-… We also replicated the same technique for Malaysia Hansard and MS CommonCrawl samples. All synthetic …","url":["https://arxiv.org/pdf/2401.13565"]}
{"year":"2024","title":"Large Scale Transfer Learning for Tabular Data via Language Modeling","authors":["J Gardner, JC Perdomo, L Schmidt - arXiv preprint arXiv:2406.12031, 2024"],"snippet":"… Given that T4 consists of 3.1Mtables sourced from public data sources (Common Crawl, Github) and that our evaluations are also comprised of public benchmarks, we investigate the extent and possible impact of data contamination – that is …","url":["https://arxiv.org/pdf/2406.12031"]}
{"year":"2024","title":"Large Vocabulary Size Improves Large Language Models","authors":["S Takase, R Ri, S Kiyono, T Kato - arXiv preprint arXiv:2406.16508, 2024"],"snippet":"This paper empirically investigates the relationship between subword vocabulary size and the performance of large language models (LLMs) to provide insights on how to define the vocabulary size. Experimental results show that larger vocabulary …","url":["https://arxiv.org/pdf/2406.16508"]}
{"year":"2024","title":"Large-language models facilitate discovery of the molecular signatures regulating sleep and activity","authors":["D Peng, L Zheng, D Liu, C Han, X Wang, Y Yang… - Nature Communications, 2024"],"snippet":"Sleep, locomotor and social activities are essential animal behaviors, but their reciprocal relationships and underlying mechanisms remain poorly understood. Here, we elicit information from a cutting-edge large-language model (LLM), generative pre-trained …","url":["https://www.nature.com/articles/s41467-024-48005-w"]}
{"year":"2024","title":"Large-Language-Models (LLM)-Based AI Chatbots: Architecture, In-Depth Analysis and Their Performance Evaluation","authors":["V Kumar, P Srivastava, A Dwivedi, I Budhiraja… - International Conference on …, 2023"],"snippet":"… LLaMA models span from 7 billion to 65 billion parameters and were trained on trillions of tokens derived from publicly accessible datasets, including Common Crawl and Wikipedia. The primary objective of LLaMA models is to serve as …","url":["https://link.springer.com/chapter/10.1007/978-3-031-53085-2_20"]}
{"year":"2024","title":"Large-scale machine unlearning in transformer-based pre-trained language models: Evaluation and adaptation of existing machine unlearning frameworks KGA and …","authors":["D Kowieski"],"snippet":"In the past few years, Machine Learning (ML) models such as GPT-4, utilized by the prominent chatbot ChatGPT, have faced data breaches, raising concerns about data privacy and awareness about the \"right to be forgotten.\" Consequently, the concept …","url":["https://opus.fhv.at/files/5470/FHV_Master_Thesis_Dominik_Kowieski_Print.pdf"]}
{"year":"2024","title":"Large-scale Summarization of Chat Transcripts in the Absence of Annotated Summaries","authors":["PK Biswas - Proceedings of the 7th International Conference on …, 2024"],"snippet":"Text summarization is the process of condensing a piece of text to fewer sentences, while still preserving its content. Chat transcript, in this context, is a textual copy of a digital/web conversation between a customer (caller) and agent (s). This paper …","url":["https://aclanthology.org/2024.icnlsp-1.12.pdf"]}
{"year":"2024","title":"LASERBEAK: Evolving Website Fingerprinting Attacks with Attention and Multi-Channel Feature Representation","authors":["N Mathews, JK Holland, N Hopper, M Wright - IEEE Transactions on Information …, 2024"],"snippet":"In this paper, we present LASERBEAK, a new state-of-the-art website fingerprinting attack for Tor that achieves nearly 96% accuracy against FRONT-defended traffic by combining two innovations: (i) multi-channel traffic representations and (ii) advanced …","url":["https://ieeexplore.ieee.org/abstract/document/10693553/"]}
{"year":"2024","title":"Latent mechanisms of language disorganization relate to specific dimensions of psychopathology","authors":["I Fradkin, RA Adams, N Siegelman, R Moran, RJ Dolan - Nature Mental Health, 2024"],"snippet":"Comprehensible communication is critical for social functioning and well-being. In psychopathology, incoherent discourse is assumed to reflect disorganized thinking, which is classically linked to psychotic disorders. However, people do not express …","url":["https://www.nature.com/articles/s44220-024-00351-w"]}
{"year":"2024","title":"Latxa: An Open Language Model and Evaluation Suite for Basque","authors":["J Etxaniz, O Sainz, N Perez, I Aldabe, G Rigau, E Agirre… - arXiv preprint arXiv …, 2024"],"snippet":"We introduce Latxa, a family of large language models for Basque ranging from 7 to 70 billion parameters. Latxa is based on Llama 2, which we continue pretraining on a new Basque corpus comprising 4.3M documents and 4.2B tokens. Addressing the …","url":["https://arxiv.org/pdf/2403.20266"]}
{"year":"2024","title":"Law and the Political Economy of AI Production","authors":["P Terzis"],"snippet":"The governance of Artificial Intelligence (AI) is at a historical juncture. Legislative acts, global treaties, export controls, and technical standards are now dominating the discourse over what used to be a predominantly market-driven space. Amidst all this …","url":["https://osf.io/q593j/download"]}
{"year":"2024","title":"Law, Technology and Humans","authors":["J De Cooman"],"snippet":"… Around 60% of GPT-3 training data comes from a filtered version of Common Crawl—that is, a non-profit organisation that archives and provides open-access petabytes of data collected since 2011. [30] The remaining 40% comes from diverse …","url":["https://www.austlii.edu.au/au/journals/LawTechHum/2023/3.html"]}
{"year":"2024","title":"Law/Juridiskā zinātne: The Journal of the University of Latvia, N 17","authors":["L Universitāte - 2024"],"snippet":"The goal of this research is to provide recommendations for the improvement of both national legislation and the practice of public prosecution in the suppression of corruption. In the paper, authors started from the assumption that the effectiveness of …","url":["https://dspace.lu.lv/dspace/bitstream/handle/7/67112/Juridisk%20_Zin%20tne_2024_Nr_17.pdf?sequence=1"]}
{"year":"2024","title":"LAWSUIT: a LArge expert-Written SUmmarization dataset of ITalian constitutional court verdicts","authors":["L Ragazzi, G Moro, S Guidi, G Frisoni - Artificial Intelligence and Law, 2024"],"snippet":"Large-scale public datasets are vital for driving the progress of abstractive summarization, especially in law, where documents have highly specialized jargon. However, the available resources are English-centered, limiting research …","url":["https://link.springer.com/article/10.1007/s10506-024-09414-w"]}
{"year":"2024","title":"LDAdam: Adaptive Optimization from Low-Dimensional Gradient Statistics","authors":["T Robert, M Safaryan, IV Modoranu, D Alistarh - arXiv preprint arXiv:2410.16103, 2024"],"snippet":"We introduce LDAdam, a memory-efficient optimizer for training large models, that performs adaptive optimization steps within lower dimensional subspaces, while consistently exploring the full parameter space during training. This strategy keeps …","url":["https://arxiv.org/pdf/2410.16103"]}
{"year":"2024","title":"Learning entity and relation representation for low-resource medical language processing","authors":["S Amin - 2024"],"snippet":"Recent advancements in natural language processing have led to growing interest in critical domains such as legal, finance, and healthcare. In particular, medical language processing has emerged as a focus of its own. As the number of …","url":["https://publikationen.sulb.uni-saarland.de/bitstream/20.500.11880/38051/1/PhD_final_Amin.pdf"]}
{"year":"2024","title":"Learning Fine-Grained Grounded Citations for Attributed Large Language Models","authors":["L Huang, X Feng, W Ma, Y Gu, W Zhong, X Feng, W Yu… - arXiv preprint arXiv …, 2024"],"snippet":"… 2021), a pre-processed and cleaned version of the Common Crawl corpus, serving as a proxy web search index. In particular, for a given user query sampled from the AQuAMuSe dataset, we initially retrieve the top 100 relevant documents …","url":["https://arxiv.org/pdf/2408.04568"]}
{"year":"2024","title":"Learning from Noisy Data for Cross Lingual Text Generation in Low-Resource Languages","authors":["KA Hari - 2024"],"snippet":"With Large Language Models (LLMs) and Language models in general becoming a more significant part of our daily content consumption, it is paramount to ensure that languages with fewer resources do not get excluded. As most language models are …","url":["https://web2py.iiit.ac.in/research_centres/publications/download/mastersthesis.pdf.8dbb3b9e6b257dcc.7468657369732d66696e616c2e706466.pdf"]}
{"year":"2024","title":"Learning to Generate Answers with Citations via Factual Consistency Models","authors":["R Aly, Z Tang, S Tan, G Karypis - arXiv preprint arXiv:2406.13124, 2024"],"snippet":"Large Language Models (LLMs) frequently hallucinate, impeding their reliability in mission-critical situations. One approach to address this issue is to provide citations to relevant sources alongside generated content, enhancing the verifiability of …","url":["https://arxiv.org/pdf/2406.13124"]}
{"year":"2024","title":"Learning When to Retrieve, What to Rewrite, and How to Respond in Conversational QA","authors":["N Roy, LFR Ribeiro, R Blloshmi, K Small - arXiv preprint arXiv:2409.15515, 2024"],"snippet":"… In particular, we use 54M passages from Wikipedia and Common Crawl as the knowledge base.We use an off-the-shelf Contriever model trained on MS-MARCO as the retriever.. The retrieved passages are used by SELFmulti-RAG to generate …","url":["https://arxiv.org/pdf/2409.15515"]}
{"year":"2024","title":"Learning with Noisy Foundation Models","authors":["H Chen, J Wang, Z Wang, R Tao, H Wei, X Xie… - arXiv preprint arXiv …, 2024"],"snippet":"… GPT2 is pre-trained on WebText [29], a scraped web dataset from Common Crawl that contains low-quality raw texts. We also leverage OpenAI’s API service “text-ada-002”. We cannot use larger and more recent language models such as LLaMA [30], since …","url":["https://arxiv.org/pdf/2403.06869"]}
{"year":"2024","title":"Leveraging AI to Deliver Culturally Responsive Mental Health Care at Scale","authors":["A Cerezo, D Cooper, V Palat, A Jolley, S Peregrine"],"snippet":"… One of the most commonly used datasets to train LLMs is The Common Crawl dataset, a large collection of web pages scraped from the internet since 2014. These pages contain the gamut from high-quality news, science, and literature to the …","url":["https://s3.ca-central-1.amazonaws.com/assets.jmir.org/assets/preprints/preprint-56965-submitted.pdf"]}
{"year":"2024","title":"Leveraging distant supervision and deep learning for twitter sentiment and emotion classification","authors":["M Kastrati, Z Kastrati, A Shariq Imran, M Biba - Journal of Intelligent Information …, 2024"],"snippet":"Nowadays, various applications across industries, healthcare, and security have begun adopting automatic sentiment analysis and emotion detection in short texts, such as posts from social media. Twitter stands out as one of the most popular …","url":["https://link.springer.com/article/10.1007/s10844-024-00845-0"]}
{"year":"2024","title":"Leveraging investments, promoting transparency and mobilising communities: a qualitative analysis of news articles about how the Ebola outbreak informed COVID …","authors":["LP Courtney, M Billaud, A Paulenich, R Chew… - BMJ Global Health, 2024"],"snippet":"… Articles were compiled from the Common Crawl archives,24 an open-source database of historical web pages across local, regional, and international news outlets, extracted using the Python ‘news-please’ library25 and translated into …","url":["https://gh.bmj.com/content/9/10/e015378"]}
{"year":"2024","title":"Leveraging Large Language Models for Code-Mixed Data Augmentation in Sentiment Analysis","authors":["L Zeng - arXiv preprint arXiv:2411.00691, 2024"],"snippet":"Code-mixing (CM), where speakers blend languages within a single expression, is prevalent in multilingual societies but poses challenges for natural language processing due to its complexity and limited data. We propose using a large …","url":["https://arxiv.org/pdf/2411.00691"]}
{"year":"2024","title":"Leveraging Large Language Models for Fact Verification in Italian","authors":["A Scaiella, S Costanzo, E Passone, D Croce… - 2024"],"snippet":"… For the automatic translation process, we utilized MADLAD400 [20], a machine translation system based on the Transformer architecture3, trained on MADLAD, a manually audited, general domain 3T token multilingual dataset based on …","url":["https://clic2024.ilc.cnr.it/wp-content/uploads/2024/12/97_main_long.pdf"]}
{"year":"2024","title":"Leveraging large language models for word sense disambiguation","authors":["JH Yae, NC Skelly, NC Ranly, PM LaCasse - Neural Computing and Applications, 2024"],"snippet":"Natural language processing (NLP) is difficult because human language contains ambiguity. The same word can have a different meaning depending on the context and may result in different interpretations given biases held by a NLP technique …","url":["https://link.springer.com/article/10.1007/s00521-024-10747-5"]}
{"year":"2024","title":"Leveraging Large Language Models to Measure Gender Bias in Gendered Languages","authors":["E Derner, SS de la Fuente, Y Gutiérrez, P Moreda… - arXiv preprint arXiv …, 2024"],"snippet":"Gender bias in text corpora used in various natural language processing (NLP) contexts, such as for training large language models (LLMs), can lead to the perpetuation and amplification of societal inequalities. This is particularly …","url":["https://arxiv.org/pdf/2406.13677"]}
{"year":"2024","title":"Leveraging LLMs for Collaborative Ontology Engineering in Parkinson Disease Monitoring and Alerting","authors":["G Bouchouras, D Doumanas, A Soularidis, K Kotis…"],"snippet":"This paper explores the integration of Large Language Models (LLMs) in the engineering of a Parkinson’s Disease (PD) monitoring and alerting ontology through four key methodologies: One Shot (OS) prompt techniques, Chain of Thought (CoT) …","url":["https://neurosymbolic-ai-journal.com/system/files/nai-paper-773.pdf"]}
{"year":"2024","title":"Leveraging Open Large Language Models for Multilingual Policy Topic Classification: The Babel Machine Approach","authors":["M Sebők, Á Máté, O Ring, V Kovács, R Lehoczki - Social Science Computer Review, 2024"],"snippet":"The article presents an open-source and freely available natural language processing system for comparative policy studies. The CAP Babel Machine allows for the automated classification of input files based on the 21 major policy topics of …","url":["https://journals.sagepub.com/doi/pdf/10.1177/08944393241259434"]}
{"year":"2024","title":"Leveraging Parameter Efficient Training Methods for Low Resource Text Classification: A case study in Marathi","authors":["P Deshmukh, N Kulkarni, S Kulkarni, K Manghani… - 2024 IEEE 9th International …, 2024"],"snippet":"With the surge in digital content in low-resource languages, there is an escalating demand for advanced Natural Language Processing (NLP) techniques tailored to these languages. BERT (Bidirectional Encoder Representations from Transformers) …","url":["https://ieeexplore.ieee.org/abstract/document/10543946/"]}
{"year":"2024","title":"Leveraging Social Media and Deep Learning for Sentiment Analysis for Smart Governance: A Case Study of Public Reactions to Educational Reforms in Saudi Arabia","authors":["A Alotaibi, F Nadeem - Computers, 2024"],"snippet":"The Saudi government’s educational reforms aim to align the system with market needs and promote economic opportunities. However, a lack of credible data makes assessing public sentiment towards these reforms challenging. This research …","url":["https://www.mdpi.com/2073-431X/13/11/280"]}
{"year":"2024","title":"Leveraging Social Media Data For More Comprehensive Traffic Load Prediction","authors":["U MEHMOOD, I MOSER - 2024"],"snippet":"Traffic congestion is a major problem in developing countries, where urban space is often limited. With the growing urban population and increasing number of vehicles, it has become essential to manage the existing road networks efficiently. In the past …","url":["https://figshare.swinburne.edu.au/articles/thesis/Leveraging_Social_Media_Data_For_More_Comprehensive_Traffic_Load_Prediction/26360341/1/files/47884201.pdf"]}
{"year":"2024","title":"Leveraging Universal Speech Representations for Detecting and Assessing the Severity of Mild Cognitive Impairment Across Languages","authors":["A Favaro, T Cao, N Dehak, L Moro-Velazquez"],"snippet":"This study examines the suitability of language-agnostic features for automatically detecting Mild Cognitive Impairment (MCI) and predicting Mini-Mental State Examination (MMSE) scores in a multilingual framework. We explored two methods …","url":["https://www.isca-archive.org/interspeech_2024/favaro24_interspeech.pdf"]}
{"year":"2024","title":"Leveraging Zero-Shot Prompting for Efficient Language Model Distillation","authors":["L Vöge, V Gurgul, S Lessmann - arXiv preprint arXiv:2403.15886, 2024"],"snippet":"… Specifically, we use the T5 v1.1 models which were only pretrained on the C4 Common Crawl dataset for general language understanding without additional task-specific finetuning. The use of text-to-text models allows for straightforward processing, as …","url":["https://arxiv.org/pdf/2403.15886"]}
{"year":"2024","title":"LexEval: A Scalable LLM Evaluation Framework","authors":["S Singh, A Edalat, C Lala, R Hu - 2024"],"snippet":"As Large Language Models (LLMs) become more powerful and their parameter counts increase, it is crucial for them to exhibit consistent recall capabilities for terms that appear less frequently in their pre-training data. The importance of accurate …","url":["https://www.imperial.ac.uk/media/imperial-college/faculty-of-engineering/computing/public/2324-ug-projects/Siddhant-Singh-EDITED-LexEval-A-Scalable-LLM-Evaluation-Framework.pdf"]}
{"year":"2024","title":"Lib2Life–Digital Library Services Empowered with Advanced Natural Language Processing Techniques","authors":["M Nitu, M Dascalu, MD Dascalu, LM Neagu…"],"snippet":"Educational institutions are struggling to keep up with the accelerated technological advancements; hence, sustainable and supportive tools have become essential to reshape traditional models into intelligent learning systems. This paper introduces …","url":["https://www.researchgate.net/profile/Nitu-Melania-2/publication/380769622_Lib2Life_-_Digital_Library_Services_Empowered_with_Advanced_Natural_Language_Processing_Techniques/links/664efa3022a7f16b4f43a5e1/Lib2Life-Digital-Library-Services-Empowered-with-Advanced-Natural-Language-Processing-Techniques.pdf"]}
{"year":"2024","title":"LiBERTa: Advancing Ukrainian Language Modeling through Pre-training from Scratch","authors":["M Haltiuk, A Smywiński-Pohl - Proceedings of the Third Ukrainian Natural Language …, 2024"],"snippet":"… CC-100, a multilingual text corpus sourced from Wikipedia and CommonCrawl, was processed following the CCNet1 methodology. The Ukrainian segment of CC-100 encompasses 6.5 billion tokens, equivalent to 84 GiB of data2. This corpus primarily …","url":["https://aclanthology.org/2024.unlp-1.14.pdf"]}
{"year":"2024","title":"LIBRARIES, ARCHIVES, AND THE BORN-DIGITAL","authors":["P Gooding - The Routledge Companion to Libraries, Archives, and …, 2024"],"snippet":"The material record of contemporary culture is increasingly being created in digital form. While decades in the making, this shift has accelerated in recent years as communications, work, commerce, and creativity are mediated by computers. We …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=CiQzEQAAQBAJ&oi=fnd&pg=PT204&dq=commoncrawl&ots=KP8x4_bStL&sig=G4ezH45UoY_KiitL6aIzLmJllk0"]}
{"year":"2024","title":"Likelihood as a Performance Gauge for Retrieval-Augmented Generation","authors":["T Liu, J Qi, P He, A Bisazza, M Sachan, R Cotterell - arXiv preprint arXiv:2411.07773, 2024"],"snippet":"… 2021)—a filtered version of Common Crawl9, where k is taken to be {5,10,20} to avoid truncation due to the long questions and LMs responses for the long-form QA task. In contrast to NQ-Open, ELI5 does not provide the annotations of gold …","url":["https://arxiv.org/pdf/2411.07773"]}
{"year":"2024","title":"Limitations of Language Models in The Oil & Gas Upstream Operations","authors":["A Alsultan, FA Razak - International Petroleum Technology Conference, 2024"],"snippet":"… Although the process is simple in principle, it is done on very large training corpra which can be as big as dataset provided by the Common Crawl project (428.81 TB as of the date of writing this paper). Thus, training these models using these large …","url":["https://onepetro.org/IPTCONF/proceedings-abstract/24IPTC/All-24IPTC/542606"]}
{"year":"2024","title":"Limits to Predicting Online Speech Using Large Language Models","authors":["M Remeli, M Hardt, RC Williamson - arXiv preprint arXiv:2407.12850, 2024"],"snippet":"We study the predictability of online speech on social media, and whether predictability improves with information outside a user's own posts. Recent work suggests that the predictive information contained in posts written by a user's peers …","url":["https://arxiv.org/pdf/2407.12850"]}
{"year":"2024","title":"LINGOLY: A Benchmark of Olympiad-Level Linguistic Reasoning Puzzles in Low-Resource and Extinct Languages","authors":["AM Bean, S Hellsten, H Mayne, J Magomere, EA Chi… - arXiv preprint arXiv …, 2024"],"snippet":"… ], while the second and fourth rows are sorted by Common Crawl Share [16]. The upper two … of pages tagged with a given language in the Common Crawl dataset [16]. Figure 12 show the … LLMs are trained on, using the Common Crawl share and …","url":["https://arxiv.org/pdf/2406.06196"]}
{"year":"2024","title":"Linguistic Profiling of Deepfakes: An Open Database for Next-Generation Deepfake Detection","authors":["Y Wang, Z Huang, Z Ma, X Hong - arXiv preprint arXiv:2401.02335, 2024"],"snippet":"The emergence of text-to-image generative models has revolutionized the field of deepfakes, enabling the creation of realistic and convincing visual content directly from textual descriptions. However, this advancement presents considerably greater …","url":["https://arxiv.org/pdf/2401.02335"]}
{"year":"2024","title":"Linguistic Structure from a Bottleneck on Sequential Information Processing","authors":["R Futrell, M Hahn - arXiv preprint arXiv:2405.12109, 2024"],"snippet":"… Table 3: English expressions for the given meanings, along with frequencies from the English Common Crawl web corpus [64]. Example … n-gram counts and language models from the common crawl. In Language Resources and Evaluation …","url":["https://arxiv.org/pdf/2405.12109"]}
{"year":"2024","title":"Linguistic variation beyond the Indo-European web: Analyzing Turkish web registers in TurCORE","authors":["S Erten-Johansson, V Skantsi, S Pyysalo, V Laippala - Register Studies, 2024"],"snippet":"… To ensure that the documents in TurCORE do not retain any structure from the original CommonCrawl datasets, we extracted the TurCORE … CommonCrawl data are typically very noisy due to the automatic processes involved in crawling and …","url":["https://www.jbe-platform.com/content/journals/10.1075/rs.24002.ert"]}
{"year":"2024","title":"Linguistic_Hygenist at PAN 2024 TextDetox: HybridDetox-A Combination of Supervised and Unsupervised Methods for Effective Multilingual Text Detoxification","authors":["S Gangopadhyay, MT Khan, H Jabeen - 2024"],"snippet":"… To handle these, we used the XLM-RoBERTa large model [25], which is pretrained in a self-supervised manner on 2.5TB of filtered CommonCrawl data spanning 100 languages, including all languages featured in the competition. The model employs a …","url":["https://ceur-ws.org/Vol-3740/paper-236.pdf"]}
{"year":"2024","title":"Linguistically-Informed Multilingual Instruction Tuning: Is There an Optimal Set of Languages to Tune?","authors":["G Soykan, GG Şahin - arXiv preprint arXiv:2410.07809, 2024"],"snippet":"Multilingual language models often perform unevenly across different languages due to limited generalization capabilities for some languages. This issue is significant because of the growing interest in making universal language models …","url":["https://arxiv.org/pdf/2410.07809"]}
{"year":"2024","title":"Link, Synthesize, Retrieve: Universal Document Linking for Zero-Shot Information Retrieval","authors":["DY Hwang, B Taha, H Pande, Y Nechaev - arXiv preprint arXiv:2410.18385, 2024"],"snippet":"Despite the recent advancements in information retrieval (IR), zero-shot IR remains a significant challenge, especially when dealing with new domains, languages, and newly-released use cases that lack historical query traffic from existing users. For …","url":["https://arxiv.org/pdf/2410.18385"]}
{"year":"2024","title":"LITS: An Optimized Learned Index for Strings (An Extended Version)","authors":["Y Yang, S Chen - arXiv preprint arXiv:2407.11556, 2024"],"snippet":"Index is an important component in database systems. Learned indexes have been shown to outperform traditional tree-based index structures for fixed-sized integer or floating point keys. However, the application of the learned solution to variable-length …","url":["https://arxiv.org/pdf/2407.11556"]}
{"year":"2024","title":"LITS: An Optimized Learned Index for Strings","authors":["Y Yang, S Chen - Proceedings of the VLDB Endowment, 2024"],"snippet":"Index is an important component in database systems. Learned indexes have been shown to outperform traditional tree-based index structures for fixed-sized integer or floating point keys. However, the application of the learned solution to variable-length …","url":["https://dl.acm.org/doi/abs/10.14778/3681954.3682010"]}
{"year":"2024","title":"Living in Digital Ecosystems: Are We Aware of This?","authors":["S Cozzini, M de Luca - Digital Environments and Human Relations, 2024"],"snippet":"… , we briefly discuss the Common Crawl case, which has already been extensively analysed (Baack and Insights, 2024). Common Crawl is a … Recently, Common Crawl dataset has become one of the most important sources of training for …","url":["https://link.springer.com/chapter/10.1007/978-3-031-76961-0_6"]}
{"year":"2024","title":"Living in Digital Ecosystems: Are","authors":["S Cozzini, M de Luca - Digital Environments and Human Relations: Ethical …"],"snippet":"… , we briefly discuss the Common Crawl case, which has already been extensively analysed (Baack and Insights, 2024). Common Crawl is a … Recently, Common Crawl dataset has become one of the most important sources of training for …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=N6c2EQAAQBAJ&oi=fnd&pg=PA112&dq=commoncrawl&ots=ypwoSLClje&sig=yoaOZkLpoHid1T7WSwHwu4BELYo"]}
{"year":"2024","title":"LL\\\" aMmlein: Compact and Competitive German-Only Language Models from Scratch","authors":["J Pfister, J Wunderle, A Hotho - arXiv preprint arXiv:2411.11171, 2024"],"snippet":"We create two German-only decoder models, LL\\\"aMmlein 120M and 1B, transparently from scratch and publish them, along with the training data, for the German NLP research community to use. The model training involved several key …","url":["https://arxiv.org/pdf/2411.11171"]}
{"year":"2024","title":"Llama (LLM)","authors":["C Room - algorithms, 2024"],"snippet":"… Data was mostly from CommonCrawl and C4. Llama-2-70B saw 2T tokens but Llama-3-70B saw 15T tokens. Llama-3-8B and Llama-3-70B took 1.3M and 6.4M GPU hours for pretraining. …","url":["https://devopedia.org/llama-llm"]}
{"year":"2024","title":"LLaMA Beyond English: An Empirical Study on Language Capability Transfer","authors":["J Zhao, Z Zhang, Q Zhang, T Gui, X Huang - arXiv preprint arXiv:2401.01055, 2024"],"snippet":"In recent times, substantial advancements have been witnessed in large language models (LLMs), exemplified by ChatGPT, showcasing remarkable proficiency across a range of complex tasks. However, many mainstream LLMs (eg LLaMA) are …","url":["https://arxiv.org/pdf/2401.01055"]}
{"year":"2024","title":"LLaMA-MoE: Building Mixture-of-Experts from LLaMA with Continual Pre-training","authors":["T Zhu, X Qu, D Dong, J Ruan, J Tong, C He, Y Cheng - arXiv preprint arXiv …, 2024"],"snippet":"… As to the Dev-to-Train differences in Figure 9b, we find HellaSwag and ARC-c share the most similar expert preferences with CommonCrawl and C4, and GSM-8K is similar to arXiv. This may provide some insights for continual pre-training to further …","url":["https://arxiv.org/pdf/2406.16554"]}
{"year":"2024","title":"LLaMAX: Scaling Linguistic Horizons of LLM by Enhancing Translation Capabilities Beyond 100 Languages","authors":["Y Lu, W Zhu, L Li, Y Qiao, F Yuan - arXiv preprint arXiv:2407.05975, 2024"],"snippet":"Large Language Models~(LLMs) demonstrate remarkable translation capabilities in high-resource language tasks, yet their performance in low-resource languages is hindered by insufficient multilingual data during pre-training. To address this, we …","url":["https://arxiv.org/pdf/2407.05975"]}
{"year":"2024","title":"LLM and RAG-Based Question Answering Assistant for Enterprise Knowledge Management","authors":["G Şahin, K Varol, BK Pak - 2024 9th International Conference on Computer …, 2024"],"snippet":"Large language models (LLM) have become integral to many natural language processing applications, particularly in the area of automatic question answering. In this study, a question answering system was developed to enable Adesso Turkiye …","url":["https://ieeexplore.ieee.org/abstract/document/10773564/"]}
{"year":"2024","title":"LLM-Assistance for Quality Control of LLM Output","authors":["K Sandkuhl - Perspectives in Business Informatics Research: 23rd …"],"snippet":"… GPT-3, the model behind ChatGPT, operates with 175 billion parameters and utilizes datasets that include nearly a trillion words sourced from various corpora, such as the Common Crawl, WebText2, internet-based books, and the English …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=sY0gEQAAQBAJ&oi=fnd&pg=PA36&dq=commoncrawl&ots=7ATobvYXgl&sig=RJV3xH5raqRU8u_MUvAQUaj0VrM"]}
{"year":"2024","title":"LLM-Based Edge Intelligence: A Comprehensive Survey on Architectures, Applications, Security and Trustworthiness","authors":["O Friha, MA Ferrag, B Kantarci, B Cakmak, A Ozgun… - IEEE Open Journal of the …, 2024"],"snippet":"The integration of Large Language Models (LLMs) and Edge Intelligence (EI) introduces a groundbreaking paradigm for intelligent edge devices. With their capacity for human-like language processing and generation, LLMs empower edge …","url":["https://ieeexplore.ieee.org/iel8/8782661/8901158/10669603.pdf"]}
{"year":"2024","title":"LLM-Datasets: An Open Framework for Pretraining Datasets of Large Language Models","authors":["M Ostendorff, PO Suarez, LF Lage, G Rehm"],"snippet":"… All of the numbers are given by Common Crawl dump. … 2 show the number of documents by both date of the CommonCrawl dump and language, the percentage of documents removed at each filtering step, and the final document and token …","url":["https://ostendorff.org/assets/pdf/ostendorff2024-preprint.pdf"]}
{"year":"2024","title":"LLM-jp: A Cross-organizational Project for the Research and Development of Fully Open Japanese LLMs","authors":["A Aizawa, E Aramaki, B Chen, F Cheng, H Deguchi… - arXiv preprint arXiv …, 2024"],"snippet":"… The statistics of the Japanese corpus from Common Crawl dumps are presented in Figure 2. We used the publicly available Common Crawl dumps from 2013 to the middle of 2023. We merged the Common Crawl dumps from 2013 to 2016 because …","url":["https://arxiv.org/pdf/2407.03963"]}
{"year":"2024","title":"LLM2LLM: Boosting LLMs with Novel Iterative Data Enhancement","authors":["N Lee, T Wattanawong, S Kim, K Mangalam, S Shen… - arXiv preprint arXiv …, 2024"],"snippet":"… We assume that we are given an LLM model M (eg, GPT-3.5 or LLaMA2-7B) that is pre-trained on some source dataset (eg, Common Crawl). The goal is to adapt M (hereon called the student model) to a new target domain by using a small seed dataset D …","url":["https://arxiv.org/pdf/2403.15042"]}
{"year":"2024","title":"LLM4Schema. org: Generating Schema. org Markups with Large Language Models","authors":["MH Dang, THT Pham, P Molli, H Skaf-Molli, A Gaignard"],"snippet":"The integration of Schema. org markup in web pages has resulted in the creation of billions of RDF triples, yet approximately 75% of all web pages still lack these essential markups. Large Language Models (LLMs) offer a potential solution by …","url":["https://www.semantic-web-journal.net/system/files/swj3716.pdf"]}
{"year":"2024","title":"LLMs achieve adult human performance on higher-order theory of mind tasks","authors":["W Street, JO Siy, G Keeling, A Baranes, B Barnett… - arXiv preprint arXiv …, 2024"],"snippet":"This paper examines the extent to which large language models (LLMs) have developed higher-order theory of mind (ToM); the human ability to reason about multiple mental and emotional states in a recursive manner (eg I think that you …","url":["https://arxiv.org/pdf/2405.18870"]}
{"year":"2024","title":"LLMs for Low Resource Languages in Multilingual, Multimodal and Dialectal Settings","authors":["F Alam, SA Chowdhury, S Boughorbel, M Hasanain - … of the 18th Conference of the …, 2024"],"snippet":"The recent breakthroughs in Artificial Intelligence (AI) can be attributed to the remarkable performance of Large Language Models (LLMs) across a spectrum of research areas (eg, machine translation, question-answering, automatic speech …","url":["https://aclanthology.org/2024.eacl-tutorials.5.pdf"]}
{"year":"2024","title":"LLMs Still Can't Avoid Instanceof: An Investigation Into GPT-3.5, GPT-4 and Bard's Capacity to Handle Object-Oriented Programming Assignments","authors":["BP Cipriano, P Alves - arXiv preprint arXiv:2403.06254, 2024"],"snippet":"… are high-level descriptions of the training datasets (eg a filtered version of Common Crawl 14, English Wikipedia, among others) [3], it was not possible to perform this analysis for those models. 13https:github.com/camilaabrantes/CursoJava …","url":["https://arxiv.org/pdf/2403.06254"]}
{"year":"2024","title":"LLMs: A Comprehensive Survey of Applications, Challenges, Datasets, Models, Limitations, and Future Prospects","authors":["MU Hadi, Q Al-Tashi, R Qureshi, A Shah, A Muneer…"],"snippet":"Within the vast expanse of computerized language processing, a revolutionary entity known as Large Language Models (LLMs) has emerged, wielding immense power in its capacity to comprehend intricate linguistic patterns and conjure coherent and …","url":["https://www.researchgate.net/profile/Syed-Hassan-130/publication/383818024_Large_Language_Models_A_Comprehensive_Survey_of_its_Applications_Challenges_Limitations_and_Future_Prospects/links/66ecf315750edb3bea5ebf3a/Large-Language-Models-A-Comprehensive-Survey-of-its-Applications-Challenges-Limitations-and-Future-Prospects.pdf"]}
{"year":"2024","title":"LMaaS: Exploring Pricing Strategy of Large Model as a Service for Communication","authors":["P Wu, Q Liu, Y Dong, F Wang - arXiv preprint arXiv:2401.02675, 2024"],"snippet":"The next generation of communication is envisioned to be intelligent communication, that can replace traditional symbolic communication, where highly condensed semantic information considering both source and channel will be extracted and …","url":["https://arxiv.org/pdf/2401.02675"]}
{"year":"2024","title":"LMCK: pre-trained language models enhanced with contextual knowledge for Vietnamese natural language inference","authors":["NLT Nguyen, KTK Phan, TV Huynh, KV Nguyen - Multimedia Tools and Applications, 2024"],"snippet":"… trained with a cross-lingual masked language modeling objective on data in 100 languages, including Vietnamese from Common Crawl. … a combination of span masking and sentence shuffling objectives on a subset of 25 languages, including …","url":["https://link.springer.com/article/10.1007/s11042-024-19671-1"]}
{"year":"2024","title":"LogogramNLP: Comparing Visual and Textual Representations of Ancient Logographic Writing Systems for NLP","authors":["D Chen, F Shi, A Agarwal, J Myerston… - arXiv preprint arXiv …, 2024"],"snippet":"… 2023), a pixel-based language model pre-trained on the Common Crawl dataset with a masked image modeling objective, to encode the … Among the aforementioned models, T5, ByT5, and PIXEL are pre-trained on large-scale text …","url":["https://arxiv.org/pdf/2408.04628"]}
{"year":"2024","title":"Long-input summarization using Large Language Models","authors":["E Järvinen - 2024"],"snippet":"… the colossal and cleaned version of common crawl CNN … T5 was pre-trained on the C4 (The Colossal and Cleaned version of Common Crawl) dataset. C4 contains text from 350M web pages; the dataset is 750 GB. A maximum sequence length of …","url":["https://aaltodoc.aalto.fi/bitstreams/cd47964e-5b5e-4af0-9af4-731970184358/download"]}
{"year":"2024","title":"Long-Term Ad Memorability: Understanding & Generating Memorable Ads","authors":["SI Harini, S Singh, Y Kumar, A Bhattacharyya, V Baths…"],"snippet":"Marketers spend billions of dollars on advertisements, but to what end? At purchase time, if customers cannot recognize the brand for which they saw an ad, the money spent on the ad is essentially wasted. Despite its importance in marketing, until now …","url":["https://www.researchgate.net/profile/Yaman-Singla/publication/373642219_Long-Term_Ad_Memorability_Understanding_Generating_Memorable_Ads/links/6645020b0b0d2845743647cc/Long-Term-Ad-Memorability-Understanding-Generating-Memorable-Ads.pdf"]}
{"year":"2024","title":"LongWanjuan: Towards Systematic Measurement for Long Text Quality","authors":["K Lv, X Liu, Q Guo, H Yan, C He, X Qiu, D Lin - arXiv preprint arXiv:2402.13583, 2024"],"snippet":"… In the English data, the CommonCrawl domain predominates, accounting for over 50% of the data. Apart from a significant amount of aggregated texts in the CommonCrawl domain, the majority of data in other domains consists of holistic texts …","url":["https://arxiv.org/pdf/2402.13583"]}
{"year":"2024","title":"Look Ahead or Look Around? A Theoretical Comparison Between Autoregressive and Masked Pretraining","authors":["Q Zhang, T Du, H Huang, Y Wang, Y Wang - Forty-first International Conference on Machine …"],"snippet":"In recent years, the rise of generative self-supervised learning (SSL) paradigms has exhibited impressive performance across visual, language, and multi-modal domains. While the varied designs of generative SSL objectives lead to distinct properties in …","url":["https://openreview.net/pdf?id=2rPoTgEmjV"]}
{"year":"2024","title":"Look Hear: Gaze Prediction for Speech-directed Human Attention","authors":["S Mondal, S Ahn, Z Yang, N Balasubramanian… - arXiv preprint arXiv …, 2024"],"snippet":"For computer systems to effectively interact with humans using spoken language, they need to understand how the words being generated affect the users' moment-by-moment attention. Our study focuses on the incremental prediction of attention as a person is …","url":["https://arxiv.org/pdf/2407.19605"]}
{"year":"2024","title":"LoQT: Low-Rank Adapters for Quantized Pretraining","authors":["SB Loeschcke, M Toftrup, M Kastoryano, S Belongie… - The Thirty-eighth Annual …"],"snippet":"Despite advances using low-rank adapters and quantization, pretraining of large models on consumer hardware has not been possible without model sharding, offloading during training, or per-layer gradient updates. To address these limitations …","url":["https://openreview.net/pdf?id=Pnv8C0bU9t"]}
{"year":"2024","title":"LoRA-Enhanced Language Alignments for Robust Code-Mixed Text Representation","authors":["X Ran, Y Zhang, J Wang, D Xu, X Zhang - 2024 International Joint Conference on …, 2024"],"snippet":"… • XLM-RoBERTa-Large [3] is a multilingual version of RoBERTa, which is pre-trained on a filtered Common Crawl dataset containing 100 languages. • XMFGM [31] applies adversarial training to construct some adversarial samples via adding …","url":["https://ieeexplore.ieee.org/abstract/document/10651379/"]}
{"year":"2024","title":"LoRA-Guard: Parameter-Efficient Guardrail Adaptation for Content Moderation of Large Language Models","authors":["H Elesedy, PM Esperança, SV Oprea, M Ozay - arXiv preprint arXiv:2407.02987, 2024"],"snippet":"Guardrails have emerged as an alternative to safety alignment for content moderation of large language models (LLMs). Existing model-based guardrails have not been designed for resource-constrained computational portable devices, such …","url":["https://arxiv.org/pdf/2407.02987"]}
{"year":"2024","title":"Lory: Fully Differentiable Mixture-of-Experts for Autoregressive Language Model Pre-training","authors":["Z Zhong, M Xia, D Chen, M Lewis - arXiv preprint arXiv:2405.03133, 2024"],"snippet":"… We suspect that segment-level routing may be particularly effective at handling out-of-domain evaluation data (we assume that there is only a very small part of Python code in Commoncrawl). Our analysis in Section 5.4 shows that segment-level routing …","url":["https://arxiv.org/pdf/2405.03133"]}
{"year":"2024","title":"Low-Complexity and Secure Clustering-Based Similarity Detection for Private Files","authors":["DF Najem, VO Nyangaresi - 2024"],"snippet":"Detection of the similarity between files is a requirement for many practical applications, such as copyright protection, file management, plagiarism detection, and detecting duplicate submissions of scientific articles to multiple journals or …","url":["https://www.temjournal.com/content/133/TEMJournalAugust2024_2341_2349.pdf"]}
{"year":"2024","title":"LP Data Pipeline: Lightweight, Purpose-driven Data Pipeline for Large Language Models","authors":["Y Kim, H Ha, S Yang, S Lee, J Kim, C Park - arXiv preprint arXiv:2411.11289, 2024"],"snippet":"… To validate the feasibility of the LP Data Pipeline with large-scale datasets, we conducted experiments using actual CommonCrawl dumps, focusing on key metrics such as processing time and estimated cost. The results demonstrate the pipeline’s …","url":["https://arxiv.org/pdf/2411.11289"]}
{"year":"2024","title":"LSHBloom: Memory-efficient, Extreme-scale Document Deduplication","authors":["A Khan, R Underwood, C Siebenschuh, Y Babuji… - arXiv preprint arXiv …, 2024"],"snippet":"… 2020) (CCNET) is an automated preprocessing pipeline that aims to extract high-quality monolingual language datasets from the Common Crawl corpus of Web content. CCNet performs dataset sharding, deduplication, language identification, and …","url":["https://arxiv.org/pdf/2411.04257"]}
{"year":"2024","title":"M2SA: Multimodal and Multilingual Model for Sentiment Analysis of Tweets","authors":["G Thakkar, S Hakimov, M Tadić - arXiv preprint arXiv:2404.01753, 2024"],"snippet":"… 2020b) is a large multilingual language model trained on 2.5 TB of filtered Common Crawl data containing 100 languages. The model was trained with the Masked Language Modelling (MLM) objective, with 15% of the input words masked …","url":["https://arxiv.org/pdf/2404.01753"]}
{"year":"2024","title":"Machine learning and natural language processing to assess the emotional impact of influencers' mental health content on Instagram","authors":["N Merayo, A Ayuso-Lanchares, C González-Sanguino - PeerJ Computer Science, 2024"],"snippet":"Background This study aims to examine, through artificial intelligence, specifically machine learning, the emotional impact generated by disclosures about mental health on social media. In contrast to previous research, which primarily focused on …","url":["https://peerj.com/articles/cs-2251/"]}
{"year":"2024","title":"Machine Learning and Neural NLG","authors":["E Reiter - Natural Language Generation, 2024"],"snippet":"This chapter gives an overview of machine learning and neural approaches to NLG, including language models. Because this area is changing very rapidly, the focus is on giving a high-level overview of basic concepts behind models and then …","url":["https://link.springer.com/chapter/10.1007/978-3-031-68582-8_3"]}
{"year":"2024","title":"Machine Learning and the Analysis of Culture","authors":["S Mützel, É Ollion - 2024"],"snippet":"The focus of this chapter is on how machine learning (ML) impacts the analysis of culture in sociology. It shows how ML has greatly advanced the analysis of culture, with new tools enabling a massive and fine-grained extraction of information from …","url":["https://osf.io/nvtp2/download"]}
{"year":"2024","title":"Machine Translation that Peeks at the Reference","authors":["V Zouhar"],"snippet":"Abstract Machine translation with lexical constraints is a popular research topic, especially for terminology translation. Existing approaches for lexical control in MT are usually complex and not easily applicable to all existing MT toolkits. We propose …","url":["https://vilda.net/papers/mt_peek.pdf"]}
{"year":"2024","title":"Machine-Learning Phishing Detection Model Used in the E-Banking Environment","authors":["M Manala, J Jansen van Vuuren - IFIP International Conference on Human Choice …, 2024"],"snippet":"… Rashid, Mahmood [20] proposed a machine-learning approach that uses Alexa and the Common Crawl archive dataset with 5000 URLs. … Geyik, Erensoy [21] used the PhishTank Alexa Common-Crawl datasets. The performance attained …","url":["https://link.springer.com/chapter/10.1007/978-3-031-67535-5_7"]}
{"year":"2024","title":"Machines Do See Color: A Guideline to Classify Different Forms of Racist Discourse in Large Corpora","authors":["DD Gordillo, J Timoneda, SV Vera - arXiv preprint arXiv:2401.09333, 2024"],"snippet":"Current methods to identify and classify racist language in text rely on small-n qualitative approaches or large-n approaches focusing exclusively on overt forms of racist discourse. This article provides a step-by-step generalizable guideline to …","url":["https://arxiv.org/pdf/2401.09333"]}
{"year":"2024","title":"MagicLens: Self-Supervised Image Retrieval with Open-Ended Instructions","authors":["K Zhang, Y Luan, H Hu, K Lee, S Qiao, W Chen, Y Su… - arXiv preprint arXiv …, 2024"],"snippet":"… We collect all images with the same URL from Common Crawl2 as a group of images from the same web page for potential pairing. Due to the inevitable noisy images introduced by simple grouping, we remove duplicated, low-resolution, and …","url":["https://arxiv.org/pdf/2403.19651"]}
{"year":"2024","title":"MAiDE-up: Multilingual Deception Detection of GPT-generated Hotel Reviews","authors":["O Ignat, X Xu, R Mihalcea - arXiv preprint arXiv:2404.12938, 2024"],"snippet":"Deceptive reviews are becoming increasingly common, especially given the increase in performance and the prevalence of LLMs. While work to date has addressed the development of models to differentiate between truthful and …","url":["https://arxiv.org/pdf/2404.12938"]}
{"year":"2024","title":"MaiNLP at SemEval-2024 Task 1: Analyzing Source Language Selection in Cross-Lingual Textual Relatedness","authors":["S Zhou, H Shan, B Plank, R Litschko - arXiv preprint arXiv:2404.02570, 2024"],"snippet":"This paper presents our system developed for the SemEval-2024 Task 1: Semantic Textual Relatedness (STR), on Track C: Cross-lingual. The task aims to detect semantic relatedness of two sentences in a given target language without access to …","url":["https://arxiv.org/pdf/2404.02570"]}
{"year":"2024","title":"MAKG: A maritime accident knowledge graph for intelligent accident analysis and management","authors":["D Liu, L Cheng - Ocean Engineering, 2024"],"snippet":"With the increasing frequency of human activities at sea, maritime accidents are occurring more often. Analyzing and mining maritime accident cases can help uncover the causal mechanisms behind these incidents, thereby enhancing …","url":["https://www.sciencedirect.com/science/article/pii/S0029801824026180"]}
{"year":"2024","title":"Making Javascript Render Decisions to Optimize Security-Oriented Crawler Process","authors":["O Aktas, AB Can - IEEE Access, 2024"],"snippet":"… They indicate that if their method had applied to the July 2015 Common Crawl dataset, a web-scale archival crawler would have discovered an additional 7.17 PB (5.12 times more) of information per year. However, rendering JavaScript and using client-side …","url":["https://ieeexplore.ieee.org/iel8/6287639/6514899/10719995.pdf"]}
{"year":"2024","title":"MambaByte: Token-free Selective State Space Model","authors":["J Wang, T Gangavarapu, JN Yan, AM Rush - arXiv preprint arXiv:2401.13660, 2024"],"snippet":"Token-free language models learn directly from raw bytes and remove the bias of subword tokenization. Operating on bytes, however, results in significantly longer sequences, and standard autoregressive Transformers scale poorly in such settings …","url":["https://arxiv.org/pdf/2401.13660"]}
{"year":"2024","title":"MAmmoTH2: Scaling Instructions from the Web","authors":["X Yue, T Zheng, G Zhang, W Chen - arXiv preprint arXiv:2405.03548, 2024"],"snippet":"… We argue that the pre-training corpus (eg, Common Crawl) already contains a vast amount of high-quality instruction data for LLM reasoning. For example, the web corpus contains a large amount of educational materials in the form of instruction-following …","url":["https://arxiv.org/pdf/2405.03548"]}
{"year":"2024","title":"MAP-Neo: Highly Capable and Transparent Bilingual Large Language Model Series","authors":["G Zhang, S Qu, J Liu, C Zhang, C Lin, CL Yu, D Pan… - arXiv preprint arXiv …, 2024"],"snippet":"… Inspired by [89], which adopts an iterative pipeline to facilitate the acquisition of large-scale, high-quality data from Common Crawl, we propose to select high-quality data for mathematics, scientific exam synthetic data, and wiki-based content in our Matrix. …","url":["https://arxiv.org/pdf/2405.19327"]}
{"year":"2024","title":"Mapping the media landscape: predicting factual reporting and political bias through web interactions","authors":["D Sánchez-Cortés, S Burdisso, E Villatoro-Tello… - International Conference of …, 2024","P Motlicek"],"snippet":"… In this work we used the graph G built in [8] consisting of 17K news sources obtained after processing 100M news articles from Common Crawl News. Following [3, 8] we report 5-fold cross-validation evaluation results on our MBFC datasets …","url":["https://link.springer.com/chapter/10.1007/978-3-031-71736-9_7","https://publications.idiap.ch/attachments/papers/2024/Sanchez-Cortes_CLEF2024_2024.pdf"]}
{"year":"2024","title":"Mapping the Positive Self-Bias Embedded in Human Languages","authors":["Y Zhang, F Zou, S Jia, F Wang"],"snippet":"… Here, we employed the fastText algorithm 62, pre-trained on the Common Crawl and Wikipedia corpora, for the analyses across Studies 1a-c. We opted for this model due to its leading performance, widespread acceptance, and multilingual …","url":["https://osf.io/mnv37/download"]}
{"year":"2024","title":"MapPool-Bubbling up an extremely large corpus of maps for AI","authors":["R Schnürer - 2024 ICA Workshop on AI, Geovisualization, and …, 2024"],"snippet":"MapPool is a dataset of 75 million potential maps and textual captions. It has been derived from CommonPool, a dataset consisting of 12 billion text-image pairs from the Internet. The images have been encoded by a vision transformer and classified …","url":["https://infoscience.epfl.ch/bitstreams/6e8eef7c-95e9-48cc-b2d6-39b43ea6d68d/download"]}
{"year":"2024","title":"Marco-LLM: Bridging Languages via Massive Multilingual Training for Cross-Lingual Enhancement","authors":["L Ming, B Zeng, C Lyu, T Shi, Y Zhao, X Yang, Y Liu… - arXiv preprint arXiv …, 2024"],"snippet":"… First of all, we extract the main contents from the raw Common Crawl (WARC) files. Meanwhile, we perform URL filter and language identification to avoid subsequent computationally expensive processing. The former targets fraudulent and/or adult …","url":["https://arxiv.org/pdf/2412.04003"]}
{"year":"2024","title":"Massively Multi-Cultural Knowledge Acquisition & LM Benchmarking","authors":["Y Fung, R Zhao, J Doo, C Sun, H Ji - arXiv preprint arXiv:2402.09369, 2024"],"snippet":"Pretrained large language models have revolutionized many applications but still face challenges related to cultural bias and a lack of cultural commonsense knowledge crucial for guiding cross-culture communication and interactions …","url":["https://arxiv.org/pdf/2402.09369"]}
{"year":"2024","title":"MASTER THESIS Large-scale product classification for efficient matching in procurement systems","authors":["IHS GRONDAHL"],"snippet":"… Peeters, and Bizer, 2019 is compiled based on open data from the Common Crawl … 1https://commoncrawl.org/ … available Common Crawl and Wikipedia datasets. For our experiments, we have …","url":["https://er.ucu.edu.ua/server/api/core/bitstreams/5774cb47-43f6-4a86-bd97-0f01dc0ea295/content"]}
{"year":"2024","title":"MASTERARBEIT/MASTER'S THESIS","authors":["S Jang - 2023"],"snippet":"Today, a huge amount of unstructured data from various sources is available. Natural language processing (NLP) techniques using such data are applied to several tasks such as named entity recognition (NER). This study is designed to …","url":["https://phaidra.univie.ac.at/detail/o:1637602.pdf"]}
{"year":"2024","title":"MASTERARBEIT| MASTER'S THESIS","authors":["K Niederreiter - 2024"],"snippet":"The exponential growth of the social media user base has led to an alarming rise in the use of offensive language and profanity, necessitating effective detection mechanisms. This thesis explores the challenges and advancements in automatic …","url":["https://phaidra.univie.ac.at/detail/o:2080697.pdf"]}
{"year":"2024","title":"Mastering Transformers: The Journey from BERT to Large Language Models and Stable Diffusion","authors":["S Yıldırım, M Asgari-Chenaghlu - 2024"],"snippet":"Explore transformer-based language models from BERT to GPT, delving into NLP and computer vision tasks, while tackling challenges effectively Key Features Understand the complexity of deep learning architecture and transformers …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=M_wJEQAAQBAJ&oi=fnd&pg=PP1&dq=commoncrawl&ots=avP-WYfjWC&sig=KVeolFlauPbA8bVyuAQyJTiTH4Y"]}
{"year":"2024","title":"MaTElDa: Multi-Table Error Detection","authors":["F Ahmadi, M Speckmann, MF Kuhlmann, Z Abedjan - 2025"],"snippet":"… WDC Web Table Corpus: We randomly picked 100 Englishlanguage relational webtables out of the massive collection of over 233 million tables derived from the July 2015 version of the CommonCrawl [30] to measure the effectiveness of our …","url":["https://openproceedings.org/2025/conf/edbt/paper-98.pdf"]}
{"year":"2024","title":"Materials science in the era of large language models: a perspective","authors":["G Lei, R Docherty, SJ Cooper - arXiv preprint arXiv:2403.06949, 2024"],"snippet":"Large Language Models (LLMs) have garnered considerable interest due to their impressive natural language capabilities, which in conjunction with various emergent properties make them versatile tools in workflows ranging from complex …","url":["https://arxiv.org/pdf/2403.06949"]}
{"year":"2024","title":"MathCoder2: Better Math Reasoning from Continued Pretraining on Model-translated Mathematical Code","authors":["Z Lu, A Zhou, K Wang, H Ren, W Shi, J Pan, M Zhan… - arXiv preprint arXiv …, 2024"],"snippet":"… We first use a fastText classifier to filter the Common Crawl corpus, resulting in the initial filtered math texts. Then, we annotate part of the filtered texts to train a new fastText classifier, and conduct a second filtering, resulting in the finer filtered math …","url":["https://arxiv.org/pdf/2410.08196"]}
{"year":"2024","title":"MathPile: A Billion-Token-Scale Pretraining Corpus for Math","authors":["Z Wang, X Li, R Xia, P Liu - The Thirty-eight Conference on Neural Information …"],"snippet":"… , especially given the vast size of the Common Crawl corpus . We also experimented with more intricate … -CommonCrawl, totaling approximately 633 million tokens. We acknowledge the potential for more efficient methods to sift …","url":["https://openreview.net/pdf?id=RSvhU69sbG"]}
{"year":"2024","title":"Matthew Coscia and","authors":["A Weber"],"snippet":"… URL: https://github.com/commoncrawl/ia-web-commons. [9] Image Details - Container Registry - Google Cloud Platform. 2022. …","url":["https://vtechworks.lib.vt.edu/server/api/core/bitstreams/42cd566c-369f-44c1-afff-4cc3e6a2fb00/content"]}
{"year":"2024","title":"Maximize Your Data's Potential: Enhancing LLM Accuracy with Two-Phase Pretraining","authors":["S Feng, S Prabhumoye, K Kong, D Su, M Patwary… - arXiv preprint arXiv …, 2024"],"snippet":"… 2024a) mentions that web crawl documents like Common Crawl (CC) form a large majority of their pretraining data, none of them share a recipe on how to mix different slices of CC. … The overall percentage of the Common Crawl Snapshots in …","url":["https://arxiv.org/pdf/2412.15285"]}
{"year":"2024","title":"McGill NLP Group Submission to the MRL 2024 Shared Task: Ensembling Enhances Effectiveness of Multilingual Small LMs","authors":["S Li, H Yu, J Ojo, D Adelani - Proceedings of the Fourth Workshop on Multilingual …, 2024"],"snippet":"… mT5 is pre-trained on a massive multilingual dataset covering 101 languages from the Common Crawl corpus, which enables it to perform a wide range of natural language processing tasks. It operates using a text-to-text framework, where all …","url":["https://aclanthology.org/2024.mrl-1.28.pdf"]}
{"year":"2024","title":"MDSAA","authors":["IRVG Roque"],"snippet":"In the field of digital marketing, efficient content gap analysis is crucial for developing effective SEO strategies. Traditional approaches to this task are time-consuming, representing a challenge for Organic Performance teams, who must process large …","url":["https://run.unl.pt/bitstream/10362/164588/1/TCDMAA1449.pdf"]}
{"year":"2024","title":"Measuring and Enhancing Trustworthiness of LLMs in RAG through Grounded Attributions and Learning to Refuse","authors":["M Song, SH Sim, R Bhardwaj, HL Chieu, N Majumder… - arXiv preprint arXiv …, 2024"],"snippet":"… To do this, we query Wikipedia and Common Crawl to retrieve the 100 most relevant documents. We filter seed question for which the retriever fails to retrieve relevant documents. Furthermore, we identify 5 documents that are equally effective …","url":["https://arxiv.org/pdf/2409.11242"]}
{"year":"2024","title":"Measuring and Improving the Energy Efficiency of Large Language Models Inference","authors":["MF Argerich, M Patiño-Martínez - IEEE Access, 2024"],"snippet":"… 4) RedPajama [42]: another family of models based on Pythia with 7B and 3B parameters, fine-tuned on a dataset with the same name as the model, with over 100B text documents coming from 84 CommonCrawl snapshots. Similar to Dolly …","url":["https://ieeexplore.ieee.org/iel8/6287639/6514899/10549890.pdf"]}
{"year":"2024","title":"Measuring Bias of Web-filtered Text Datasets and Bias Propagation Through Training","authors":["Y Mansour, R Heckel - arXiv preprint arXiv:2412.02857, 2024"],"snippet":"… Thus all of the datasets we consider for LLM training are obtained by the dataset creators by extracting text from CommonCrawl data… CommonCrawl. We consider the CommonCrawl part, which was obtained by first downloading about a quarter of …","url":["https://arxiv.org/pdf/2412.02857"]}
{"year":"2024","title":"Measuring complex psychological and sociological constructs in large-scale text","authors":["A Herderich, J Lasser, S Aroyehun, D Garcia…"],"snippet":"In recent years, there has been an increasing exchange between social and computational sciences. Methods from natural language processing enable social scientists to systematically process large amounts of text. Rich psycho-sociological …","url":["https://files.de-1.osf.io/v1/resources/tzc9p/providers/osfstorage/66aaf8ae5827b357732edfde?action=download&direct&version=1"]}
{"year":"2024","title":"Measuring Contextual Informativeness in Child-Directed Text","authors":["M Valentini, T Wright, A Marashian, J Weber… - arXiv preprint arXiv …, 2024"],"snippet":"To address an important gap in creating children's stories for vocabulary enrichment, we investigate the automatic evaluation of how well stories convey the semantics of target vocabulary words, a task with substantial implications for generating …","url":["https://arxiv.org/pdf/2412.17427"]}
{"year":"2024","title":"Measuring individual semantic networks: A simulation study","authors":["S Aeschbach, R Mata, DU Wulff - arXiv preprint arXiv:2410.18326, 2024"],"snippet":"Accurately capturing individual differences in semantic networks is fundamental to advancing our mechanistic understanding of semantic memory. Past empirical attempts to construct individual-level semantic networks from behavioral paradigms …","url":["https://arxiv.org/pdf/2410.18326"]}
{"year":"2024","title":"Medical Concept Normalization in a Low-Resource Setting","authors":["T Patzelt - arXiv preprint arXiv:2409.14579, 2024"],"snippet":"… The multilingual RoBERTa model, RoBERTaXLM, by conneau_unsupervised_2020 was trained on more than two terabytes of filtered Common Crawl (wenzek_ccnet_2020) data. The Common Crawl dataset is a …","url":["https://arxiv.org/pdf/2409.14579"]}
{"year":"2024","title":"Medical mT5: An Open-Source Multilingual Text-to-Text LLM for The Medical Domain","authors":["I García-Ferrero, R Agerri, AA Salazar, E Cabrio… - arXiv preprint arXiv …, 2024"],"snippet":"… mT5 was trained using mC4, a 1 Trillion token Common Crawl-based dataset covering 101 languages. The pre-training is based on a masked language modeling “spancorruption” objective, where consecutive spans of input tokens are replaced …","url":["https://arxiv.org/pdf/2404.07613"]}
{"year":"2024","title":"MedQAS: A Medical Question Answering System Based on Finetuning Large Language Models","authors":["BT Duong, TH Le - International Conference on Future Data and Security …, 2024"],"snippet":"… Specifically, LLaMA was trained on 1.0 trillion tokens from publicly accessible data sources such as CommonCrawl and arXiv [6]. They fine-tuned the LLaMA model using conversations from HealthCareMagic-100k [15] following the Stanford …","url":["https://link.springer.com/chapter/10.1007/978-981-96-0434-0_21"]}
{"year":"2024","title":"Meeting the challenge: A benchmark corpus for automated Urdu meeting summarization","authors":["B Sadia, F Adeeba, S Shams, K Javed - Information Processing & Management, 2024"],"snippet":"Meeting summarization has become crucial as the world is gradually shifting towards remote work. Nowadays, automation of meeting summary generation is really needed in order to minimize the time and effort. The surge in online meetings …","url":["https://www.sciencedirect.com/science/article/pii/S0306457324000943"]}
{"year":"2024","title":"MELTing point: Mobile Evaluation of Language Transformers","authors":["S Laskaridis, K Kateveas, L Minto, H Haddadi - arXiv preprint arXiv:2403.12844, 2024"],"snippet":"Transformers have revolutionized the machine learning landscape, gradually making their way into everyday tasks and equipping our computers with ``sparks of intelligence''. However, their runtime requirements have prevented them from being …","url":["https://arxiv.org/pdf/2403.12844"]}
{"year":"2024","title":"Memorization and Privacy Risks in Domain-Specific Large Language Models","authors":["X Yang, Z Wen, W Qu, Z Chen, Z Xiang, B Chen, H Yao - ICLR 2024 Workshop on Reliable …"],"snippet":"… Common Crawl3 is a nonprofit organization that provides a large and open web crawl data repository for public use. It collects web pages from the internet every month and stores them on Amazon Web Services. Common Crawl’s … C4 cleanses …","url":["https://openreview.net/pdf?id=KmW8WkCKRx"]}
{"year":"2024","title":"Mentions of prejudice in news media–an international comparison","authors":["D Rozado - Journal of Computational Social Science, 2024"],"snippet":"Previous research has identified a post-2010 sharp increase of terms used to denounce prejudice (ie racism, sexism, homophobia, Islamophobia, anti-Semitism, etc.) in US and UK news media content. Here, we extend previous analysis to an …","url":["https://link.springer.com/article/10.1007/s42001-024-00295-2"]}
{"year":"2024","title":"MeSH2Matrix: Combining MeSH keywords and machine learning for biomedical relation classification based on PubMed","authors":["H Turki, BFP Dossou, CC Emezue, A Toluwase…"],"snippet":"Biomedical relation classification has been significantly improved by the application of advanced machine learning techniques on the raw texts of scholarly publications. Despite this improvement, the reliance on large chunks of raw text makes these …","url":["https://www.researchgate.net/profile/Houcemeddine-Turki/publication/383738915_MeSH2Matrix_Combining_MeSH_keywords_and_machine_learning_for_biomedical_relation_classification_based_on_PubMed/links/66d836172390e50b2c523024/MeSH2Matrix-Combining-MeSH-keywords-and-machine-learning-for-biomedical-relation-classification-based-on-PubMed.pdf"]}
{"year":"2024","title":"MetaphorShare: A Dynamic Collaborative Repository of Open Metaphor Datasets","authors":["J Boisson, A Mehmood, J Camacho-Collados - arXiv preprint arXiv:2411.18260, 2024"],"snippet":"The metaphor studies community has developed numerous valuable labelled corpora in various languages over the years. Many of these resources are not only unknown to the NLP community, but are also often not easily shared among the …","url":["https://arxiv.org/pdf/2411.18260"]}
{"year":"2024","title":"Methodological and practical challenges of doing transnational studies","authors":["N Brügger - The Routledge Companion to Transnational Web …, 2024"],"snippet":"… collections such as the Internet Archive or Common Crawl, or holdings of other national web … establishment of the web archive, whereas using the Common Crawl is uncharted territory. … for both the Internet Archive and the Common Crawl …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=RLYyEQAAQBAJ&oi=fnd&pg=PA93&dq=commoncrawl&ots=ebVn40Yl74&sig=nGYnlZ9dHpBu08bkfTtqeUTRbns"]}
{"year":"2024","title":"Methods and Applications for Probing Deep Neural Networks","authors":["Z Zhu - 2024"],"snippet":"In recent years, the impressive abilities shown by deep neural network (DNN)-based systems have led to the curiosity towards the intrinsic mechanisms. The query towards these mechanisms has led to an emerging field, model interpretation. In this …","url":["https://tspace.library.utoronto.ca/bitstream/1807/139626/2/Zhu_Zining_202406_PhD_thesis.pdf"]}
{"year":"2024","title":"Methods Futures Report–Sea, Sky, and Land: Engaging in Solidarity in Endangered Ecologies–4S Conference Nov 2023","authors":["R Meckin - 2024"],"snippet":"This is a report of the 4S 2023 conference. The 4S (Society for the Social Studies of Science) conference 2023 was a large, disciplinarily diverse gathering with over 400 sessions spread over four days. Navigating a particular route through the conference …","url":["https://eprints.ncrm.ac.uk/id/eprint/4948/1/NCRM%20method%20futures%204S%20conference%20report.pdf"]}
{"year":"2024","title":"Methods to Assess the UK Government's Current Role as a Data Provider for AI","authors":["N Majithia, E Simperl - arXiv preprint arXiv:2412.09632, 2024"],"snippet":"… Each website was present in CommonCrawl datasets before April 2024, therefore sitting in the training window for up-to-date models like Llama 3.1 [13]. The plaintext of each website was requested from the CommonCrawl index server, cleaned …","url":["https://arxiv.org/pdf/2412.09632"]}
{"year":"2024","title":"MEXA: Multilingual Evaluation of English-Centric LLMs via Cross-Lingual Alignment","authors":["AH Kargaran, A Modarressi, N Nikeghbal, J Diesner… - arXiv preprint arXiv …, 2024"],"snippet":"English-centric large language models (LLMs) often show strong multilingual capabilities. However, the multilingual performance of these models remains unclear and is not thoroughly evaluated for many languages. Most benchmarks for …","url":["https://arxiv.org/pdf/2410.05873"]}
{"year":"2024","title":"mGTE: Generalized Long-Context Text Representation and Reranking Models for Multilingual Text Retrieval","authors":["X Zhang, Y Zhang, D Long, W Xie, Z Dai, J Tang, H Lin… - arXiv preprint arXiv …, 2024"],"snippet":"We present systematic efforts in building long-context multilingual text representation model (TRM) and reranker from scratch for text retrieval. We first introduce a text encoder (base size) enhanced with RoPE and unpadding, pre-trained …","url":["https://arxiv.org/pdf/2407.19669"]}
{"year":"2024","title":"mHumanEval--A Multilingual Benchmark to Evaluate Large Language Models for Code Generation","authors":["N Raihan, A Anastasopoulos, M Zampieri - arXiv preprint arXiv:2410.15037, 2024"],"snippet":"Recent advancements in large language models (LLMs) have significantly enhanced code generation from natural language prompts. The HumanEval Benchmark, developed by OpenAI, remains the most widely used code generation …","url":["https://arxiv.org/pdf/2410.15037"]}
{"year":"2024","title":"Milestones in Bengali Sentiment Analysis leveraging Transformer-models: Fundamentals, Challenges and Future Directions","authors":["S Sengupta, S Ghosh, P Mitra, TI Tamiti - arXiv preprint arXiv:2401.07847, 2024"],"snippet":"Sentiment Analysis (SA) refers to the task of associating a view polarity (usually, positive, negative, or neutral; or even fine-grained such as slightly angry, sad, etc.) to a given text, essentially breaking it down to a supervised (since we have the view …","url":["https://arxiv.org/pdf/2401.07847"]}
{"year":"2024","title":"MIND: Math Informed syNthetic Dialogues for Pretraining LLMs","authors":["SN Akter, S Prabhumoye, J Kamalu, S Satheesh… - arXiv preprint arXiv …, 2024"],"snippet":"… OpenWebMath contains 14.7B tokens of mathematical web pages filtered from CommonCrawl based on mathematical strings, … 2016) classifier to further extract mathematical documents from CommonCrawl. They cluster the extracted documents …","url":["https://arxiv.org/pdf/2410.12881"]}
{"year":"2024","title":"MindLLM: Lightweight large language model pre-training, evaluation and domain application","authors":["Y Yang, H Sun, J Li, R Liu, Y Li, Y Liu, Y Gao, H Huang - AI Open, 2024"],"snippet":"Large Language Models (LLMs) have demonstrated remarkable performance across various natural language tasks, marking significant strides towards general artificial intelligence. While general artificial intelligence is leveraged by developing …","url":["https://www.sciencedirect.com/science/article/pii/S2666651024000111"]}
{"year":"2024","title":"Mini-InternVL: A Flexible-Transfer Pocket Multimodal Model with 5% Parameters and 90% Performance","authors":["Z Gao, Z Chen, E Cui, Y Ren, W Wang, J Zhu, H Tian… - arXiv preprint arXiv …, 2024"],"snippet":"Multimodal large language models (MLLMs) have demonstrated impressive performance in vision-language tasks across a broad spectrum of domains. However, the large model scale and associated high computational costs pose significant …","url":["https://arxiv.org/pdf/2410.16261"]}
{"year":"2024","title":"MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategies","authors":["S Hu, Y Tu, X Han, C He, G Cui, X Long, Z Zheng… - arXiv preprint arXiv …, 2024"],"snippet":"The burgeoning interest in developing Large Language Models (LLMs) with up to trillion parameters has been met with concerns regarding resource efficiency and practical expense, particularly given the immense cost of experimentation. This …","url":["https://arxiv.org/pdf/2404.06395"]}
{"year":"2024","title":"MINNESOTA JOURNAL OF LAW, SCIENCE & TECHNOLOGY","authors":["Z Niesel, J Villasenor, J Perl, DE Ho, A Vallebueno"],"snippet":"In administrative law, there is perhaps no more misunderstood phrase than the\" arbitrary and capricious\" standard of judicial review. American administrative law's cornerstone is the judicial review of agency decision-making-a review which has …","url":["https://heinonline.org/hol-cgi-bin/get_pdf.cgi?handle=hein.journals/mipr25&section=19"]}
{"year":"2024","title":"MINT-1T: Scaling Open-Source Multimodal Data by 10x: A Multimodal Dataset with One Trillion Tokens","authors":["A Awadalla, L Xue, O Lo, M Shu, H Lee, EK Guha… - arXiv preprint arXiv …, 2024"],"snippet":"… We follow OBELICS’s method for extracting interleaved multimodal documents from CommonCrawl WARC files by parsing each WARC entry’s DOM tree. While OBELICS only processed documents from February 2020 to February 2023 …","url":["https://arxiv.org/pdf/2406.11271"]}
{"year":"2024","title":"Misinformation Resilient Search Rankings with Webgraph-based Interventions","authors":["P Carragher, EM Williams, KM Carley - arXiv preprint arXiv:2404.08869, 2024"],"snippet":"… To this end, we investigate the distribution of changes in CommonCrawl PageRank as a result of our interventions for all domains in the webgraph, not just news domains. We then take the domains whose PR score changes significantly ( 50%) …","url":["https://arxiv.org/pdf/2404.08869"]}
{"year":"2024","title":"Mission Critical--Satellite Data is a Distinct Modality in Machine Learning","authors":["E Rolf, K Klemmer, C Robinson, H Kerner - arXiv preprint arXiv:2402.01444, 2024"],"snippet":"Satellite data has the potential to inspire a seismic shift for machine learning -- one in which we rethink existing practices designed for traditional data modalities. As machine learning for satellite data (SatML) gains traction for its real-world impact …","url":["https://arxiv.org/pdf/2402.01444"]}
{"year":"2024","title":"Mitigating Catastrophic Forgetting in Language Transfer via Model Merging","authors":["A Alexandrov, V Raychev, MN Müller, C Zhang… - arXiv preprint arXiv …, 2024"],"snippet":"As open-weight large language models (LLMs) achieve ever more impressive performances across a wide range of tasks in English, practitioners aim to adapt these models to different languages. However, such language adaptation is often …","url":["https://arxiv.org/pdf/2407.08699"]}
{"year":"2024","title":"Mitigating Downstream Model Risks via Model Provenance","authors":["K Wang, AN Iranzad, S Schaffter, D Precup… - arXiv preprint arXiv …, 2024"],"snippet":"Research and industry are rapidly advancing the innovation and adoption of foundation model-based systems, yet the tools for managing these models have not kept pace. Understanding the provenance and lineage of models is critical for …","url":["https://arxiv.org/pdf/2410.02230"]}
{"year":"2024","title":"Mitigating the Impact of Adversarial Fine-tuning on Large Language Models through Perturbation Attenuation","authors":["Z Jejesi, A McBride, F Kovacic, L O'Connor - 2024"],"snippet":"The increasing complexity and scale of machine learning models have rendered them vulnerable to adversarial manipulation, particularly during fine-tuning processes where subtle perturbations can lead to significant degradation in model …","url":["https://www.researchsquare.com/article/rs-5046765/latest.pdf"]}
{"year":"2024","title":"Mitigating the negative impact of over-association for conversational query production","authors":["A Wang, L Song, Z Min, G Xu, X Wang, J Yao, J Su - Information Processing & …, 2025"],"snippet":"Conversational query generation aims at producing search queries from dialogue histories, which are then used to retrieve relevant knowledge from a search engine to help knowledge-based dialogue systems. Trained to maximize the likelihood of …","url":["https://www.sciencedirect.com/science/article/pii/S0306457324002668"]}
{"year":"2024","title":"Mitigating the Privacy Issues in Retrieval-Augmented Generation (RAG) via Pure Synthetic Data","authors":["S Zeng, J Zhang, P He, J Ren, T Zheng, H Lu, H Xu… - arXiv preprint arXiv …, 2024"],"snippet":"… 2021), we randomly select segments from the Common Crawl dataset to function as the information component. However, the randomness of the input may affect the command component. To mitigate this issue, we limit the maximum length of the …","url":["https://arxiv.org/pdf/2406.14773"]}
{"year":"2024","title":"MixEval-X: Any-to-Any Evaluations from Real-World Data Mixtures","authors":["J Ni, Y Song, D Ghosal, B Li, DJ Zhang, X Yue, F Xue… - arXiv preprint arXiv …, 2024"],"snippet":"… In this phase, we detected around 20k queries using Vicuna 33B over a subset of Common Crawl. We then used GPT-4 to more accurately … 98%) on our benchmarks and detected 2M user queries from the Common Crawl subset. Finally …","url":["https://arxiv.org/pdf/2410.13754"]}
{"year":"2024","title":"MixEval: Deriving Wisdom of the Crowd from LLM Benchmark Mixtures","authors":["J Ni, F Xue, X Yue, Y Deng, M Shah, K Jain, G Neubig… - arXiv preprint arXiv …, 2024"],"snippet":"… In the detection phase, we train open-source LLMs on self-collected data to detect queries in Common Crawl splits. During filtering, we utilize GPT-4 Turbo to exclude non-query sentences. In classification, we categorize the filtered queries by input …","url":["https://arxiv.org/pdf/2406.06565"]}
{"year":"2024","title":"Mixture of Hidden-Dimensions Transformer","authors":["Y Chen, J Shang, Z Zhang, J Sheng, T Liu, S Wang… - arXiv preprint arXiv …, 2024"],"snippet":"Transformer models encounter challenges in scaling hidden dimensions efficiently, as uniformly increasing them inflates computational and memory costs while failing to emphasize the most relevant features for each token. For further understanding …","url":["https://arxiv.org/pdf/2412.05644"]}
{"year":"2024","title":"ML-EAT: A Multilevel Embedding Association Test for Interpretable and Transparent Social Science","authors":["R Wolfe, A Hiniker, B Howe - arXiv preprint arXiv:2408.01966, 2024"],"snippet":"This research introduces the Multilevel Embedding Association Test (ML-EAT), a method designed for interpretable and transparent measurement of intrinsic bias in language technologies. The ML-EAT addresses issues of ambiguity and difficulty in …","url":["https://arxiv.org/pdf/2408.01966"]}
{"year":"2024","title":"MlingConf: A Comprehensive Study of Multilingual Confidence Estimation on Large Language Models","authors":["B Xue, H Wang, R Wang, S Wang, Z Wang, Y Du… - arXiv preprint arXiv …, 2024"],"snippet":"… 2024) which determines the resource levels for each language by utilizing the data ratio from the CommonCrawl corpus 7, we select three languages (Chinese, Japanese, and French) in high-resource category whose data ratio exceeds 1 …","url":["https://arxiv.org/pdf/2410.12478"]}
{"year":"2024","title":"MM-Eval: A Multilingual Meta-Evaluation Benchmark for LLM-as-a-Judge and Reward Models","authors":["G Son, D Yoon, J Suk, J Aula-Blasco, M Aslan, VT Kim… - arXiv preprint arXiv …, 2024"],"snippet":"Large language models (LLMs) are commonly used as evaluators in tasks (eg, reward modeling, LLM-as-a-judge), where they act as proxies for human preferences or judgments. This leads to the need for meta-evaluation: evaluating the …","url":["https://arxiv.org/pdf/2410.17578"]}
{"year":"2024","title":"MMRA: A Benchmark for Multi-granularity Multi-image Relational Association","authors":["S Wu, K Zhu, Y Bai, Y Liang, Y Li, H Wu, J Liu, R Liu… - arXiv preprint arXiv …, 2024"],"snippet":"Given the remarkable success that large visual language models (LVLMs) have achieved in image perception tasks, the endeavor to make LVMLs perceive the world like humans is drawing increasing attention. Current multi-modal benchmarks …","url":["https://arxiv.org/pdf/2407.17379"]}
{"year":"2024","title":"Mobile Generative AI: Opportunities and Challenges","authors":["Y Zhang, J Zhang, S Yue, W Lu, J Ren, X Shen - IEEE Wireless Communications, 2024"],"snippet":"Recently, generative artificial intelligence (GenAI) has gained significant interest on a global scale, particularly with the explosion of some killer GenAl applications, like ChatGPT. However, due to the excessively large sizes of generative models, most …","url":["https://ieeexplore.ieee.org/abstract/document/10628027/"]}
{"year":"2024","title":"MobileVLM: A Fast, Reproducible and Strong Vision Language Assistant for Mobile Devices","authors":["X Chu, L Qiao, X Lin, S Xu, Y Yang, Y Hu, F Wei… - arXiv preprint arXiv …, 2023"],"snippet":"We present MobileVLM, a competent multimodal vision language model (MMVLM) targeted to run on mobile devices. It is an amalgamation of a myriad of architectural designs and techniques that are mobile-oriented, which comprises a set of language …","url":["https://arxiv.org/pdf/2312.16886"]}
{"year":"2024","title":"Model Internals-based Answer Attribution for Trustworthy Retrieval-Augmented Generation","authors":["TRA Generation"],"snippet":"Ensuring the verifiability of model answers is a fundamental challenge for retrieval-augmented generation (RAG) in the question answering (QA) domain. Recently, self-citation prompting was proposed to make large language models (LLMs) generate citations …","url":["https://openreview.net/pdf?id=VzVEKmElJT"]}
{"year":"2024","title":"Modeling Caption Diversity in Contrastive Vision-Language Pretraining","authors":["S Lavoie, P Kirichenko, M Ibrahim, M Assran… - arXiv preprint arXiv …, 2024"],"snippet":"There are a thousand ways to caption an image. Contrastive Language Pretraining (CLIP) on the other hand, works by mapping an image and its caption to a single vector -- limiting how well CLIP-like models can represent the diverse ways to describe an …","url":["https://arxiv.org/pdf/2405.00740"]}
{"year":"2024","title":"Modeling Nonnative Sentence Processing with L2 Language Models","authors":["T Aoyama, N Schneider - Proceedings of the 2024 Conference on Empirical …, 2024"],"snippet":"We study LMs pretrained sequentially on two languages (“L2LMs”) for modeling nonnative sentence processing. In particular, we pretrain GPT2 on 6 different first languages (L1s), followed by English as the second language (L2). We examine the …","url":["https://aclanthology.org/2024.emnlp-main.283.pdf"]}
{"year":"2024","title":"Modeling the Sacred: Considerations when Using Considerations when Using Religious Texts in Natural Language Processing","authors":["B Hutchinson - arXiv preprint arXiv:2404.14740, 2024"],"snippet":"This position paper concerns the use of religious texts in Natural Language Processing (NLP), which is of special interest to the Ethics of NLP. Religious texts are expressions of culturally important values, and machine learned models have a …","url":["https://arxiv.org/pdf/2404.14740"]}
{"year":"2024","title":"Modelling cross-lingual transfer for semantic parsing","authors":["TR Sherborne - 2024"],"snippet":"This thesis has been submitted in fulfilment of the requirements for a postgraduate degree (eg PhD, MPhil, DClinPsychol) at t Page 1 This thesis has been submitted in fulfilment of the requirements for a postgraduate degree (eg PhD, MPhil …","url":["https://era.ed.ac.uk/bitstream/handle/1842/42188/SherborneTR_2024.pdf?sequence=1"]}
{"year":"2024","title":"Modelling Multimodal Integration in Human Concept Processing with Vision-and-Language Models","authors":["A Bavaresco, MH Kloots, S Pezzelle, R Fernández - arXiv preprint arXiv:2407.17914, 2024"],"snippet":"Representations from deep neural networks (DNNs) have proven remarkably predictive of neural activity involved in both visual and linguistic processing. Despite these successes, most studies to date concern unimodal DNNs, encoding either …","url":["https://arxiv.org/pdf/2407.17914"]}
{"year":"2024","title":"Modelling Visual Semantics via Image Captioning to extract Enhanced Multi-Level Cross-Modal Semantic Incongruity Representation with Attention for Multimodal …","authors":["S Aggarwal, A Pandey, DK Vishwakarma - arXiv preprint arXiv:2408.02595, 2024"],"snippet":"… With over 2 terabytes of cleaned CommonCrawl data [45], the masked language model [44] has already been pre-trained on over a hundred languages, including Hindi. We chose this particular variant of [46] for our investigation since the majority …","url":["https://arxiv.org/pdf/2408.02595"]}
{"year":"2024","title":"Models for analyzing the complexity of English words in the text on the scale from A1 to C2","authors":["М Бєліков, Т Ліхоузова, Ю Олійник - Адаптивні системи автоматичного управління, 2024"],"snippet":"… This model was trained on data from Common Crawl (web archives with data from web pages on various topics), OntoNotes 5 (corpus of annotated texts together with annotations of parts of speech, word dependencies and named entities) and …","url":["https://asac.kpi.ua/article/download/313091/304134"]}
{"year":"2024","title":"MoH: Multi-Head Attention as Mixture-of-Head Attention","authors":["P Jin, B Zhu, L Yuan, S Yan - arXiv preprint arXiv:2410.11842, 2024"],"snippet":"In this work, we upgrade the multi-head attention mechanism, the core of the Transformer model, to improve efficiency while maintaining or surpassing the previous accuracy level. We show that multi-head attention can be expressed in the …","url":["https://arxiv.org/pdf/2410.11842"]}
{"year":"2024","title":"MojoBench: Language Modeling and Benchmarks for Mojo","authors":["N Raihan, J Santos, M Zampieri - arXiv preprint arXiv:2410.17736, 2024"],"snippet":"The recently introduced Mojo programming language (PL) by Modular, has received significant attention in the scientific community due to its claimed significant speed boost over Python. Despite advancements in code Large Language Models (LLMs) …","url":["https://arxiv.org/pdf/2410.17736"]}
{"year":"2024","title":"Mono-InternVL: Pushing the Boundaries of Monolithic Multimodal Large Language Models with Endogenous Visual Pre-training","authors":["G Luo, X Yang, W Dou, Z Wang, J Dai, Y Qiao, X Zhu - arXiv preprint arXiv …, 2024"],"snippet":"The rapid advancement of Large Language Models (LLMs) has led to an influx of efforts to extend their capabilities to multimodal tasks. Among them, growing attention has been focused on monolithic Multimodal Large Language Models (MLLMs) …","url":["https://arxiv.org/pdf/2410.08202"]}
{"year":"2024","title":"Mono-lingual text reuse detection for the Urdu language at lexical level","authors":["A Noreen, I Muneer, RMA Nawab - Engineering Applications of Artificial Intelligence, 2024"],"snippet":"Text reuse is the process of creating new texts from pre-existing ones. In recent years, Urdu Text Reuse Detection (U-TRD) has garnered the attention of researchers due to the ready availability of digital text all over the internet, which can be copied or …","url":["https://www.sciencedirect.com/science/article/pii/S0952197624011618"]}
{"year":"2024","title":"mOSCAR: A Large-scale Multilingual and Multimodal Document-level Corpus","authors":["M Futeral, A Zebaze, PO Suarez, J Abadji, R Lacroix… - arXiv preprint arXiv …, 2024"],"snippet":"… This motivated us to collect and release the first large-scale multilingual and multimodal document dataset derived from Common Crawl.Our dataset, multimodal OSCAR (mOSCAR), follows the OSCAR initiative [Ortiz Suárez et al., 2019, Abadji et …","url":["https://arxiv.org/pdf/2406.08707"]}
{"year":"2024","title":"Moshi: a speech-text foundation model for real-time dialogue","authors":["A Défossez, L Mazaré, M Orsini, A Royer, P Pérez…"],"snippet":"… Our training dataset is made of a mix of high-quality data sources and filtered web data from CommonCrawl. More specifically, 12.5% of our … The remaining 87.5% of our dataset is from CommonCrawl, and was filtered with the pipeline described in …","url":["https://kyutai.org/Moshi.pdf"]}
{"year":"2024","title":"MoVA: Adapting Mixture of Vision Experts to Multimodal Context","authors":["Z Zong, B Ma, D Shen, G Song, H Shao, D Jiang, H Li… - arXiv preprint arXiv …, 2024"],"snippet":"As the key component in multimodal large language models (MLLMs), the ability of the visual encoder greatly affects MLLM's understanding on diverse image content. Although some large-scale pretrained vision encoders such as vision encoders in …","url":["https://arxiv.org/pdf/2404.13046"]}
{"year":"2024","title":"MPDS: A Movie Posters Dataset for Image Generation with Diffusion Model","authors":["M Xu, T Zhang, F Wang, Y Lei, X Liu, Z Cui - arXiv preprint arXiv:2410.16840, 2024"],"snippet":"… This dataset is sourced from Common Crawl (Crawl 2024), a non-profit organization that regularly releases HTML data from billions of … Some Image-Text Datasets, such as LAION-400M, obtain HTML-like data from Common Crawl …","url":["https://arxiv.org/pdf/2410.16840"]}
{"year":"2024","title":"mPLM-Sim: Better Cross-Lingual Similarity and Transfer in Multilingual Pretrained Language Models","authors":["P Lin, C Hu, Z Zhang, AFT Martins, H Schütze - Findings of the Association for …, 2024"],"snippet":"Recent multilingual pretrained language models (mPLMs) have been shown to encode strong language-specific signals, which are not explicitly provided during pretraining. It remains an open question whether it is feasible to employ mPLMs to …","url":["https://aclanthology.org/2024.findings-eacl.20.pdf"]}
{"year":"2024","title":"mPLUG-DocOwl 1.5: Unified Structure Learning for OCR-free Document Understanding","authors":["A Hu, H Xu, J Ye, M Yan, L Zhang, B Zhang, C Li… - arXiv preprint arXiv …, 2024"],"snippet":"Structure information is critical for understanding the semantics of text-rich images, such as documents, tables, and charts. Existing Multimodal Large Language Models (MLLMs) for Visual Document Understanding are equipped with text recognition …","url":["https://arxiv.org/pdf/2403.12895"]}
{"year":"2024","title":"MQM-Chat: Multidimensional Quality Metrics for Chat Translation","authors":["Y Li, J Suzuki, M Morishita, K Abe, K Inui - arXiv preprint arXiv:2408.16390, 2024"],"snippet":"The complexities of chats pose significant challenges for machine translation models. Recognizing the need for a precise evaluation metric to address the issues of chat translation, this study introduces Multidimensional Quality Metrics for Chat …","url":["https://arxiv.org/pdf/2408.16390"]}
{"year":"2024","title":"MS MARCO Web Search: a Large-scale Information-rich Web Dataset with Millions of Real Click Labels","authors":["Q Chen, X Geng, C Rosset, C Buractaon, J Lu, T Shen… - Companion Proceedings of …, 2024"],"snippet":"Recent breakthroughs in large models have highlighted the critical significance of data scale, labels and modals. In this paper, we introduce MS MARCO Web Search, the first large-scale information-rich web dataset, featuring millions of real clicked …","url":["https://dl.acm.org/doi/pdf/10.1145/3589335.3648327"]}
{"year":"2024","title":"Mult-IT Multiple Choice Questions on Multiple Topics in Italian: A CALAMITA Challenge","authors":["M Rinaldi, J Gili, M Francis, M Goffetti, V Patti, M Nissim - Proceedings of the 10th …, 2024"],"snippet":"… For example, the Common Crawl dataset2, often used as a base for more refined datasets to be employed in the pre-training of LLMs, is composed of 45% English content, while the data for languages such as Spanish, French, Italian, and Chinese …","url":["https://clic2024.ilc.cnr.it/wp-content/uploads/2024/12/131_calamita_long.pdf"]}
{"year":"2024","title":"Multi Class Depression Detection Through Tweets using Artificial Intelligence","authors":["MO Nusrat, W Shahzad, SA Jamal - arXiv preprint arXiv:2404.13104, 2024"],"snippet":"… Typically, GloVe embeddings were pretrained on extensive corpora like Wikipedia or Common Crawl and fine-tuned for specific tasks. 300 LSTM units were used with a dropout rate of 0.4. For depression classification, the dense layer was …","url":["https://arxiv.org/pdf/2404.13104"]}
{"year":"2024","title":"Multi-Agent Collaborative Data Selection for Efficient LLM Pretraining","authors":["T Bai, L Yang, ZH Wong, J Peng, X Zhuang, C Zhang… - arXiv preprint arXiv …, 2024"],"snippet":"… For the topic agent, due to the absence of a suitable pretrained model for topic classification and labeling, we designed a classification schema using 1.44 billion documents collected by the Common Crawl project (Project, 2007) and fine-tuned a …","url":["https://arxiv.org/pdf/2410.08102"]}
{"year":"2024","title":"Multi-class hate speech detection in the Norwegian language using FAST-RNN and multilingual fine-tuned transformers","authors":["E Hashmi, SY Yayilgan - Complex & Intelligent Systems, 2024"],"snippet":"… FastText, a word representation tool developed by Facebook’s research division, offers both unsupervised and supervised modes and features a comprehensive database of 2 million words from Common Crawl, each represented by 300 …","url":["https://link.springer.com/article/10.1007/s40747-024-01392-5"]}
{"year":"2024","title":"Multi-Head Mixture-of-Experts","authors":["X Wu, S Huang, W Wang, F Wei - arXiv preprint arXiv:2404.15045, 2024"],"snippet":"Sparse Mixtures of Experts (SMoE) scales model capacity without significant increases in training and inference costs, but exhibits the following two issues: (1) Low expert activation, where only a small subset of experts are activated for …","url":["https://arxiv.org/pdf/2404.15045"]}
{"year":"2024","title":"Multi-modal Comparative Analysis on Execution of Phishing Detection using Artificial Intelligence","authors":["DJ Dsouza, AP Rodrigues, R Fernandes - IEEE Access, 2024"],"snippet":"Phishing is the process of deceiving or stealing private or confidential information through illicit means. This could lead to financial loss, loss of reputation, and identity theft. Hence, identifying and preventing the use of such phishing sites becomes …","url":["https://ieeexplore.ieee.org/iel8/6287639/6514899/10742373.pdf"]}
{"year":"2024","title":"Multi-News+: Cost-efficient Dataset Cleansing via LLM-based Data Annotation","authors":["J Choi, J Yun, K Jin, YB Kim - arXiv preprint arXiv:2404.09682, 2024"],"snippet":"… an analysis of undesirable content in the common crawl corpus. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 2 …","url":["https://arxiv.org/pdf/2404.09682"]}
{"year":"2024","title":"Multi-Reference Benchmarks for Russian Grammatical Error Correction","authors":["FP Gomez, A Rozovskaya - Proceedings of the 18th Conference of the European …, 2024"],"snippet":"This paper presents multi-reference benchmarks for the Grammatical Error Correction (GEC) of Russian, based on two existing single-reference datasets, for a total of 7,444 learner sentences from a variety of first language backgrounds. Each …","url":["https://aclanthology.org/2024.eacl-long.76.pdf"]}
{"year":"2024","title":"Multi-Stream Keypoint Attention Network for Sign Language Recognition and Translation","authors":["M Guan, Y Wang, G Ma, J Liu, M Sun - arXiv preprint arXiv:2405.05672, 2024"],"snippet":"Sign language serves as a non-vocal means of communication, transmitting information and significance through gestures, facial expressions, and bodily movements. The majority of current approaches for sign language recognition (SLR) …","url":["https://arxiv.org/pdf/2405.05672"]}
{"year":"2024","title":"Multi-Task Contrastive Learning for 8192-Token Bilingual Text Embeddings","authors":["I Mohr, M Krimmel, S Sturua, MK Akram, A Koukounas… - arXiv preprint arXiv …, 2024"],"snippet":"… Seeking further diversity and volume, we utilize Common Crawl data to create two types of pairs: one from web page titles and their contents, and another by mining questionanswer pairs from FAQ and support-related pages. Additionally, we pair …","url":["https://arxiv.org/pdf/2402.17016"]}
{"year":"2024","title":"Multidimensional Text Feature Analysis: Unveiling the Veil of Automatically Generated Text","authors":["M Guo, Z Han, X Wang, J Peng - 2024"],"snippet":"… Given the widespread use of transformer-based pre-trained models in various downstream tasks and the availability of multilingual datasets in official task data, XLM-RoBERTa[19] is a multilingual version of Roberta that has been pre-trained on …","url":["https://ceur-ws.org/Vol-3756/IberAuTexTification2024_paper3.pdf"]}
{"year":"2024","title":"Multilingual Blending: LLM Safety Alignment Evaluation with Language Mixture","authors":["J Song, Y Huang, Z Zhou, L Ma - arXiv preprint arXiv:2407.07342, 2024"],"snippet":"… We consider most state-of-the-art LLMs to have trained on these 55 source languages, as these languages are enclosed in the CommonCrawl corpus. All multilingual translations are conducted using Google Translate API3. All codes for …","url":["https://arxiv.org/pdf/2407.07342"]}
{"year":"2024","title":"Multilingual Detection of Cyberbullying in Mixed Urdu, Roman Urdu, and English Social Media Conversations","authors":["F Razi, N Ejaz - IEEE Access, 2024"],"snippet":"… The pre-training data is carefully selected from Common Crawl, a vast collection of web pages, to ensure that it’s both high-quality and diverse. This diverse training data allows m-BERT to learn language-agnostic representations, making it easier to …","url":["https://ieeexplore.ieee.org/iel8/6287639/6514899/10608139.pdf"]}
{"year":"2024","title":"Multilingual Diversity Improves Vision-Language Representations","authors":["T Nguyen, M Wallingford, S Santy, WC Ma, S Oh… - arXiv preprint arXiv …, 2024"],"snippet":"… Data We experiment with the medium pool of the DataComp benchmark [14], which consists of 128M image-text pairs randomly sampled from Common Crawl dumps between 2014 and 2022, and deduplicated. Unlike other heavily filtered …","url":["https://arxiv.org/pdf/2405.16915"]}
{"year":"2024","title":"Multilingual E5 Text Embeddings: A Technical Report","authors":["L Wang, N Yang, X Huang, L Yang, R Majumder, F Wei - arXiv preprint arXiv …, 2024"],"snippet":"This technical report presents the training methodology and evaluation results of the open-source multilingual E5 text embedding models, released in mid-2023. Three embedding models of different sizes (small / base / large) are provided, offering a …","url":["https://arxiv.org/pdf/2402.05672"]}
{"year":"2024","title":"Multilingual Fake News Detection: A Study on Various Models and Training","authors":["R Chalehchaleh, R Farahbakhsh, N Crespi - … Systems and Applications: Proceedings of the …"],"snippet":"… XLM-RoBERTa model is pre-trained on 2.5 TB of filtered CommonCrawl data containing 100 languages it was introduced in [8]. LASER (Language-Agnostic SEntence Representations)[3] is trained to capture the semantic meaning of sentences …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=bPUWEQAAQBAJ&oi=fnd&pg=PA73&dq=commoncrawl&ots=bV7FBJjOrm&sig=kp34-0SCGl9K41Vpc-e346H0O4k"]}
{"year":"2024","title":"Multilingual Hallucination Gaps in Large Language Models","authors":["C Chataigner, A Taïk, G Farnadi - arXiv preprint arXiv:2410.18270, 2024"],"snippet":"Large language models (LLMs) are increasingly used as alternatives to traditional search engines given their capacity to generate text that resembles human language. However, this shift is concerning, as LLMs often generate hallucinations, misleading …","url":["https://arxiv.org/pdf/2410.18270"]}
{"year":"2024","title":"Multilingual Hate Speech Detection: Comparison of Transfer Learning Methods to Classify German, Italian, and Spanish Posts","authors":["J Fillies, MP Hoffmann, A Paschke - 2023 IEEE International Conference on Big Data …, 2023"],"snippet":"… This datasetincludes Wikipedia dumps for all supported languages anda substantial 2.5 terabytes of Common Crawl Data collectedfrom the Internet. The ”RoBERTa” component in the model’sname indicates the adherence to the training procedure …","url":["https://www.computer.org/csdl/proceedings-article/bigdata/2023/10386244/1TUOShUglSU"]}
{"year":"2024","title":"Multilingual Language Models: Analysis and Algorithms","authors":["T Blevins - 2024"],"snippet":"While large language models (LLMs) continue to grow in scale and gain new zero-shot capabilities, their performance for languages beyond English increasingly lags behind. This gap is due to the curse of multilinguality, where multilingual language …","url":["https://search.proquest.com/openview/4cef5f85645d35790bfeb1b6dd56e4c1/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
{"year":"2024","title":"Multilingual Large Language Models and Curse of Multilinguality","authors":["D Gurgurov, T Bäumel, T Anikina - arXiv preprint arXiv:2406.10602, 2024"],"snippet":"… Common Crawl The Common Crawl corpus is a vast collection of web data accumulated over more than 10 years through web crawling. It includes raw web page data, metadata extracts, and text extracts. This noncurated dataset includes …","url":["https://arxiv.org/pdf/2406.10602"]}
{"year":"2024","title":"Multilingual Large Language Models: A Systematic Survey","authors":["S Zhu, S Xu, H Sun, L Pan, M Cui, J Du, R Jin… - arXiv preprint arXiv …, 2024"],"snippet":"… CommonCrawl9, a large-scale collection of web dumps. It crawls billions of web pages every month and releases a snapshot, now containing snapshots from 2008 to the present, and it is continuously being updated. CommonCrawl … 12 snapshots …","url":["https://arxiv.org/pdf/2411.11072"]}
{"year":"2024","title":"Multilingual Model Fine-tuning for Sentiment Analysis","authors":["ML Elrefai, MI Khalil, HM Abbas - … on Intelligent Computing and Information Systems …, 2023"],"snippet":"… A sizable multilingual language model was created using 2.5 TB of filtered CommonCrawl data. One of the outstanding XLMRoBERTa in low-resource languages, Low-resource languages are languages with limited available data for …","url":["https://ieeexplore.ieee.org/abstract/document/10391141/"]}
{"year":"2024","title":"Multilingual Models in Neural Machine Translation","authors":["G Yang"],"snippet":"… XGLM [19] uses the decoder-only model architecture similar to that of GPT-3 [6], and was pre-trained on CC100-XL that covers 68 Common Crawl (CC) snapshots and 134 languages. Experiment results show that XGLM (7.5B) outperforms GPT-3 (6.7B) …","url":["http://mi.eng.cam.ac.uk/~wjb31/MPhil_Thesis_Guangyu_Yang.pdf"]}
{"year":"2024","title":"Multilingual Pretraining Using a Large Corpus Machine-Translated from a Single Source Language","authors":["J Wang, Y Lu, M Weber, M Ryabinin, Y Chen, R Tang… - arXiv preprint arXiv …, 2024"],"snippet":"English, as a very high-resource language, enables the pretraining of high-quality large language models (LLMs). The same cannot be said for most other languages, as leading LLMs still underperform for non-English languages, likely due to a gap in …","url":["https://arxiv.org/pdf/2410.23956?"]}
{"year":"2024","title":"Multilingual Sarcasm Detection for Enhancing Sentiment Analysis using Deep Learning Algorithms","authors":["AD Yacoub, AE Aboutabl, SO Slim"],"snippet":"Recent years have seen a notable rise in online opinion-sharing, underscoring the demand for automated sentiment analysis tools. Addressing sarcasm in text is crucial, as it can significantly influence the effectiveness of sentiment analysis models. This …","url":["https://jcoms.fesb.unist.hr/pdfs/v20n4_2024-0071_Yacoub.pdf"]}
{"year":"2024","title":"Multilingual Speech and Language Analysis for the Assessment of Mild Cognitive Impairment: Outcomes from the Taukadial Challenge","authors":["PA Perez-Toro, T Arias-Vergara, P Klumpp, T Weise…"],"snippet":"… Our analysis utilized the BERTBase and RoBERTa-Base models, trained on Wikicorpus data spanning 102 languages and CommonCrawl data filtered from 100 languages [16], respectively. For both models, the final layer, comprising 768 units …","url":["https://www.isca-archive.org/interspeech_2024/pereztoro24_interspeech.pdf"]}
{"year":"2024","title":"MultiLS: A Multi-task Lexical Simplification Framework","authors":["K North, T Ranasinghe, M Shardlow, M Zampieri - arXiv preprint arXiv:2402.14972, 2024"],"snippet":"Lexical Simplification (LS) automatically replaces difficult to read words for easier alternatives while preserving a sentence's original meaning. LS is a precursor to Text Simplification with the aim of improving text accessibility to various target …","url":["https://arxiv.org/pdf/2402.14972"]}
{"year":"2024","title":"Multimodal Alignment and Fusion: A Survey","authors":["S Li, H Tang - arXiv preprint arXiv:2411.17040, 2024"],"snippet":"This survey offers a comprehensive review of recent advancements in multimodal alignment and fusion within machine learning, spurred by the growing diversity of data types such as text, images, audio, and video. Multimodal integration enables …","url":["https://arxiv.org/pdf/2411.17040"]}
{"year":"2024","title":"Multimodal Approaches to Fair Image Classification: An Ethical Perspective","authors":["J Hickmon - arXiv preprint arXiv:2412.12165, 2024"],"snippet":"In the rapidly advancing field of artificial intelligence, machine perception is becoming paramount to achieving increased performance. Image classification systems are becoming increasingly integral to various applications, ranging from …","url":["https://arxiv.org/pdf/2412.12165"]}
{"year":"2024","title":"Multimodal Large Language Models for Bioimage Analysis","authors":["S Zhang, G Dai, T Huang, J Chen - arXiv preprint arXiv:2407.19778, 2024"],"snippet":"Rapid advancements in imaging techniques and analytical methods over the past decade have revolutionized our ability to comprehensively probe the biological world at multiple scales, pinpointing the type, quantity, location, and even temporal …","url":["https://arxiv.org/pdf/2407.19778"]}
{"year":"2024","title":"Multimodal Latent Language Modeling with Next-Token Diffusion","authors":["Y Sun, H Bao, W Wang, Z Peng, L Dong, S Huang… - arXiv preprint arXiv …, 2024"],"snippet":"Multimodal generative models require a unified approach to handle both discrete data (eg, text and code) and continuous data (eg, image, audio, video). In this work, we propose Latent Language Modeling (LatentLM), which seamlessly integrates …","url":["https://arxiv.org/pdf/2412.08635"]}
{"year":"2024","title":"Multimodal Learning for Visual Question Answering using World Knowledge","authors":["MBA Alhaj"],"snippet":"Navigating the frontier of the Visual Turing Test, this research delves into multimodal learning to bridge the gap between visual perception and linguistic interpretation, a foundational challenge in artificial intelligence. It scrutinizes the integration of visual …","url":["https://huggingface.co/spaces/m7mdal7aj/KB-VQA/resolve/main/Files/Dissertation%20Report.pdf"]}
{"year":"2024","title":"Multimodal predictive model for analyzing news data","authors":["P KADLEC"],"snippet":"The aim of this thesis is to create a predictive tool utilising a multimodal machine-learning model for the combined textual and visual data from a dataset of news articles to predict the political orientation of news articles. A thorough exploration of multimodal …","url":["https://is.muni.cz/th/rn04p/Master_Thesis___Multimodal_predictive_model_for_analysing_news_data.pdf"]}
{"year":"2024","title":"MULTINET: ABENCHMARK FOR GENERALIST ACTION MODELS","authors":["P Guruprasad, H Sikka"],"snippet":"… OBELICS OBELICS [27] is an open web-scale filtered dataset of interleaved image-text documents extracted from Common Crawl [1]. It … The dataset was curated from approximately 10 billion initial pairs collected from CommonCrawl …","url":["https://multinet.ai/static/pdfs/MultiNet_Dataset_Spec_Paper.pdf"]}
{"year":"2024","title":"Multiscale cascaded domain-based approach for Arabic fake reviews detection in e-commerce platforms","authors":["N Qandos, G Hamad, M Alharbi, S Alturki, W Alharbi… - Journal of King Saud …, 2024"],"snippet":"Fake reviews in e-commerce can lead to customer deception and financial losses. Despite the importance of fake reviews detection, studies for Arabic language are scarce due to the lack of comprehensive datasets. This study addresses this gap by …","url":["https://www.sciencedirect.com/science/article/pii/S1319157824000156"]}
{"year":"2024","title":"Multivariate Log-based Anomaly Detection for Distributed Database","authors":["L Zhang, T Jia, M Jia, Y Li, Y Yang, Z Wu - arXiv preprint arXiv:2406.07976, 2024"],"snippet":"… Following this, MultiLog utilizes pre-trained word vectors based on the Common Crawl Corpus with the FastText algorithm[45], which is adept at capturing the inherent relationships among words in natural language. This means each word in a …","url":["https://arxiv.org/pdf/2406.07976"]}
{"year":"2024","title":"Musical Word Embedding for Music Tagging and Retrieval","authors":["SH Doh, J Lee, D Jeong, J Nam - arXiv preprint arXiv:2404.13569, 2024"],"snippet":"… We used two publicly available embeddings trained on Common Crawl, a large-scale general word corpus, with the GloVe and skipgram … It demonstrates that word embeddings trained with a general word corpus, such as Common Crawl and Wiki …","url":["https://arxiv.org/pdf/2404.13569"]}
{"year":"2024","title":"Myanmar XNLI: Building a Dataset and Exploring Low-resource Approaches to Natural Language Inference with Myanmar","authors":["AK Htet, M Dras - 2024"],"snippet":"Despite dramatic recent progress in NLP, it is still a major challenge to apply Large Language Models (LLM) to low-resource languages. This is made visible in benchmarks such as Cross-Lingual Natural Language Inference (XNLI), a key task …","url":["https://www.researchsquare.com/article/rs-4329843/latest.pdf"]}
{"year":"2024","title":"Named Entity Recognition in Italian Lung Cancer Clinical Reports using Transformers","authors":["D Paolo, A Bria, C Greco, M Russano, S Ramella… - 2023 IEEE International …, 2023"],"snippet":"The widespread adoption of electronic health records (EHRs) offers a valuable opportunity to support clinical research by containing crucial patient information, including diagnoses, symptoms, medications, lab tests, and more. Despite the …","url":["https://ieeexplore.ieee.org/abstract/document/10385778/"]}
{"year":"2024","title":"NATALITY AT RISK? RAISING DOUBTS ON THE EDUCATIONAL IMPORTANCE OF ChatGPT","authors":["P Rojahn - Colloquium, 2024"],"snippet":"Digital tools are part of our daily life. Thus, they also enter educational contexts. With reference to Hannah Arendt’s writings this paper explores if, and to what extent, digital tools can be considered to be helpful and desirable in education. For this …","url":["https://colloquium.elsite.eu/index.php/colloquium/article/download/908/527"]}
{"year":"2024","title":"Native Design Bias: Studying the Impact of English Nativeness on Language Model Performance","authors":["M Reusens, P Borchert, J De Weerdt, B Baesens - arXiv preprint arXiv:2406.17385, 2024"],"snippet":"Large Language Models (LLMs) excel at providing information acquired during pretraining on large-scale corpora and following instructions through user prompts. This study investigates whether the quality of LLM responses varies depending on …","url":["https://arxiv.org/pdf/2406.17385"]}
{"year":"2024","title":"Natural GaLore: Accelerating GaLore for memory-efficient LLM Training and Fine-tuning","authors":["A Das - arXiv preprint arXiv:2410.16029, 2024"],"snippet":"Training LLMs presents significant memory challenges due to growing size of data, weights, and optimizer states. Techniques such as data and model parallelism, gradient checkpointing, and offloading strategies address this issue but are often …","url":["https://arxiv.org/pdf/2410.16029"]}
{"year":"2024","title":"Natural Language Processing Advancements: Breaking Barriers in Human-Computer Interaction","authors":["JGC Ramírez - Journal of Artificial Intelligence General science (JAIGS …, 2024"],"snippet":"Natural Language Processing (NLP) advancements have revolutionized human-computer interaction, breaking barriers and opening new frontiers in technology. NLP techniques enable machines to understand, interpret, and generate human …","url":["https://ojs.boulibrary.com/index.php/JAIGS/article/download/63/35"]}
{"year":"2024","title":"Natural Language Processing Approaches for Monitoring Health Activities","authors":["D Yu - 2024"],"snippet":"Monitoring health activities is vital for individual and public health. It identifies trends, detects risks early, and tailors interventions. At the individual level, it informs customized treatments. At the population level, monitoring broad health patterns …","url":["https://deepblue.lib.umich.edu/bitstream/handle/2027.42/194449/deahanyu_1.pdf?sequence=1"]}
{"year":"2024","title":"Natural Language Processing for Dialects of a Language: A Survey","authors":["A Joshi, R Dabre, D Kanojia, Z Li, H Zhan, G Haffari… - arXiv preprint arXiv …, 2024"],"snippet":"State-of-the-art natural language processing (NLP) models are trained on massive training corpora, and report a superlative performance on evaluation datasets. This survey delves into an important attribute of these datasets: the dialect of a language …","url":["https://arxiv.org/pdf/2401.05632"]}
{"year":"2024","title":"Natural Language Processing for Slang","authors":["Z Sun - 2024"],"snippet":"… Existing NLP approaches rely on large training corpora derived from sources such as Wikipedia8 and Common Crawl9 which are composed of formal documents such as news articles and wiki pages. Because of this, models observe formal …","url":["https://zhewei-sun.github.io/files/nlp_for_slang_thesis.pdf"]}
{"year":"2024","title":"Natural Language Processing Journal","authors":["A Caesar, O Özdemir, C Weber, S Wermter","MN Hoque, U Salma, MJ Uddin, MM Ahamad, S Aktar","S Gopali, S Siami-Namini, F Abri, AS Namin"],"snippet":"In the sentiment analysis (SA) task, we can obtain a positive or negative-typed comment or feedback from an online user or a customer about any object, such as a movie, drama, food, and others. This user’s sentiment may positively impact various …","url":["https://www.researchgate.net/profile/Saroj-Gopali/publication/386200631_The_performance_of_the_LSTM-based_code_generated_by_Large_Language_Models_LLMs_in_forecasting_time_series_data/links/6761ba00af28fb680fbfd7ac/The-performance-of-the-LSTM-based-code-generated-by-Large-Language-Models-LLMs-in-forecasting-time-series-data.pdf","https://www.researchgate.net/profile/Umme-Salma-28/publication/383094728_Exploring_transformer_models_in_the_sentiment_analysis_task_for_the_under-resource_Bengali_language/links/66bc7bc92ff54d6c9ecf33d7/Exploring-transformer-models-in-the-sentiment-analysis-task-for-the-under-resource-Bengali-language.pdf","https://www2.informatik.uni-hamburg.de/wtm/publications/2024/COWW24a/1-s2.0-S2949719124000207-main.pdf"]}
{"year":"2024","title":"Natural Language Processing Methods for Symbolic Music Generation and Information Retrieval: a Survey","authors":["DVT Le, L Bigo, M Keller, D Herremans - arXiv preprint arXiv:2402.17467, 2024","L Bigo, M Keller, D Herremans - 2024"],"snippet":"Several adaptations of Transformers models have been developed in various domains since its breakthrough in Natural Language Processing (NLP). This trend has spread into the field of Music Information Retrieval (MIR), including studies …","url":["https://arxiv.org/pdf/2402.17467","https://hal.science/hal-04621444/document"]}
{"year":"2024","title":"Natural Language Processing Tools for Romanian–Going Beyond a Low-Resource Language","authors":["M Nitu, M Dascalu"],"snippet":"… Oscar (Open Super-large Crawled Aggregated coRpus) [64] is a multilingual dataset obtained via filtering the common crawl corpus. It encompasses 151 languages. The Romanian sub-corpus contains over 4,5 million documents …","url":["https://www.researchgate.net/profile/Nitu-Melania-2/publication/380779085_Natural_Language_Processing_Tools_for_Romanian_-_Going_Beyond_a_Low-Resource_Language/links/664efa81479366623a08548f/Natural-Language-Processing-Tools-for-Romanian-Going-Beyond-a-Low-Resource-Language.pdf"]}
{"year":"2024","title":"Natural Language Processing","authors":["CH Focke, RM Sylvester - Statistical Methods in Epilepsy, 2024"],"snippet":"In this chapter, we introduce modern natural language processing (NLP) libraries, techniques and their applications. This chapter focuses on deep learning methods and less on computational linguistics that require nuanced knowledge of linguistics …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=x1QIEQAAQBAJ&oi=fnd&pg=PA302&dq=commoncrawl&ots=nunktBqRF2&sig=V-n3c25TaVqCLY-Hs7tRdfKtPBI"]}
{"year":"2024","title":"Natural Language, Legal Hurdles: Navigating the Complexities in Natural Language Processing Development and Application","authors":["I Ilin, A Kelli - Journal of the University of Latvia. Law, 2024"],"snippet":"This article delves into the legal challenges faced in developing and deploying Natural Language Processing (NLP) technologies, focusing particularly on the European Union’s legal framework, especially the DSM Directive, the InfoSoc …","url":["https://journal.lu.lv/jull/article/download/2064/1996"]}
{"year":"2024","title":"Natural","authors":["E Reiter"],"snippet":"I have been working on natural language generation (NLG), that is using artificial intelligence techniques to produce texts in English and other human languages, since I got my PhD in this area in 1990. In late 2022, NLG became much more …","url":["https://link.springer.com/content/pdf/10.1007/978-3-031-68582-8.pdf"]}
{"year":"2024","title":"Navigating Challenges and Technical Debt in Large Language Models Deployment","authors":["A Menshawy, Z Nawaz, M Fahmy - Proceedings of the 4th Workshop on Machine …, 2024"],"snippet":"… These models, trained on an internet scale data including common crawl, books, and articles, have acquired an extensive understanding of language patterns, nuances, and contexts. This profound comprehension allows LLMs to perform a …","url":["https://dl.acm.org/doi/abs/10.1145/3642970.3655840"]}
{"year":"2024","title":"Navigating Data Scarcity using Foundation Models: A Benchmark of Few-Shot and Zero-Shot Learning Approaches in Medical Imaging","authors":["S Woerner, CF Baumgartner - arXiv preprint arXiv:2408.08058, 2024"],"snippet":"… LAION-2B contains 2 billion image-text pairs extracted from common crawl [3] and is the English language subset of the larger LAION-5B [12] … https://commoncrawl.org. [4] Alexey Dosovitskiy et al. An Image is Worth 16x16 Words: Transformers for Image …","url":["https://arxiv.org/pdf/2408.08058"]}
{"year":"2024","title":"Navigating Multimodal Complexity: Advances in Model Design, Dataset Creation, and Evaluation Techniques","authors":["PGJ Vickers - 2024"],"snippet":"Ibn Sina, a philosopher of 11th-century Persia, wrote of a `Floating Man'. This man is floating through a void, without the use of his sight or touch or any of the senses which make us human. Yet as he has a human brain this man, according to Ibn Sina …","url":["https://etheses.whiterose.ac.uk/35513/1/Peter_Vickers_PhD_Thesis__Final_.pdf"]}
{"year":"2024","title":"Navigating the Digital World as Humans Do: Universal Visual Grounding for GUI Agents","authors":["B Gou, R Wang, B Zheng, Y Xie, C Chang, Y Shu… - arXiv preprint arXiv …, 2024"],"snippet":"… We apply few filtering methods, excluding non-webpage files based on URLs, and removing non-English pages based on labels of language provided by Common Crawl. We use Playwright to load and render the webpages, capturing …","url":["https://arxiv.org/pdf/2410.05243"]}
{"year":"2024","title":"Navigating the ethical landscape behind ChatGPT","authors":["L Peng, B Zhao - Big Data & Society, 2024"],"snippet":"… While ChatGPT and similar text-generating AIs claim to be trained on mostly public data such as the Common Crawl archives, rendering … content in public datasets used for AI training, such as the Common Crawl, which is beyond the …","url":["https://journals.sagepub.com/doi/pdf/10.1177/20539517241237488"]}
{"year":"2024","title":"Navigating the Legal Landscape: Technical Implementation of Copyright Reservations for Text and Data Mining in the Era of AI Language Models","authors":["L Löbling, C Handschigl, K Hofmann, J Schwedhelm - JIPITEC–Journal of Intellectual …, 2023"],"snippet":"… However, limitations arose from the potential omission of specific pages of a website in individual monthly crawls by Common Crawl. Through manual investigation, a section containing the terms of use could be identified for 40 …","url":["https://www.jipitec.eu/jipitec/article/download/16/11"]}
{"year":"2024","title":"Ncl-uor at semeval-2024 task 8: Fine-tuning large language models for multigenerator, multidomain, and multilingual machine-generated text detection","authors":["F Xiong, T Markchom, Z Zheng, S Jung, V Ojha… - Proceedings of the 18th …, 2024"],"snippet":"SemEval-2024 Task 8 introduces the challenge of identifying machine-generated texts from diverse Large Language Models (LLMs) in various languages and domains. The task comprises three subtasks: binary classification in monolingual …","url":["https://aclanthology.org/2024.semeval-1.25.pdf"]}
{"year":"2024","title":"Near to Mid-term Risks and Opportunities of Open Source Generative AI","authors":["F Eiras, A Petrov, B Vidgen, CS de Witt, F Pizzati… - arXiv preprint arXiv …, 2024"],"snippet":"In the next few years, applications of Generative AI are expected to revolutionize a number of different areas, ranging from science & medicine to education. The potential for these seismic changes has triggered a lively debate about potential …","url":["https://arxiv.org/pdf/2404.17047"]}
{"year":"2024","title":"Need a Programming Exercise Generated in Your Native Language? ChatGPT's Got Your Back: Automatic Generation of Non-English Programming Exercises Using …","authors":["M Jordan, K Ly, AG Soosai Raj - Proceedings of the 55th ACM Technical Symposium …, 2024"],"snippet":"Large language models (LLMs) like ChatGPT are changing computing education and may create additional barriers to those already faced by non-native English speakers (NNES) learning computing. We investigate an opportunity for a positive …","url":["https://dl.acm.org/doi/pdf/10.1145/3626252.3630897"]}
{"year":"2024","title":"Negotiating becoming: a Nietzschean critique of large language models","authors":["SWS Fischer, B Boer - Ethics and Information Technology, 2024"],"snippet":"Large language models (LLMs) structure the linguistic landscape by reflecting certain beliefs and assumptions. In this paper, we address the risk of people unthinkingly adopting and being determined by the values or worldviews embedded …","url":["https://link.springer.com/article/10.1007/s10676-024-09783-5"]}
{"year":"2024","title":"Nemotron-4 15B Technical Report","authors":["J Parmar, S Prabhumoye, J Jennings, M Patwary… - arXiv preprint arXiv …, 2024"],"snippet":"We introduce Nemotron-4 15B, a 15-billion-parameter large multilingual language model trained on 8 trillion text tokens. Nemotron-4 15B demonstrates strong performance when assessed on English, multilingual, and coding tasks: it …","url":["https://arxiv.org/pdf/2402.16819"]}
{"year":"2024","title":"Nemotron-CC: Transforming Common Crawl into a Refined Long-Horizon Pretraining Dataset","authors":["D Su, K Kong, Y Lin, J Jennings, B Norick, M Kliegl… - arXiv preprint arXiv …, 2024"],"snippet":"Recent English Common Crawl datasets like FineWeb-Edu and DCLM achieved significant benchmark gains via aggressive model-based filtering, but at the cost of removing 90% of data. This limits their suitability for long token horizon training, such …","url":["https://arxiv.org/pdf/2412.02595"]}
{"year":"2024","title":"NER-RoBERTa: Fine-Tuning RoBERTa for Named Entity Recognition (NER) within low-resource languages","authors":["AA Abdullah, SH Abdulla, DM Toufiq, HS Maghdid… - arXiv preprint arXiv …, 2024"],"snippet":"… In the same vein, a new version of RoBERTa is fine-tuned in 2024 and it is re-trained using various text-datasets within 100 different languages using the CommonCrawl dataset [11]. However, the RoBERTa for NER purposes using Central-Kurdish …","url":["https://arxiv.org/pdf/2412.15252"]}
{"year":"2024","title":"Neural Approaches to Decode Semantic Similarities in Spanish Song Lyrics for Enhanced Recommendation Systems","authors":["A Ghajari Espinosa - 2024"],"snippet":"… In this model, it was found that traditional methods of pre-training, which rely on large amounts of data from sources such as Common Crawl… The mC4 dataset is a multilingual variant of C4, containing natural text in 101 languages from the public …","url":["http://e-spacio.uned.es/fez/eserv/bibliuned:master-ETSInformatica-TL-Aghajari/Ghajari_Espinosa_Adrian_TFM.pdf"]}
{"year":"2024","title":"Neural Chat Translation as Online Document-to-Document Translation","authors":["M Lyu, H Dou, J Li, M Zhu, G Zhou - … on Natural Language Processing and Chinese …, 2024"],"snippet":"Neural chat translation (NCT) aims to translate utterances in a bilingual dialogue, where participants speak different languages, into their respective native languages. Recent advances on NCT translate chat utterances one by one using document-to-sentence …","url":["https://link.springer.com/chapter/10.1007/978-981-97-9437-9_20"]}
{"year":"2024","title":"Neural Information Retrieval","authors":["N Tonellotto - Information Retrieval: Advanced Topics and …, 2024"],"snippet":"… As illustrated in Figure 2.3, pre-training typically requires a huge generalpurpose training corpus, such as Wikipedia or Common Crawl web pages, expensive computation resources, and long training times, spanning several days or weeks. On …","url":["https://dl.acm.org/doi/pdf/10.1145/3674127.3674130"]}
{"year":"2024","title":"NEURAL MACHINE TRANSLATION BETWEEN MYANMAR AND ENGLISH LANGUAGES","authors":["NZM Aye"],"snippet":"This study aims to present a thorough overview of cutting-edge machine translation solutions and evaluate their effectiveness in translating between Myanmar and English language pairs. Translating Myanmar poses challenges due to its unique …","url":["http://www.ijcse.com/docs/INDJCSE24-15-04-022.pdf"]}
{"year":"2024","title":"Neural Methods for Aligning Large-Scale Parallel Corpora from the Web for South and East Asian Languages","authors":["P Koehn"],"snippet":"We introduce neural methods and a toxicity filtering step to the hierarchical web mining approach of Paracrawl (Bañón et al., 2020), showing large improvements. We apply these methods to web-scale parallel corpus mining for 9 South and East …","url":["https://www2.statmt.org/wmt24/pdf/2024.wmt-1.132.pdf"]}
{"year":"2024","title":"NEURAL MODELS FOR ONTOLOGY ANNOTATIONS-NEMO","authors":["P Devkota, SD Mohanty"],"snippet":"Words cannot express my gratitude to my advisors Dr. Somya D. Mohanty and Dr. Prashanti Manda for their invaluable supervision and guidance. I am extremely grateful to them for their continuous support, constructive suggestions, and …","url":["https://libres.uncg.edu/ir/uncg/f/Devkota_uncg_0154M_13725.pdf"]}
{"year":"2024","title":"Neural Network-based Language Modelling for Code-Switching in South African Languages","authors":["JJ van Vüren"],"snippet":"Language models, specifically those based on neural network architectures, have become an attractive alternative to classical statistical language models for natural language processing and speech recognition. Naturally, therefore, the field of neural …","url":["https://scholar.sun.ac.za/bitstreams/481dc105-b6b9-402b-9e68-f600dbc56745/download"]}
{"year":"2024","title":"Neural Networks with Model Compression","authors":["B Zhang, T Wang, S Xu, D Doermann - 2024"],"snippet":"… Firstly, the availability of large-scale datasets, such as ImageNet for computer vision or the Common Crawl dataset for natural language processing, has enabled the training of deep neural networks with millions or even billions of parameters …","url":["https://link.springer.com/content/pdf/10.1007/978-981-99-5068-3.pdf"]}
{"year":"2024","title":"Neural Pathway Embedding Through Hierarchical Interchange Networks in Large Language Models","authors":["L Eamen, A Phillips, J Mitchell, B Parker, S Bennett - 2024"],"snippet":"… Dataset Description The model was trained and tested on the Common Crawl dataset, a comprehensive corpus of web pages that provided … The selection of the Common Crawl dataset was motivated through its extensive coverage of linguistic …","url":["https://www.techrxiv.org/doi/pdf/10.36227/techrxiv.173273643.32824661"]}
{"year":"2024","title":"Neural Speech Tracking in EEG: Integrating Acoustics and Linguistics for Hearing Aid Users","authors":["K Almgren, A Mentzer - 2024"],"snippet":"This master thesis explores the neural encoding of speech features for hearing aid users. The study utilizes electroencephalography (EEG) and audio data from an experiment that stimulates a Cocktail Party scenario. This is a complex auditory …","url":["https://lup.lub.lu.se/student-papers/record/9174277/file/9174278.pdf"]}
{"year":"2024","title":"Neutral residues: revisiting adapters for model extension","authors":["FS Talla, H Jegou, E Grave - arXiv preprint arXiv:2410.02744, 2024"],"snippet":"… For the French finetuning dataset, we use a dataset extracted from CommonCrawl, which was pre-processed with the following steps. First, the … Finally, we filtered document using a fastText linear classifier, which was trained to discriminate …","url":["https://arxiv.org/pdf/2410.02744"]}
{"year":"2024","title":"Next word prediction for newspaper article formulation","authors":["AC Zechmeister - 2024"],"snippet":"Next word prediction describes the process of predicting the next word after every written word in the authoring of texts. It refers to machine learning techniques, which are part of the language modelling domain, a sub-domain of natural language …","url":["https://epub.technikum-wien.at/obvftwhsm/content/titleinfo/10097600/full.pdf"]}
{"year":"2024","title":"NLLB-Based Uzbek NMT: Leveraging Multisource Data","authors":["N Abdurakhmonova, AZ Mohirdev, M Salokhiddinov… - 2024 9th International …, 2024"],"snippet":"Recent advancements in Neural Machine Translation (NMT) have been largely propelled by the development of transformer-based architectures, exemplified by the NLLB (No Language Left Behind) model. This study extends previous work on low-resource …","url":["https://ieeexplore.ieee.org/abstract/document/10773423/"]}
{"year":"2024","title":"NLP Essentials","authors":["H Assoudi - Natural Language Processing on Oracle Cloud …, 2024"],"snippet":"In the digital era, there has been a significant increase in text data, ranging from social media content to corporate documents. To effectively utilize this data, a thorough grasp of Natural Language Processing (NLP) is essential. This chapter …","url":["https://link.springer.com/chapter/10.1007/979-8-8688-1073-2_1"]}
{"year":"2024","title":"NLP for The Greek Language: A Longer Survey","authors":["K Papantoniou, Y Tzitzikas - arXiv preprint arXiv:2408.10962, 2024"],"snippet":"English language is in the spotlight of the Natural Language Processing (NLP) community with other languages, like Greek, lagging behind in terms of offered methods, tools and resources. Due to the increasing interest in NLP, in this paper we …","url":["https://arxiv.org/pdf/2408.10962"]}
{"year":"2024","title":"NLP-ML Hybrid: Identifying Signs of Suicidal Thoughts in Social Media Content","authors":["RJR Samuel, A Jenefa, P Santhiya, GJL Paulraj… - 2024 2nd International …, 2024"],"snippet":"… Model Used: cc.en.300.bin represents the implementation of pre-trained embeddings on Common Crawl data with 300-dimensional vectors for the English language. 2) TF-IDF: The Term Frequency-Inverse Document Frequency (TF-IDF) is …","url":["https://ieeexplore.ieee.org/abstract/document/10761004/"]}
{"year":"2024","title":"No Filter: Cultural and Socioeconomic Diversityin Contrastive Vision-Language Models","authors":["A Pouget, L Beyer, E Bugliarello, X Wang, AP Steiner… - arXiv preprint arXiv …, 2024"],"snippet":"We study cultural and socioeconomic diversity in contrastive vision-language models (VLMs). Using a broad range of benchmark datasets and evaluation metrics, we bring to attention several important findings. First, the common filtering of training …","url":["https://arxiv.org/pdf/2405.13777"]}
{"year":"2024","title":"No Need to Talk: Asynchronous Mixture of Language Models","authors":["A Filippova, A Katharopoulos, D Grangier, R Collobert - arXiv preprint arXiv …, 2024"],"snippet":"We introduce SmallTalk LM, an innovative method for training a mixture of language models in an almost asynchronous manner. Each model of the mixture specializes in distinct parts of the data distribution, without the need of high-bandwidth …","url":["https://arxiv.org/pdf/2410.03529"]}
{"year":"2024","title":"Non-governmental Governance of Trust on the Internet: WebPKI as Public Good","authors":["K Grindal, M Mueller, V Srivastava"],"snippet":"… The population of sites we sampled from was indexed by the non-profit foundation Common Crawl. We then employed a script to pull certificate information from our list of URLs. Slightly more than half the sample did not return certificate …","url":["https://weis.utdallas.edu/files/2024/03/Grindal-et-al-WEIS-2024-0836cad1909f1424.pdf"]}
{"year":"2024","title":"Not All Countries Celebrate Thanksgiving: On the Cultural Dominance in Large Language Models","authors":["ECF German"],"snippet":"This paper identifies a cultural dominance issue within large language models (LLMs) due to the predominant use of English data in model training (eg, ChatGPT). LLMs often provide inappropriate English-culture-related answers that are not relevant to …","url":["https://openreview.net/pdf?id=Og0zmSOFEI0"]}
{"year":"2024","title":"Not All Tokens Are What You Need for Pretraining","authors":["Z Lin, Z Gou, Y Gong, X Liu, R Xu, C Lin, Y Yang, J Jiao… - The Thirty-eighth Annual …"],"snippet":"Previous language model pre-training methods have uniformly applied a next-token prediction loss to all training tokens. Challenging this norm, we posit that ''Not all tokens in a corpus are equally important for language model training''. Our initial …","url":["https://openreview.net/pdf?id=0NMzBwqaAJ"]}
{"year":"2024","title":"Notes towards infrastructure governance for large language models","authors":["L Dal Molin - First Monday, 2024"],"snippet":"This paper draws on information infrastructures (IIs) in science and technology studies (STS), as well as on feminist STS scholarship and contemporary critical accounts of digital technologies, to build an initial mapping of the infrastructural …","url":["https://firstmonday.org/ojs/index.php/fm/article/download/13567/11409"]}
{"year":"2024","title":"nowhash at SemEval-2024 Task 4: Exploiting Fusion of Transformers for Detecting Persuasion Techniques in Multilingual Memes","authors":["AN Chowdhury, M Ptaszynski - Proceedings of the 18th International Workshop on …, 2024"],"snippet":"Nowadays, memes are considered one of the most prominent forms of medium to disseminate information on social media. Memes are typically constructed in multilingual settings using visuals with texts. Sometimes people use memes to …","url":["https://aclanthology.org/2024.semeval-1.21.pdf"]}
{"year":"2024","title":"NRK at SemEval-2024 Task 1: Semantic Textual Relatedness through Domain Adaptation and Ensemble Learning on BERT-based models","authors":["NT Kiet, D Van Thin - Proceedings of the 18th International Workshop on …, 2024"],"snippet":"This paper describes the system of the team NRK for Task A in the SemEval-2024 Task 1: Semantic Textual Relatedness (STR). We focus on exploring the performance of ensemble architectures based on the voting technique and different …","url":["https://aclanthology.org/2024.semeval-1.13.pdf"]}
{"year":"2024","title":"NSINA: A News Corpus for Sinhala","authors":["H Hettiarachchi, D Premasiri, L Uyangodage… - arXiv preprint arXiv …, 2024"],"snippet":"The introduction of large language models (LLMs) has advanced natural language processing (NLP), but their effectiveness is largely dependent on pre-training resources. This is especially evident in low-resource languages, such as Sinhala …","url":["https://arxiv.org/pdf/2403.16571"]}
{"year":"2024","title":"Numerical Claim Detection in Finance: A New Financial Dataset, Weak-Supervision Model, and Market Analysis","authors":["A Shah, A Hiray, P Shah, A Banerjee, A Singh… - arXiv preprint arXiv …, 2024"],"snippet":"In this paper, we investigate the influence of claims in analyst reports and earnings calls on financial market returns, considering them as significant quarterly events for publicly traded companies. To facilitate a comprehensive analysis, we construct a …","url":["https://arxiv.org/pdf/2402.11728"]}
{"year":"2024","title":"NusaBERT: Teaching IndoBERT to be Multilingual and Multicultural","authors":["W Wongso, DS Setiawan, S Limcorn, A Joyoadikusumo - arXiv preprint arXiv …, 2024"],"snippet":"… We also note that NusaBERT was pre-trained on Wikipedia and common crawl corpora, which explains its effectiveness on and closeness to NusaX and NusaTranslation source domains, but not so for NusaParagraph. Thus, due to their high linguistic and …","url":["https://arxiv.org/html/2403.01817v1"]}
{"year":"2024","title":"Nyonic Technical Report","authors":["J Tian, R Wang, C Li, Y Zhou, J Liu, J Wang - arXiv preprint arXiv:2404.15702, 2024"],"snippet":"… Our curated dataset is specifically designed to meet these criteria, incorporating sources such as the Common Crawl, books, Wikipedia, code, and … Our data sources encompass Common Crawl, Wiki, and various coding repositories. The final …","url":["https://arxiv.org/pdf/2404.15702"]}
{"year":"2024","title":"Ocean Decade Vision 2030 White Papers–Challenge 8: Create a digital representation of the ocean.","authors":["JB Calewaert, PC Sierra-Correa, O McMeel… - 2024"],"snippet":"… The Common crawl and WebImageText are examples, with communities such as Hugging Face and KAGGLE creating new communities of practice16F … 17 https://commoncrawl.org, https://github.com/google-research-datasets/wit, https://huggingface.co, https://www.kaggle.com …","url":["https://aquadocs.org/bitstream/handle/1834/43137/WP8_v.2.0.docx.pdf?sequence=1&isAllowed=y"]}
{"year":"2024","title":"OF CLOSED NATIONAL WEB ARCHIVES THROUGH SUMMARIES","authors":["J Nielsen, Y Maurer, E Zierau - The Routledge Companion to Transnational Web …, 2024"],"snippet":"… are the national web archives placed at the national libraries of Denmark, France, Hungary, and Luxembourg as well as what has been preserved of these countries’ national country code top-level domains (ccTLDs) in the collections of the Internet …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=RLYyEQAAQBAJ&oi=fnd&pg=PA52&dq=commoncrawl&ots=ebVn40Yl74&sig=sC2wHRvUBJhMgMCa0HylVVZ4a2A"]}
{"year":"2024","title":"OF. LU DOMAIN NAMES THROUGH A TRANSNATIONAL COMPARISON","authors":["C Noguera, J Nielsen, Y Maurer, B Els - The Routledge Companion to Transnational …, 2024"],"snippet":"This chapter aims to study the development of the. lu domain by analysing the domain names from 1992 to 2022 and putting the results in perspective using a transnational approach. Part of the objective is to evaluate whether a method used …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=RLYyEQAAQBAJ&oi=fnd&pg=PA73&dq=commoncrawl&ots=ebVn40Yl74&sig=kqqAbo8fGuNTOLhV4g9uPVDrGrM"]}
{"year":"2024","title":"Offensive language detection in low resource languages: A use case of Persian language","authors":["M Mozafari, K Mnassri, R Farahbakhsh, N Crespi - PLOS ONE, 2024"],"snippet":"… XLM-RoBERTa [27]: is a transformer-based multilingual masked language model pre-trained on 100 languages, including Persian, using more than two terabytes of filtered CommonCrawl data. To fine-tune XLM-RoBERTa model on our target …","url":["https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0304166"]}
{"year":"2024","title":"OLMo: Accelerating the Science of Language Models","authors":["D Groeneveld, I Beltagy, P Walsh, A Bhagia, R Kinney… - arXiv preprint arXiv …, 2024"],"snippet":"… well on evaluations predominated by Common Crawl, such as C4, though different ways of postprocessing Common Crawl are best fit by … The RedPajama evaluation shows a similar pattern, perhaps as only 2 of its 7 domains are from …","url":["https://arxiv.org/pdf/2402.00838"]}
{"year":"2024","title":"OLMoE: Open Mixture-of-Experts Language Models","authors":["N Muennighoff, L Soldaini, D Groeneveld, K Lo… - arXiv preprint arXiv …, 2024"],"snippet":"We introduce OLMoE, a fully open, state-of-the-art language model leveraging sparse Mixture-of-Experts (MoE). OLMoE-1B-7B has 7 billion (B) parameters but uses only 1B per input token. We pretrain it on 5 trillion tokens and further adapt it to …","url":["https://arxiv.org/pdf/2409.02060"]}
{"year":"2024","title":"OmniDocBench: Benchmarking Diverse PDF Document Parsing with Comprehensive Annotations","authors":["L Ouyang, Y Qu, H Zhou, J Zhu, R Zhang, Q Lin… - arXiv preprint arXiv …, 2024"],"snippet":"… Specifically, we collected 200,000 initial PDF documents from Common Crawl, Google, Baidu search engines, and internal data. Subsequently, we extracted visual features from these document pages using ResNet-50 and performed clustering …","url":["https://arxiv.org/pdf/2412.07626"]}
{"year":"2024","title":"Omniview-Tuning: Boosting Viewpoint Invariance of Vision-Language Pre-training Models","authors":["S Ruan, Y Dong, H Liu, Y Huang, H Su, X Wei - arXiv preprint arXiv:2404.12139, 2024","X Wei"],"snippet":"Vision-Language Pre-training (VLP) models like CLIP have achieved remarkable success in computer vision and particularly demonstrated superior robustness to distribution shifts of 2D images. However, their robustness under 3D viewpoint …","url":["https://arxiv.org/pdf/2404.12139","https://link.springer.com/content/pdf/10.1007/978-3-031-73347-5_18.pdf"]}
{"year":"2024","title":"On humans'(explicit) intuitions about the meaning of novel words","authors":["D Gatti, F Rodio, L Rinaldi, M Marelli - Cognition, 2024"],"snippet":"Pseudowords offer a unique opportunity to investigate how humans deal with new (verbal) information. Within this framework, previous studies have shown that, at the implicit level, humans exploit systematic associations in the form-meaning interface to …","url":["https://www.sciencedirect.com/science/article/pii/S0010027724001689"]}
{"year":"2024","title":"On Initializing Transformers with Pre-trained Embeddings","authors":["HY Kim, N Balasubramanian, B Kang - arXiv preprint arXiv:2407.12514, 2024"],"snippet":"It has become common practice now to use random initialization schemes, rather than the pre-trained embeddings, when training transformer based models from scratch. Indeed, we find that pre-trained word embeddings from GloVe, and some …","url":["https://arxiv.org/pdf/2407.12514"]}
{"year":"2024","title":"On Instruction-Finetuning Neural Machine Translation Models","authors":["V Raunak, R Grundkiewicz, M Junczys-Dowmunt - arXiv preprint arXiv:2410.05553, 2024"],"snippet":"In this work, we introduce instruction finetuning for Neural Machine Translation (NMT) models, which distills instruction following capabilities from Large Language Models (LLMs) into orders-of-magnitude smaller NMT models. Our instruction-finetuning …","url":["https://arxiv.org/pdf/2410.05553"]}
{"year":"2024","title":"On Labs and Fabs: Mapping How Alliances, Acquisitions, and Antitrust are Shaping the Frontier AI Industry","authors":["T Aguirre - arXiv preprint arXiv:2406.01722, 2024"],"snippet":"As frontier AI models progress, policy proposals for safe AI development are gaining increasing attention from researchers and policymakers. This paper evaluates the present landscape of integration within the AI supply chain, emphasizing vertical …","url":["https://arxiv.org/pdf/2406.01722"]}
{"year":"2024","title":"On Protecting the Data Privacy of Large Language Models (LLMs): A Survey","authors":["B Yan, K Li, M Xu, Y Dong, Y Zhang, Z Ren, X Cheng - arXiv preprint arXiv …, 2024"],"snippet":"… For example, GPT-3, developed by OpenAI, was pre-trained using CommonCrawl, constituting 45TB of compressed plaintext before filtering [37]. Regarding multimodal LLMs, CLIP’s training dataset encompasses 400 million pairs of images and text …","url":["https://arxiv.org/pdf/2403.05156"]}
{"year":"2024","title":"On the data scarcity problem of neural-based named entity recognition","authors":["R Zhou - 2023"],"snippet":"… The initial release trained on Wikipedia includes word representations for nine languages, namely Arabic, Czech, German, English, Spanish, French, Italian, Romanian and Russian, and has quickly expanded to 157 languages by training on larger …","url":["https://dr.ntu.edu.sg/bitstream/10356/173481/2/Thesis_ZhouRan_final.pdf"]}
{"year":"2024","title":"On the evaluation and application of neural language models for grammatical error detection","authors":["C Davis - 2024"],"snippet":"Neural language models (NLM) have become a core component in many downstream applications within the field of natural language processing, including the task of data-driven automatic grammatical error detection (GED). This thesis …","url":["https://www.repository.cam.ac.uk/bitstreams/f9ca765c-f10e-4b64-8c10-3d3b7d38810d/download"]}
{"year":"2024","title":"On the importance of Data Scale in Pretraining Arabic Language Models","authors":["A Ghaddar, P Langlais, M Rezagholizadeh, B Chen - arXiv preprint arXiv:2401.07760, 2024"],"snippet":"Pretraining monolingual language models have been proven to be vital for performance in Arabic Natural Language Processing (NLP) tasks. In this paper, we conduct a comprehensive study on the role of data in Arabic Pretrained Language …","url":["https://arxiv.org/pdf/2401.07760"]}
{"year":"2024","title":"On the In-context Generation of Language Models","authors":["Z Jiang, Y Zhang, K Luo, X Yuan, J Zhao, K Liu - … of the 2024 Conference on Empirical …, 2024"],"snippet":"… As known, typical pretrained corpora contain (eg CommonCrawl1) internet data which has an unneglectable portion of array-page data such as IMDB2 review pages. After preprocessing, these pages are converted to repetition mode data, as shown in …","url":["https://aclanthology.org/2024.emnlp-main.568.pdf"]}
{"year":"2024","title":"On the Mathematical Relationship Between Contextual Probability and N400 Amplitude","authors":["JA Michaelov, BK Bergen - Open Mind, 2024"],"snippet":"Accounts of human language comprehension propose different mathematical relationships between the contextual probability of a word and how difficult it is to process, including linear, logarithmic, and super-logarithmic ones. However, the …","url":["https://direct.mit.edu/opmi/article/doi/10.1162/opmi_a_00150/123704"]}
{"year":"2024","title":"On the Question of Authorship in Large Language Models","authors":["C Soos, L Haroutunian - KO KNOWLEDGE ORGANIZATION, 2024"],"snippet":"… CommonCrawl exemplifies the problem of documentation debt. The dataset is an effort by The Common Crawl Foundation to “[democratize] access to web information by producing and maintaining an open repository of web crawl data” (Common …","url":["https://www.nomos-elibrary.de/10.5771/0943-7444-2024-2-83.pdf"]}
{"year":"2024","title":"On the Relationship of Social Gender Equality and Grammatical Gender in Pre-trained Large Language Models","authors":["M Biesialska, D Solans, J Luque, C Segura - 2024"],"snippet":"Large Language Models pre-trained on vast amounts of text have demonstrated remarkable capabilities in modeling and generating human language, finding applications across a wide range of Natural Language Processing tasks. However …","url":["https://besaya.infor.uva.es/sepln24/paper01.pdf"]}
{"year":"2024","title":"On the Robustness of Neural Networks Quantization against Data Poisoning Attacks","authors":["Y Lu, Y Wang, G Zhang, Y Yu - ICML 2024 Next Generation of AI Safety Workshop"],"snippet":"… For example, practitioners may continuously collect user data online (eg, using Common Crawl1), which may be maliciously contaminated by an attacker. Such a threat is called data poisoning attacks (Biggio et al. 2012), … https://commoncrawl.org/ …","url":["https://openreview.net/pdf?id=YuXWnkhZOj"]}
{"year":"2024","title":"On the Tip of the Tongue: Analyzing Conceptual Representation in Large Language Models with Reverse-Dictionary Probe","authors":["N Xu, Q Zhang, M Zhang, P Qian, X Huang - arXiv preprint arXiv:2402.14404, 2024"],"snippet":"Probing and enhancing large language models' reasoning capacity remains a crucial open question. Here we re-purpose the reverse dictionary task as a case study to probe LLMs' capacity for conceptual inference. We use in-context learning …","url":["https://arxiv.org/pdf/2402.14404"]}
{"year":"2024","title":"One Law, Many Languages: Benchmarking Multilingual Legal Reasoning for Judicial Support","authors":["V Rasiah, R Stern, V Matoshi, M Stürmer, I Chalkidis…"],"snippet":"Recent strides in Large Language Models (LLMs) have saturated many NLP benchmarks (even professional domain-specific ones), emphasizing the need for more challenging ones to properly assess LLM capabilities. Domain-specific and …","url":["https://openreview.net/pdf?id=7vkz7cKd1X"]}
{"year":"2024","title":"Online health search via multi-dimensional information quality assessment based on deep language models","authors":["B Zhang, N Naderi, R Mishra, D Teodoro - 2024"],"snippet":"Background Widespread misinformation in Web resources can lead to serious implications for individuals seeking health advice. Despite that, information retrieval models are often focused only on the query-document relevance dimension to rank …","url":["https://hal.science/hal-04419996/"]}
{"year":"2024","title":"Online Health Search Via Multidimensional Information Quality Assessment Based on Deep Language Models: Algorithm Development and Validation","authors":["B Zhang, N Naderi, R Mishra, D Teodoro - JMIR AI, 2024"],"snippet":"… In this study, we simulated online health information search scenarios with a topic set of 32 different health-related inquiries and a corpus containing 1 billion web documents from the April 2019 snapshot of Common Crawl. Using state-of-the-art …","url":["https://ai.jmir.org/2024/1/e42630"]}
{"year":"2024","title":"OnlySportsLM: Optimizing Sports-Domain Language Models with SOTA Performance under Billion Parameters","authors":["Z Chen, C Li, X Xie, P Dube - arXiv preprint arXiv:2409.00286, 2024"],"snippet":"This paper explores the potential of a small, domain-specific language model trained exclusively on sports-related data. We investigate whether extensive training data with specially designed small model structures can overcome model size …","url":["https://arxiv.org/pdf/2409.00286"]}
{"year":"2024","title":"Ontology Completion with Natural Language Inference and Concept Embeddings: An Analysis","authors":["N Li, T Bailleux, Z Bouraoui, S Schockaert - arXiv preprint arXiv:2403.17216, 2024"],"snippet":"We consider the problem of finding plausible knowledge that is missing from a given ontology, as a generalisation of the well-studied taxonomy expansion task. One line of work treats this task as a Natural Language Inference (NLI) problem, thus relying …","url":["https://arxiv.org/html/2403.17216v1"]}
{"year":"2024","title":"Open Assistant Toolkit--version 2","authors":["S Fischer, F Rossetto, C Gemmell, A Ramsay, I Mackie… - arXiv preprint arXiv …, 2024"],"snippet":"… To source knowledge and tasks, we release a new offline pipeline to parse and augment task data from CommonCrawl. The offline pipeline supports using LLMs and additional open-source multimodal data sources to enhance tasks and make …","url":["https://arxiv.org/pdf/2403.00586"]}
{"year":"2024","title":"Open foundation models for Azerbaijani language","authors":["J Isbarov, K Huseynova, E Mammadov, M Hajili - arXiv preprint arXiv:2407.02337, 2024"],"snippet":"The emergence of multilingual large language models has enabled the development of language understanding and generation systems in Azerbaijani. However, most of the production-grade systems rely on cloud solutions, such as GPT-4 …","url":["https://arxiv.org/pdf/2407.02337"]}
{"year":"2024","title":"Open Science at the Generative AI Turn: An Exploratory Analysis of Challenges and Opportunities","authors":["M Hosseini, SPJM Horbach, K Holmes…"],"snippet":"Technology influences Open Science (OS) practices, because conducting science in transparent, accessible, and participatory ways requires tools/platforms for collaborative research and sharing results. Due to this direct relationship …","url":["https://osf.io/zns7g/download"]}
{"year":"2024","title":"Open Source Software Policy in Industry Equilibrium","authors":["J Gortmaker - 2024"],"snippet":"… I start with homepages of the top 10,000 most visited websites, archived by Common Crawl (Appendix B) in each month from 2014 to 2022… When Common Crawl fails to archive a homepage, I assume its software remains unchanged from …","url":["https://jeffgortmaker.com/files/Open_Source_Software_Policy_in_Industry_Equilibrium.pdf"]}
{"year":"2024","title":"Open-FinLLMs: Open Multimodal Large Language Models for Financial Applications","authors":["Q Xie, D Li, M Xiao, Z Jiang, R Xiang, X Zhang, Z Chen… - arXiv preprint arXiv …, 2024"],"snippet":"Large language models (LLMs) have advanced financial applications, yet they often lack sufficient financial knowledge and struggle with tasks involving multi-modal inputs like tables and time series data. To address these limitations, we introduce \\textit{Open-FinLLMs} …","url":["https://arxiv.org/pdf/2408.11878"]}
{"year":"2024","title":"OpenAI ChatGPT and Biased Information in Higher Education","authors":["MJ O'Brien, I Alsmadi"],"snippet":"Motivated by the appearance of large language models and their sudden societal impacts—both beneficial and harmful, realized and potential—we evaluated several of them with respect to bias in its myriad forms. Bias in machine-learning models …","url":["https://apps.tamusa.edu/course-information/syllabi/Spring2024/Open-AI-Chat-GPT-and-Bias-by-OBrien-and-Alsmadi.pdf"]}
{"year":"2024","title":"OpenForge: Probabilistic Metadata Integration","authors":["T Cong, F Nargesian, J Xing, HV Jagadish - arXiv preprint arXiv:2412.09788, 2024"],"snippet":"Modern data stores increasingly rely on metadata for enabling diverse activities such as data cataloging and search. However, metadata curation remains a labor-intensive task, and the broader challenge of metadata maintenance -- ensuring its consistency …","url":["https://arxiv.org/pdf/2412.09788"]}
{"year":"2024","title":"OpenMoE: An Early Effort on Open Mixture-of-Experts Language Models","authors":["F Xue, Z Zheng, Y Fu, J Ni, Z Zheng, W Zhou, Y You - arXiv preprint arXiv:2402.01739, 2024"],"snippet":"To help the open-source community have a better understanding of Mixture-of-Experts (MoE) based large language models (LLMs), we train and release OpenMoE, a series of fully open-sourced and reproducible decoder-only MoE LLMs, ranging from …","url":["https://arxiv.org/pdf/2402.01739"]}
{"year":"2024","title":"OPI: An Open Instruction Dataset for Adapting Large Language Models to Protein-Related Tasks","authors":["H Xiao, W Lin, H Wang, Z Liu, Q Ye - Neurips 2024 Workshop Foundation Models for …"],"snippet":"Large language models (LLMs) pretrained on extensive general corpora, such as GPT-4 and Llama series, have demonstrated remarkable excellence in a large variety of natural language processing (NLP) tasks. These models provide a user-friendly …","url":["https://openreview.net/pdf?id=I4bA7ekJGh"]}
{"year":"2024","title":"OptiComm-GPT: a GPT-based versatile research assistant for optical fiber communication systems","authors":["X Jiang, M Zhang, Y Song, Y Zhang, Y Wang, C Ju… - Optics Express, 2024"],"snippet":"… Generally, LLMs are pre-trained on publicly available datasets such as BooksCorpus, Common Crawl, and Wikipedia, thereby ensuring comprehensive coverage of knowledge. Meanwhile, with the support of powerful analysis, reasoning …","url":["https://opg.optica.org/oe/fulltext.cfm?uri=oe-32-12-20776"]}
{"year":"2024","title":"Optimization and Evaluation in Machine Learning Challenges","authors":["J Pokrywka"],"snippet":"To develop new machine learning methods, it is necessary to evaluate them reliably. This doctoral thesis discusses some aspects of preparing machine learning challenges and techniques for developing their solutions. The work consists of …","url":["https://repozytorium.amu.edu.pl/bitstreams/7a38c2a1-c992-4fa5-9ece-1c73f1024154/download"]}
{"year":"2024","title":"Optimization Hyper-parameter Laws for Large Language Models","authors":["X Xie, K Ding, S Yan, KC Toh, T Wei - arXiv preprint arXiv:2409.04777, 2024"],"snippet":"Large Language Models have driven significant AI advancements, yet their training is resource-intensive and highly sensitive to hyper-parameter selection. While scaling laws provide valuable guidance on model size and data requirements, they …","url":["https://arxiv.org/pdf/2409.04777"]}
{"year":"2024","title":"Optimization of news dissemination push mode by intelligent edge computing technology for deep learning","authors":["JL DeGe, S Sang - Scientific Reports, 2024"],"snippet":"… Realnew (https://paperswithcode.com/dataset/realnews) is a large corpus of news articles from CommonCrawl. The data is crawled from CommonCrawl, which is limited to 5000 news fields of Google News Index. The author uses the …","url":["https://www.nature.com/articles/s41598-024-53859-7"]}
{"year":"2024","title":"Optimization of Unsupervised Neural Machine Translation Based on Syntactic Knowledge Improvement","authors":["A Zhou - Optimization, 2023"],"snippet":"… Common Crawl is a multilingual aligned dataset based on web crawling. Para Crawl is a multilingual parallel corpus for large-scale web crawling. As shown in Table III, the detection accuracies of LSTM in Newstest2020, Newstest2021 …","url":["https://search.proquest.com/openview/b003a8244f2be3b8735b21ff0421e7d0/1?pq-origsite=gscholar&cbl=5444811"]}
{"year":"2024","title":"Optimizing Data I/O for LLM Datasets on Remote Storage","authors":["T Zhong, J Zhao, X Guo, Q Su, G Fox"],"snippet":"Training large language models (LLMs) demands increasingly larger datasets for optimal performance [13]. In practice, these datasets may include hundreds of terabytes (TB) or even petabytes of data. For example, Common Crawl [3] needs …","url":["https://luosuu.github.io/assets/files/AIOps_24.pdf"]}
{"year":"2024","title":"Optimizing Knowledge Extraction in Large Language Models Using Dynamic Tokenization Dictionaries","authors":["H Chiappe, G Lennon"],"snippet":"Tokenization methods have long been a critical component in the performance of language models, yet traditional static approaches often fall short in capturing the dynamic nature of language. The novel concept of implementing a dynamic …","url":["https://osf.io/svj2z/download"]}
{"year":"2024","title":"Optimizing Language Augmentation for Multilingual Large Language Models: A Case Study on Korean","authors":["CS Choi, Y Jeong, S Park, IH Won, HS Lim, SM Kim… - arXiv preprint arXiv …, 2024"],"snippet":"… Llama2 is a multilingual language model trained using largescale publicly available data (including CommonCrawl, Github, Wikipedia, and ArXiv) for more than 28 languages. Thus, it possesses cross-language understanding capabilities …","url":["https://arxiv.org/pdf/2403.10882"]}
{"year":"2024","title":"Optimizing Large Language Models with Multi-Degree Low-Rank Approximations","authors":["B Sisoka, W Robinson - 2024"],"snippet":"… The use of datasets such as Common Crawl and Wikipedia facilitated a broad coverage of language variations, enhancing the generalizability of the results. Preprocessing steps were critical to ensure data quality and consistency, involving …","url":["https://www.researchsquare.com/article/rs-4966694/latest.pdf"]}
{"year":"2024","title":"Optimizing Low-Resource Language Model Training: Comprehensive Analysis of Multi-Epoch, Multi-Lingual, and Two-Stage Approaches","authors":["K Akimoto, M Oyamada - arXiv preprint arXiv:2410.12325, 2024"],"snippet":"In this paper, we address the challenge of optimizing training setups for Large Language Models (LLMs) of low-resource language with a limited amount of corpus. Existing works adopt multi-epoch, multi-lingual, and two-stage training to utilize the …","url":["https://arxiv.org/pdf/2410.12325"]}
{"year":"2024","title":"Optimizing Phishing Site Detection: Analyzing the Impact of Feature Quantity in Random Forest Model","authors":["T Nabila, HH Nuha, SA Kristyan - 2024 International Conference on Data Science …, 2024"],"snippet":"… The first dataset used is a dataset consisting of 5000 phishing sites and 5000 normal sites with 48 features using the Selenium Webdriver framework for extraction technique, This first dataset was collected and selected from Alexa and Common …","url":["https://ieeexplore.ieee.org/abstract/document/10651836/"]}
{"year":"2024","title":"Optimizing Quality Estimation for Low-Resource Language Translations: Exploring the Role of Language Relatedness","authors":["A Sindhujan, D Kanojia, C Orasan - Proceedings of the Conference New Trends in …, 2024"],"snippet":"Evaluation of machine translation (MT) is vital to determine the effectiveness of MT systems. This paper investigates quality estimation (QE) for machine translation (MT) for low-resource Indic languages. We analyse the influence of language relatedness …","url":["https://openresearch.surrey.ac.uk/esploro/fulltext/conferencePaper/Optimizing-Quality-Estimation-for-Low-Resource-Language/99916366502346?repId=12209300940002346&mId=13209300930002346&institution=44SUR_INST"]}
{"year":"2024","title":"Optimizing Sentiment Classification Using Dynamic Weighted Stacking Ensemble of Pre-trained Models","authors":["L Kuang, M Liu, G Chen, Y Tang, Z Duan, X Li, P Li… - 2024"],"snippet":"In the era of information explosion, sentiment classification, as a crucial task in natural language processing, is widely applied across various fields, including e-commerce, media, government, and finance. This paper proposes a dynamic weighted stacking …","url":["https://www.researchsquare.com/article/rs-5408406/latest.pdf"]}
{"year":"2024","title":"Optimizing social determinant of health concept extraction","authors":["N Singh - 2024"],"snippet":"Generative Artificial Intelligence has recently garnered enormous attention for a varied number of reasons, one of them being its capacity to automate complex tasks. As the potential for integrating Generative Artificial Intelligence across technology …","url":["https://digitalcommons.njit.edu/cgi/viewcontent.cgi?article=3606&context=theses"]}
{"year":"2024","title":"ORBIT: Cost-Effective Dataset Curation for Large Language Model Domain Adaptation with an Astronomy Case Study","authors":["E Modesitt, K Yang, S Hulsey, C Zhai, V Kindratenko - arXiv preprint arXiv …, 2024"],"snippet":"… FineWeb-Edu is a specialized subset of FineWeb, which is a large-scale, high-quality dataset derived from CommonCrawl web data, specifically designed for pretraining large language models. The FineWeb-Edu dataset uses the Open Data Commons …","url":["https://arxiv.org/pdf/2412.14436"]}
{"year":"2024","title":"ORCID","authors":["P Gries"],"snippet":"How are Asian and Black men and women stereotyped? Research from the gendered race and stereotype content perspectives has produced mixed empirical findings. Using BERT models pre-trained on English language books, news articles …","url":["https://psychbruce.github.io/paper/Bao_Accepted_BJSP_FMAT_Stereotype_Manuscript.pdf"]}
{"year":"2024","title":"Organic Data-Driven Approach for Turkish Grammatical Error Correction and LLMs","authors":["A Ersoy, OT Yıldız - arXiv preprint arXiv:2405.15320, 2024"],"snippet":"… 2020) which contains random paragraphs sampled from the CommonCrawl dataset3. Some studies put some effort into filling the gap and … 2020), a multilingual pre-trained encoder-decoder text-to-text transformer trained on a Common Crawl-based …","url":["https://arxiv.org/pdf/2405.15320"]}
{"year":"2024","title":"OS Agents: A Survey on MLLM-Based Agents for General Computing Devices Use","authors":["X Hu, T Xiong, B Yi, Z Wei, R Xiao, Y Chen, J Ye, M Tao… - 2024"],"snippet":"… [17] utilized CommonCrawl to acquire HTML documents, removing those with non-unicode or purely alphanumeric content, and extracted subtrees around ‘<label>’ elements to train HTML-T5, a model capable of providing executable instructions. Similarly …","url":["https://www.preprints.org/frontend/manuscript/3842b6163d82801988adf663ee18b6d5/download_pub"]}
{"year":"2024","title":"OS-ATLAS: A Foundation Action Model for Generalist GUI Agents","authors":["Z Wu, Z Wu, F Xu, Y Wang, Q Sun, C Jia, K Cheng… - arXiv preprint arXiv …, 2024"],"snippet":"… 2024), a cleaned and deduplicated English dataset derived from CommonCrawl For each webpage, we extracted all visible clickable elements from the HTML code — including buttons, scroll bars, search bars, hyperlinks, and SVG images with titles …","url":["https://arxiv.org/pdf/2410.23218"]}
{"year":"2024","title":"Outlier Detection in Serbian CommonCrawl Data","authors":["V Kalušev, D Ćulibrk - 2024 23rd International Symposium INFOTEH …, 2024"],"snippet":"The surge in large language models (LLMs) has greatly advanced natural language processing. However, their development is often hampered by the limited availability and quality of training datasets, particularly for underrepresented languages. Our …","url":["https://ieeexplore.ieee.org/abstract/document/10495987/"]}
{"year":"2024","title":"Outsmarting Artificial Intelligence in the Classroom—Incorporating Large Language Model-Based Chatbots into Teaching","authors":["J Wutzler - Issues in Accounting Education, 2024"],"snippet":"Since the release of ChatGPT in November 2022, large language model-based chatbots have attracted much attention. Although businesses value their potential for efficiency gains, academics are concerned about their effects on learning and …","url":["https://publications.aaahq.org/iae/article/doi/10.2308/ISSUES-2023-064/12560"]}
{"year":"2024","title":"Overcoming Language Barriers in Classification through Translation-Augmented Data","authors":["V Noémi, N Vlad-Andrei, T Sebastian-Antonio… - 2024 IEEE 20th …, 2024"],"snippet":"This paper addresses the challenge of adapting a multilingual language model to an unseen language by using translations to augment the training dataset. We evaluate how fine-tuning a model with Hungarian data obtained through translations impacts …","url":["https://ieeexplore.ieee.org/abstract/document/10793053/"]}
{"year":"2024","title":"Overcoming the Labeled Training Data Bottleneck","authors":["R Starzl - The Cyber Defense Review, 2024"],"snippet":"This article explores the potential of large language models (LLMs) to transform dataset creation and analysis in cybersecurity. The proposed method leverages LLMs to overcome the labeled data bottleneck by generating high-quality, task-specific …","url":["https://www.jstor.org/stable/48784778"]}
{"year":"2024","title":"Overcoming the Labeled Training Data Bottleneck: A Route to Specialized AI","authors":["R Starzl - 2024"],"snippet":"This article explores the potential of large language models (LLMs) to transform dataset creation and analysis in cybersecurity. The proposed method leverages LLMs to overcome the labeled data bottleneck by generating high-quality, task-specific …","url":["https://cyberdefensereview.army.mil/Portals/6/Documents/2024_Summer/Starzl_CDRV9N2-SE-Summer-2024.pdf"]}
{"year":"2024","title":"Overdetermination of businesswomen in the British press: a corpus-based approach in critical discourse analysis","authors":["TNT Nguyen - ICTE Conference Proceedings, 2024"],"snippet":"Within the strand of critical discourse analysis (CDA), research on media portrayal of individuals is prevalent, with the scope having been expanded beyond such subjects as refugees or asylum seekers, but also the breadth of research having …","url":["https://i-cte.org/proceedings/index.php/ictep/article/download/74/27"]}
{"year":"2024","title":"Overview of Existing LLM Families","authors":["A Kucharavy - Large, 2024"],"snippet":"… data that are considered as redundant—namely the Common Crawl and Colossal Cleaned Common Crawl (C4). Researchers who created the … to Common Crawl when it came to training LLMs [30] and should be used instead of the whole …","url":["https://link.springer.com/content/pdf/10.1007/978-3-031-54827-7.pdf#page=47"]}
{"year":"2024","title":"Overview of the TREC 2023 NeuCLIR Track (Notebook Paper)","authors":["D Lawrie, S MacAvaney, J Mayfield, P McNamee…"],"snippet":"… For more information about extracting the text for the documents from CommonCrawl News and how the collection can be obtained, see … of the track including HC4 — a CLIR collection built over three years of Common Crawl data in …","url":["https://terpconnect.umd.edu/~oard/pdf/trec23neuclir-notebook.pdf"]}
{"year":"2024","title":"P-Masking: Power Law Masking Improves Multi-attribute Controlled Generation","authors":["M Elgaar, H Amiri - arXiv preprint arXiv:2410.24201, 2024"],"snippet":"We introduce LingGen, a novel approach for controlled text generation that offers precise control over a wide array of linguistic attributes, even as the number of attributes varies. LingGen employs a dynamic P-MASKING strategy, which samples …","url":["https://arxiv.org/pdf/2410.24201?"]}
{"year":"2024","title":"Pack of LLMs: Model Fusion at Test-Time via Perplexity Optimization","authors":["C Mavromatis, P Karypis, G Karypis - arXiv preprint arXiv:2404.11531, 2024"],"snippet":"… 2019) is sa publicly available distribution of a Common Crawl snapshot. Following cBTM, we use 168B tokens of the no blocklist version (en.noblocklist) that is out of distribution to the OPT model’s pretraining corpus. S2ORC (Lo et al.…","url":["https://arxiv.org/pdf/2404.11531"]}
{"year":"2024","title":"PAL: Proxy-Guided Black-Box Attack on Large Language Models","authors":["C Sitawarin, N Mu, D Wagner, A Araujo - arXiv preprint arXiv:2402.09674, 2024"],"snippet":"Large Language Models (LLMs) have surged in popularity in recent months, but they have demonstrated concerning capabilities to generate harmful content when manipulated. While techniques like safety fine-tuning aim to minimize harmful use …","url":["https://arxiv.org/pdf/2402.09674"]}
{"year":"2024","title":"Palöri at CheckThat! 2024 Shared Task 6: GloTa-Combining GloVe Embeddings with RoBERTa for Adversarial Attack","authors":["H He, Y Song, D Massey - 2024"],"snippet":"This paper describes the submission of attack methods and results for shared task 6 at CheckThat! Lab at CLEF 2024. We present two novel attack methods to test the robustness of credibility assessment (CA) classifiers across five tasks: fact-checking …","url":["https://ceur-ws.org/Vol-3740/paper-43.pdf"]}
{"year":"2024","title":"Pandemic Surveillance Using Social Media Data, Natural Language Processing, and Machine Learning","authors":["Y Liu - 2024"],"snippet":"… The custom NER model that we trained was based on spaCy’s multi-task, OntoNotes-trained Convolutional Neural Network which uses GloVe vectors that were trained using Common Crawl [103] corpus. Topic modeling is an unsupervised …","url":["https://search.proquest.com/openview/8bcafb9de988ee1058b7b43c170b8708/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
{"year":"2024","title":"Parallel Corpus Augmentation using Masked Language Models","authors":["V Kumari, NM Kavi - arXiv preprint arXiv:2410.03194, 2024"],"snippet":"In this paper we propose a novel method of augmenting parallel text corpora which promises good quality and is also capable of producing many fold larger corpora than the seed corpus we start with. We do not need any additional monolingual …","url":["https://arxiv.org/pdf/2410.03194"]}
{"year":"2024","title":"Parallel Motif-Based Community Detection","authors":["T Chen, CE Tsourakakis"],"snippet":"… For networks like Commoncrawl and Friendster, the execution times are highly reduced by increasing the number of works, gradually becoming comparable to the competitors. Furthermore, we display the relation between memory usage and the …","url":["https://tsourakakis.com/wp-content/uploads/2024/11/parallel_motif_based_communities.pdf"]}
{"year":"2024","title":"Parameter Efficiency, Few-Shot, Zero-Shot, Prompting","authors":["J May - 2024"],"snippet":"The models we’ve discussed so far follow the paradigm that, out of the box, they don’t do too much, but when you expose them to some supervised data that is an exemplar of a task and fine-tune their parameters they can do the task when given …","url":["https://jonmay.github.io/USC-CS662/assets/files/llm.pdf"]}
{"year":"2024","title":"Parameter-Efficient Fine-Tuning in Large Models: A Survey of Methodologies","authors":["L Wang, S Chen, L Jiang, S Pan, R Cai, S Yang… - arXiv preprint arXiv …, 2024"],"snippet":"The large models, as predicted by scaling raw forecasts, have made groundbreaking progress in many fields, particularly in natural language generation tasks, where they have approached or even surpassed human levels. However, the …","url":["https://arxiv.org/pdf/2410.19878"]}
{"year":"2024","title":"Parameter-Efficient Tuning of Large Convolutional Models","authors":["W Chen, Z Miao, Q Qiu - arXiv preprint arXiv:2403.00269, 2024"],"snippet":"To address the high computational and parameter complexity associated with fine-tuning large pre-trained models, researchers have developed parameter-efficient methods, where only partial parameters are updated for downstream tasks. However, these …","url":["https://arxiv.org/pdf/2403.00269"]}
{"year":"2024","title":"Paraphrase Generation and Supervised Learning for Improved Automatic Short Answer Grading","authors":["L Ouahrani, D Bennouar - International Journal of Artificial Intelligence in …, 2024"],"snippet":"We consider the reference-based approach for Automatic Short Answer Grading (ASAG) that involves scoring a textual constructed student answer comparing to a teacher-provided reference answer. The reference answer does not cover the variety of student …","url":["https://link.springer.com/article/10.1007/s40593-023-00391-w"]}
{"year":"2024","title":"Parsability revisited and reassessed","authors":["S Monakhov - Journal of Linguistics, 2023"],"snippet":"This paper provides evidence that the inveterate way of assessing linguistic items’ degrees of analysability by calculating their derivation to base frequency ratios may obfuscate the difference between two meaning processing models: one based on …","url":["https://www.cambridge.org/core/services/aop-cambridge-core/content/view/896CFA4F3C89952AF52611DCBCD262B3/S0022226723000385a.pdf/parsability-revisited-and-reassessed.pdf"]}
{"year":"2024","title":"Part-of-Speech Tagger for Bodo Language using Deep Learning approach","authors":["D Pathak, S Narzary, S Nandi, B Som - arXiv preprint arXiv:2401.03175, 2024"],"snippet":"Language Processing systems such as Part-of-speech tagging, Named entity recognition, Machine translation, Speech recognition, and Language modeling (LM) are well-studied in high-resource languages. Nevertheless, research on these …","url":["https://arxiv.org/pdf/2401.03175"]}
{"year":"2024","title":"Past Influences, Present Ethics: How History Shapes AI Decision-Making and Technological Futures","authors":["MK Jean-Pierre"],"snippet":"OpenAI’s release of products such as Chat-GPT, DALL-E, and Sora have recently triggered existential debates around artificial intelligence and its ultimate impact on humanity. While previous innovations seen as quite banal today have gone through …","url":["https://thesis.eur.nl/pub/75140/17206.pdf"]}
{"year":"2024","title":"Pathological Liars: Algorithmic Knowing in the Rhetorical Ecosystem of Wallstreetbets","authors":["MH Yang, ZP Majdik - Rhetoric Society Quarterly, 2024"],"snippet":"This essay demonstrates the value of using artificial intelligence (AI) technologies to address specific kinds of research questions in rhetoric. The essay builds on a study of a novel rhetorical object first observed by Yang on the Reddit subreddit r/wallstreetbets …","url":["https://www.tandfonline.com/doi/abs/10.1080/02773945.2024.2343616"]}
{"year":"2024","title":"Pathological-Llama: an Explainable Medical Visual Question An","authors":["S Nguyen - 2024"],"snippet":"This thesis introduces Pathological-Llama, an explainable medical visual question answering system that integrates computer vision and natural language processing to accurately interpret medical images through a generative task approach. By …","url":["https://www.zhaw.ch/storage/engineering/institute-zentren/cai/studentische_arbeiten/Herbst_2023/MSE__Master_Thesis_23_bogo_PathologicalLlama.pdf"]}
{"year":"2024","title":"PE-GPT: A New Paradigm for Power Electronics Design","authors":["F Lin, X Li, W Lei, JJ Rodriguez-Andina, JM Guerrero… - IEEE Transactions on …, 2024"],"snippet":"Large language models (LLMs) have shown exciting potential in powering the growth of many industries, yet their adoption in the power electronics (PE) sector is hindered by a lack of specialized PE technical expertise and challenges in …","url":["https://ieeexplore.ieee.org/abstract/document/10701612/"]}
{"year":"2024","title":"Pedro L. Rodriguez Arthur Spirling Brandon M. Stewart Elisa M. Wirsching","authors":["BM Stewart"],"snippet":"… from Common Crawl and Wikipedia. A strength of the fastText model is that it uses subword … On inspection, we saw that Common Crawl includes many typos and rare terms (plus many … Beyond this potential for noise, Common Crawl is not …","url":["https://alcembeddings.org/assets/img/RSSW_paper_january_2024.pdf"]}
{"year":"2024","title":"Performance Analysis of Embedding Methods for Deep Learning-Based Turkish Sentiment Analysis Models","authors":["A Ba Alawi, F Bozkurt - Arabian Journal for Science and Engineering, 2024"],"snippet":"… Then, we chose the model which is specifically for Turkish that was trained using data from Common Crawl and Wikipedia. It employs position-weighted Continuous Bag of Words (CBOW) architecture. The model has a size of 300 and includes 5-character …","url":["https://link.springer.com/article/10.1007/s13369-024-09360-4"]}
{"year":"2024","title":"Performance Comparison of Large Language Models, GPT and Gemini on Turkish News Classification Task","authors":["ZA Guven - 2024"],"snippet":"… This was achieved by training a Transformer-based masked language model on 100 languages using more than two terabytes of filtered CommonCrawl data. The balance between high and low-resource languages and the impact of language …","url":["https://www.researchsquare.com/article/rs-4351735/latest.pdf"]}
{"year":"2024","title":"Performance Comparison of Transformer-based Intrusion Detection Model According to the Change of Character Encoding","authors":["KJ Kim, SJ Lee - Convergence Security Journal, 2024"],"snippet":"A tokenizer, which is a key component of the Transformer model, lacks the ability to effectively comprehend numerical data. Therefore, to develop a Transformer-based intrusion detection model that can operate within a real-world network environment …","url":["https://koreascience.kr/article/JAKO202430980358403.pdf"]}
{"year":"2024","title":"Performance Evaluation of Internet Domain Ranking Methodologies","authors":["D Maleki, P Goudarzi, A Mansouri","P Goudarzi, D Maleki, A Mansouri"],"snippet":"… Common Crawl platform follows a similar approach in its web graphs [27]. Common Crawl data is widely used for research in various fields. … In this method, the focus is on the breadth instead of the depth of the hosts, that is, Common Crawl …","url":["https://journal.itrc.ac.ir/article-1-635-en.pdf","https://journal.itrc.ac.ir/browse.php?a_id=635&sid=1&slc_lang=en&ftxt=1"]}
{"year":"2024","title":"Performance Evaluation of Tokenizers in Large Language Models for the Assamese Language","authors":["S Tamang, DJ Bora - arXiv preprint arXiv:2410.03718, 2024"],"snippet":"Training of a tokenizer plays an important role in the performance of deep learning models. This research aims to understand the performance of tokenizers in five state-of-the-art (SOTA) large language models (LLMs) in the Assamese language of India. The …","url":["https://arxiv.org/pdf/2410.03718"]}
{"year":"2024","title":"Performance Evaluation of Word Embedding Algorithms","authors":["S Kulshretha, L Lodha - Performance Evaluation, 2023"],"snippet":"This study intends to explore the field of word embedding and thoroughly examine and contrast various word embedding algorithms. Words retain their semantic relationships and meaning when they are transformed into vectors using word …","url":["https://ijisrt.com/assets/upload/files/IJISRT23DEC1110.pdf"]}
{"year":"2024","title":"Performance of ChatGPT on American Board of Surgery In-Training Examination Preparation Questions","authors":["CG Tran, J Chang, SK Sherman, JP De Andrade - Journal of Surgical Research, 2024"],"snippet":"… The training dataset of ChatGPT 3.5, where the artificial intelligence (AI) “knowledge” is derived, is comprised of Common Crawl (a monthly updated web archive of data), books, journals, and Wikipedia and totals over 500 billion encoded “tokens.” Many …","url":["https://www.sciencedirect.com/science/article/pii/S0022480424002294"]}
{"year":"2024","title":"Perplexed by Perplexity: Perplexity-Based Data Pruning With Small Reference Models","authors":["Z Ankner, C Blakeney, K Sreenivasan, M Marion… - arXiv preprint arXiv …, 2024"],"snippet":"… Secondly, while previous work only investigates pruning on datasets composed of just one domain (CommonCrawl1), we consider two … dataset, with 81.31% of its data being derived from the CommonCrawl. We find that successful pruning …","url":["https://arxiv.org/pdf/2405.20541"]}
{"year":"2024","title":"Persistent Pre-Training Poisoning of LLMs","authors":["Y Zhang, J Rando, I Evtimov, J Chi, EM Smith, N Carlini… - arXiv preprint arXiv …, 2024"],"snippet":"Large language models are pre-trained on uncurated text datasets consisting of trillions of tokens scraped from the Web. Prior work has shown that: (1) web-scraped pre-training datasets can be practically poisoned by malicious actors; and (2) …","url":["https://arxiv.org/pdf/2410.13722"]}
{"year":"2024","title":"Personal Science Guide to AI","authors":["R Sprague - 2024"],"snippet":"Imagine you have access to a zillion documents, preferably curated in some way reassures you about their quality and consistency. Wikipedia, for example, or maybe Reddit and other posts that have been sufficiently up-voted. Maybe you also have a …","url":["https://ai.personalscience.com/PS-AI/Book/psai.pdf"]}
{"year":"2024","title":"Personality trait detection via transfer learning","authors":["B Alshouha, J Serrano-Guerrero, F Chiclana… - Comput Mater Continua …, 2024"],"snippet":"Personality recognition plays a pivotal role when developing user-centric solutions such as recommender systems or decision support systems across various domains, including education, e-commerce, or human resources. Traditional machine …","url":["https://cdn.techscience.cn/files/cmc/2024/TSP_CMC-78-2/TSP_CMC_46711/TSP_CMC_46711.pdf"]}
{"year":"2024","title":"Perspectives of Global and Hong Kong's Media on China's Belt and Road Initiative","authors":["LC Khoo, A Datta - arXiv preprint arXiv:2312.17013, 2023"],"snippet":"This study delves into the media analysis of China's ambitious Belt and Road Initiative (BRI), which, in a polarized world, and furthermore, owing to the very polarizing nature of the initiative itself, has received both strong criticisms and …","url":["https://arxiv.org/pdf/2312.17013"]}
{"year":"2024","title":"PharmGPT: Domain-Specific Large Language Models for Bio-Pharmaceutical and Chemistry","authors":["L Chen, W Wang, Z Bai, P Xu, Y Fang, J Fang, W Wu… - arXiv preprint arXiv …, 2024"],"snippet":"… reinforcing inherent biases present in the source materials (eg, CommonCrawl dumps) and those introduced through the filtering processes. Such … New tools were developed for extracting text from HTML in Common Crawl WARC files …","url":["https://arxiv.org/pdf/2406.18045"]}
{"year":"2024","title":"Phi-4 Technical Report","authors":["M Abdin, J Aneja, H Behl, S Bubeck, R Eldan… - arXiv preprint arXiv …, 2024"],"snippet":"We present phi-4, a 14-billion parameter language model developed with a training recipe that is centrally focused on data quality. Unlike most language models, where pre-training is based primarily on organic data sources such as web content or code …","url":["https://arxiv.org/pdf/2412.08905"]}
{"year":"2024","title":"Phish-Blitz: Advancing Phishing Detection with Comprehensive Webpage Resource Collection and Visual Integrity Preservation","authors":["D Hriday, A Kulkarni, T Das, V Balachandran - 2024"],"snippet":"… Researchers can use Common Crawl to obtain legitimate web content at scale, providing a rich resource for various analyses, including phishing detection. The breadth and depth of Common Crawl’s data make it an invaluable tool for web …","url":["https://irr.singaporetech.edu.sg/articles/conference_contribution/Phish-Blitz_Advancing_Phishing_Detection_with_Comprehensive_Webpage_Resource_Collection_and_Visual_Integrity_Preservation/28099931/1/files/51390860.pdf"]}
{"year":"2024","title":"PHISHING DETECTION SYSTEM THROUGH MACHINE LEARNING BASED ON URL","authors":["PU Chandra, TV Teja, VN Reddy, S Agarwalla"],"snippet":"… Legitimate site data is often gathered from Alexa's top-ranking website database or through common-crawl. Additionally, publicly available datasets like those from the UCI machine learning repository, containing over 11,000 records with 31 …","url":["https://www.irjmets.com/uploadedfiles/paper/issue_3_march_2024/49997/final/fin_irjmets1709462277.pdf"]}
{"year":"2024","title":"Phishing Detection Using Hybrid Algorithm Based on Clustering and Machine Learning","authors":["L Al-Shalabi, Y Hasan Jazyah - International Journal of Computing and Digital …, 2024"],"snippet":"Phishing is a prevalent and evolving cyber threat that continues to exploit human vulnerability to deceive individuals and organizations into revealing sensitive information. Phishing attacks encompass a range of tactics, from deceptive emails …","url":["https://journal.uob.edu.bh/bitstream/handle/123456789/5367/1570989057.pdf?sequence=1"]}
{"year":"2024","title":"Phishing URL Detection Using Machine Learning and Deep Learning","authors":["R Ferdaws, NE Majd - 2024 IEEE World AI IoT Congress (AIIoT), 2024"],"snippet":"In the modern digital world, phishing attacks have become a persistent threat, jeopardizing the security and privacy of individuals and organizations, demanding prompt action to avoid excessive costs imposed to individuals and businesses. The …","url":["https://ieeexplore.ieee.org/abstract/document/10579005/"]}
{"year":"2024","title":"Phishing Webpage Detection: Unveiling the Threat Landscape and Investigating Detection Techniques","authors":["A Kulkarni, V Balachandran, T Das - IEEE Communications Surveys & Tutorials, 2024"],"snippet":"… Common Crawl [53] is a nonprofit organization that maintains and provides access to a large-scale web crawling dataset. This dataset, known as the Common Crawl corpus, contains a comprehensive collection of web pages and their …","url":["https://ieeexplore.ieee.org/abstract/document/10633701/"]}
{"year":"2024","title":"PhoneLM: an Efficient and Capable Small Language Model Family through Principled Pre-training","authors":["R Yi, X Li, W Xie, Z Lu, C Wang, A Zhou, S Wang… - arXiv preprint arXiv …, 2024"],"snippet":"The interest in developing small language models (SLM) for on-device deployment is fast growing. However, the existing SLM design hardly considers the device hardware characteristics. Instead, this work presents a simple yet effective principle …","url":["https://arxiv.org/pdf/2411.05046"]}
{"year":"2024","title":"Physics-informed Machine Learning with Uncertainty Quantification","authors":["A Daw - 2024"],"snippet":"Physics Informed Machine Learning (PIML) has emerged as the forefront of research in scientific machine learning with the key motivation of systematically coupling machine learning (ML) methods with prior domain knowledge often available in the …","url":["https://vtechworks.lib.vt.edu/bitstreams/ee8eca5c-29ad-4698-a9ac-f68116d90fe2/download"]}
{"year":"2024","title":"PIE: A Personalized Information Embedded model for text-based depression detection","authors":["Y Wu, Z Liu, J Yuan, B Chen, H Cai, L Liu, Y Zhao… - Information Processing & …, 2024"],"snippet":"… It undergoes pre-training on 2.5TB of filtered CommonCrawl data, encompassing 100 languages. By acquiring a comprehensive understanding of these 100 languages, the model can extract valuable features for downstream tasks. …","url":["https://www.sciencedirect.com/science/article/pii/S0306457324001894"]}
{"year":"2024","title":"PinLID: a dataset for Pinglish language identiftcation based on code-mixing sentence on unstructured resources","authors":["A Ghafouri, H Naderi, M Firouzmandi - Language Resources and Evaluation, 2024"],"snippet":"Abstract Language identification is a major task in natural language processing. It serves as an initial and effective stage in critical tasks such as information extraction, sentiment analysis, and question answering. Most research on language …","url":["https://link.springer.com/article/10.1007/s10579-024-09783-3"]}
{"year":"2024","title":"Pipeline Analysis for Developing Instruct LLMs in Low-Resource Languages: A Case Study on Basque","authors":["A Corral, I Sarasua, X Saralegi - arXiv preprint arXiv:2412.13922, 2024"],"snippet":"Large language models (LLMs) are typically optimized for resource-rich languages like English, exacerbating the gap between high-resource and underrepresented languages. This work presents a detailed analysis of strategies for developing a …","url":["https://arxiv.org/pdf/2412.13922"]}
{"year":"2024","title":"PIRB: A Comprehensive Benchmark of Polish Dense and Hybrid Text Retrieval Methods","authors":["S Dadas, M Perełkiewicz, R Poświata - arXiv preprint arXiv:2402.13350, 2024"],"snippet":"We present Polish Information Retrieval Benchmark (PIRB), a comprehensive evaluation framework encompassing 41 text information retrieval tasks for Polish. The benchmark incorporates existing datasets as well as 10 new, previously …","url":["https://arxiv.org/pdf/2402.13350"]}
{"year":"2024","title":"Pitfalls of Conversational LLMs on News Debiasing","authors":["IB Schlicht, D Altiok, M Taouk, L Flek - arXiv preprint arXiv:2404.06488, 2024"],"snippet":"This paper addresses debiasing in news editing and evaluates the effectiveness of conversational Large Language Models in this task. We designed an evaluation checklist tailored to news editors' perspectives, obtained generated texts from three …","url":["https://arxiv.org/pdf/2404.06488"]}
{"year":"2024","title":"PLAID SHIRTTT for Large-Scale Streaming Dense Retrieval","authors":["D Lawrie, E Kayi, E Yang, J Mayfield, DW Oard - arXiv preprint arXiv:2405.00975, 2024"],"snippet":"… With ten million documents from the news subset of CommonCrawl, NeuCLIR is presently the largest available test collection for MLIR; It is tiny though relative to ClueWeb, and thus has relatively small shards. The NeuCLIR MLIR task is to …","url":["https://arxiv.org/pdf/2405.00975"]}
{"year":"2024","title":"PLaMo-100B: A Ground-Up Language Model Designed for Japanese Proficiency","authors":["K Abe, K Chubachi, Y Fujita, Y Hirokawa, K Imajo… - arXiv preprint arXiv …, 2024"],"snippet":"… Initially, we constructed the Japanese corpus from CommonCrawl using CCNet. However, for the latter portion consisting of 0.5 trillion tokens, we undertook a comprehensive preprocessing effort from the ground up, using 20 data dumps …","url":["https://arxiv.org/pdf/2410.07563"]}
{"year":"2024","title":"Please be polite to your peers: a multi-task model for assessing the tone and objectivity of critiques of peer review comments","authors":["PK Bharti, M Agarwal, A Ekbal - Scientometrics, 2024"],"snippet":"The peer-review process plays a pivotal role in maintaining the quality and credibility of scientific publications. However, in recent times, there has been an increase in unhelpful and overly critical reviews, which can be detrimental to the …","url":["https://link.springer.com/article/10.1007/s11192-024-04938-z"]}
{"year":"2024","title":"PoisonedParrot: Subtle Data Poisoning Attacks to Elicit Copyright-Infringing Content from Large Language Models","authors":["MA Panaitescu-Liess, P Pathmanathan, Y Kaya, Z Che… - Neurips Safe Generative AI …"],"snippet":"… Large language models (LLMs) are typically pre-trained on massive corpora of textual data collected from the web, such as the Common Crawl… A critical analysis of the largest source for generative ai training data: Common crawl. In Proceedings …","url":["https://openreview.net/pdf?id=ZXgvPANlwe"]}
{"year":"2024","title":"Policy analysis combining artificial intelligence and text mining technology in the perspective of educational informatization","authors":["H Kuang, P Tian, X Liang - Humanities and Social Sciences Communications, 2024"],"snippet":"… The dataset used in this study is Common Crawl, an open web archive project that regularly crawls billions of web pages. Although Common Crawl itself is not specifically tailored for educational policy texts, its vast dataset covers a wide range …","url":["https://www.nature.com/articles/s41599-024-04076-0"]}
{"year":"2024","title":"Politehnica University of Bucharest, Splaiul Independentei Nr. 313, Cector 6, Bucharest, Romania radu. stefan@ live. de, radu. stefan3@ student. upt. ro","authors":["R Stefan, G Carutasu, M Mocan - The 17th International Conference Interdisciplinarity in …"],"snippet":"This paper aims to investigate the ethical considerations surrounding the implementation and usage of large language models (LLMs). LLMs have shown tremendous advance in natural language processing and have the potential to …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=u9b9EAAAQBAJ&oi=fnd&pg=PA131&dq=commoncrawl&ots=-M9_Zu0oSH&sig=tr2it1m_D-HFpU5IrX5YZn7SwEY"]}
{"year":"2024","title":"Political biases and inconsistencies in bilingual GPT models—the cases of the US and China","authors":["D Zhou, Y Zhang - Scientific Reports, 2024"],"snippet":"… (Chinese is among the largest languages in Common Crawl, accounting for 5% of the data) 45 . The specific sources of the Chinese text in Common Crawl remain unclear, but recent research 46 examining the web domains of Common Crawl …","url":["https://www.nature.com/articles/s41598-024-76395-w"]}
{"year":"2024","title":"Political Disaffection and the Decline of the Centre: Quantitative Text Analysis Approaches","authors":["C Moez - 2024"],"snippet":"Over many decades of research on anti-establishment politicians, scholars have made claims about how they speak. These descriptions are typically critical in nature: populists present the world in terms of moral binaries; they invoke negative emotions …","url":["https://tspace.library.utoronto.ca/bitstream/1807/141113/3/Moez_Catherine_202411_PhD_thesis.pdf"]}
{"year":"2024","title":"PoliticPA 2024: Author Profiling Gender and Political Ideology of Politicians in Panama","authors":["D Cedeno-Moreno, R Pan, M Vargas-Lombardo - Technologies and Innovation"],"snippet":"… It is a multilingual model trained on a large corpus of 2.5 terabytes of CommonCrawl data, including texts in 100 different languages. It uses the Masked Language Modeling (MLM) method for pre-training, which allows it to learn …","url":["https://link.springer.com/content/pdf/10.1007/978-3-031-75702-0.pdf#page=102"]}
{"year":"2024","title":"PoliticPA 2024: Author Profiling Gender and Political Ideology of Politicians","authors":["D Cedeño-Moreno¹, R Pan, M Vargas-Lombardo¹ - Technologies and Innovation: 10th …"],"snippet":"Author profiling in computational linguistics and Natural Language Processing identifies traits such as age, gender, education level, and personality from written text, with applications in marketing, cyber-security, forensics, and academia …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=YGIsEQAAQBAJ&oi=fnd&pg=PA93&dq=commoncrawl&ots=qNrjoOq2wX&sig=Rg3_vUgsl0UTX9YhFrJIVrC88Vw"]}
{"year":"2024","title":"Polynomial Composition Activations: Unleashing the Dynamics of Large Language Models","authors":["Z Zhuo, Y Wang, Y Zeng, X Li, X Zhou, J Ma - arXiv preprint arXiv:2411.03884, 2024"],"snippet":"Transformers have found extensive applications across various domains due to the powerful fitting capabilities. This success can be partially attributed to their inherent nonlinearity. Thus, in addition to the ReLU function employed in the original …","url":["https://arxiv.org/pdf/2411.03884"]}
{"year":"2024","title":"Polysemy through the lens of psycholinguistic variables: a dataset and an evaluation of static and contextualized language models","authors":["A Bruera, F Zamani, M Poesio - Proceedings of the 13th Joint Conference on Lexical …, 2024"],"snippet":"… This version was trained on a combination of Common Crawl and Wikipedia and has 300dimensional vectors. We extract word vectors for all nouns and verbs and create a phrase-specific representation for each noun as described for countpmi. …","url":["https://aclanthology.org/2024.starsem-1.3.pdf"]}
{"year":"2024","title":"Position: Data Authenticity, Consent, & Provenance for AI are all broken: what will it take to fix them?","authors":["S Longpre, R Mahari, N Obeng-Marnu, W Brannon…"],"snippet":"… Common Crawl. For pretraining text data, models routinely rely on the Common Crawl.For instance, sixty percent of GPT-3 training data is … Common Crawl is accurate with wide coverage, but not detailed. Hugging Face can be inaccurate with …","url":["https://openreview.net/pdf?id=3hSTecKy1b"]}
{"year":"2024","title":"Position: Mission Critical–Satellite Data is a Distinct Modality in Machine Learning","authors":["E Rolf, K Klemmer, C Robinson, H Kerner - Forty-first International Conference on Machine …"],"snippet":"Satellite data has the potential to inspire a seismic shift for machine learning---one in which we rethink existing practices designed for traditional data modalities. As machine learning for satellite data (SatML) gains traction for its real-world impact …","url":["https://openreview.net/pdf?id=PQ0ERKKYJu"]}
{"year":"2024","title":"Position: Near to Mid-term Risks and Opportunities of Open-Source Generative AI","authors":["F Eiras, A Petrov, B Vidgen, CS de Witt, F Pizzati… - Forty-first International Conference …"],"snippet":"In the next few years, applications of Generative AI are expected to revolutionize a number of different areas, ranging from science & medicine to education. The potential for these seismic changes has triggered a lively debate about potential …","url":["https://openreview.net/pdf?id=8q4EPdjTLE"]}
{"year":"2024","title":"Position: Will we run out of data? Limits of LLM scaling based on human-generated data","authors":["P Villalobos, A Ho, J Sevilla, T Besiroglu, L Heim… - Forty-first International Conference …"],"snippet":"… Assuming that Common Crawl is a representative sample of the indexed web,11 we can use it to estimate the average amount of plain text bytes per web page. This number has increased over time, from around 6100 bytes in 2013 to about 8200 …","url":["https://openreview.net/pdf?id=ViZcgDQjyG"]}
{"year":"2024","title":"Post-processing Techniques for Word Embedding","authors":["ZM Albujasim - 2024"],"snippet":"Word embedding has been a significant breakthrough in natural language processing (NLP). Although word representation has improved remarkably and resulted in better performance in downstream NLP applications, interpretability of …","url":["https://repository.library.carleton.ca/downloads/g445cf462"]}
{"year":"2024","title":"Posthumanist AI","authors":["G SARAH"],"snippet":"… In their now canonical paper on “Stochastic Parrots”, Bender, Gebru, McMillan-Major, and Mitchell note that \"it is easy to imagine that very large datasets, such as Common Crawl “…petabytes of data collected over 8 years of web crawling” a …","url":["https://generativeaiandhci.github.io/papers/2024/genaichi2024_32.pdf"]}
{"year":"2024","title":"Practical Unlearning for Large Language Models","authors":["C Gao, L Wang, C Weng, X Wang, Q Zhu - arXiv preprint arXiv:2407.10223, 2024"],"snippet":"While LLMs have demonstrated impressive performance across various domains and tasks, their security issues have become increasingly severe. Machine unlearning (MU) has emerged as a promising solution to address these issues by …","url":["https://arxiv.org/pdf/2407.10223"]}
{"year":"2024","title":"Pralekha: An Indic Document Alignment Evaluation Benchmark","authors":["S Suryanarayanan, H Song, MSUR Khan… - arXiv preprint arXiv …, 2024"],"snippet":"… 2020), which employs language identification and similarity metrics to detect document pairs within Common Crawl. Subsequent research has incorporated advanced multilingual embeddings and transformer-based approaches (Conneau et …","url":["https://arxiv.org/pdf/2411.19096"]}
{"year":"2024","title":"Pre-Trained Acoustic-and-Textual Modeling for End-To-End Speech-To-Text Translation","authors":["W Zhang, H Zhang, C Liu, Z Ye, X Zhou, C Lin, L Dai - ICASSP 2024-2024 IEEE …, 2024"],"snippet":"… The monolingual data are mainly from News Commentary, News crawl and Common Crawl. We apply language identification [23] to retain sentences predicted as desired language, remove sentences longer than 250 tokens and with a source/target …","url":["https://ieeexplore.ieee.org/abstract/document/10446635/"]}
{"year":"2024","title":"Pre-trained language models in medicine: A survey","authors":["X Luo, Z Deng, B Yang, MY Luo - Artificial Intelligence in Medicine, 2024"],"snippet":"With the rapid progress in Natural Language Processing (NLP), Pre-trained Language Models (PLM) such as BERT, BioBERT, and ChatGPT have shown great potential in various medical NLP tasks. This paper surveys the cutting-edge …","url":["https://www.sciencedirect.com/science/article/pii/S0933365724001465"]}
{"year":"2024","title":"Pre-trained Large Language Models for Financial Sentiment Analysis","authors":["W Luo, D Gong - arXiv preprint arXiv:2401.05215, 2024"],"snippet":"Financial sentiment analysis refers to classifying financial text contents into sentiment categories (eg positive, negative, and neutral). In this paper, we focus on the classification of financial news title, which is a challenging task due to a lack of …","url":["https://arxiv.org/pdf/2401.05215"]}
{"year":"2024","title":"Pre-training a Transformer-Based Generative Model Using a Small Sepedi Dataset","authors":["SP Ramalepe, TI Modipa, MH Davel - Southern African Conference for Artificial …, 2024"],"snippet":"… The Leipzig dataset [8] consists of newspaper texts and texts randomly collected from the web while Web crawl dataset [5, 33] consists of general data extracted from Common Crawl for various languages including Sepedi. …","url":["https://link.springer.com/chapter/10.1007/978-3-031-78255-8_19"]}
{"year":"2024","title":"Pre-training a Transformer-Based Generative Model Using a Small Sepedi","authors":["SP Ramalepe, TI Modipa - Artificial Intelligence Research: 5th Southern African …"],"snippet":"… The Leipzig dataset [8] consists of newspaper texts and texts randomly collected from the web while Web crawl dataset [5, 33] consists of general data extracted from Common Crawl for various languages including Sepedi. …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=LsY0EQAAQBAJ&oi=fnd&pg=PA319&dq=commoncrawl&ots=yOp2xVEVT5&sig=fAqkbsVGe9oQNjAi1eeRifF1ZJg"]}
{"year":"2024","title":"Pre-training Small Base LMs with Fewer Tokens","authors":["S Sanyal, S Sanghavi, AG Dimakis - arXiv preprint arXiv:2404.08634, 2024"],"snippet":"We study the effectiveness of a simple approach to develop a small base language model (LM) starting from an existing large base LM: first inherit a few transformer blocks from the larger LM, and then train this smaller model on a very small subset (0.1\\%) …","url":["https://arxiv.org/pdf/2404.08634"]}
{"year":"2024","title":"Precarity and Solidarity: Preliminary results on a study of queer and disabled fiction writers' experiences with generative AI","authors":["CE Lamb, DG Brown, MR Grossman - arXiv preprint arXiv:2412.04575, 2024"],"snippet":"We have undertaken a mixed-methods study of fiction writers' experiences and attitudes with generative AI, primarily focused on the experiences of queer and disabled writers. We find that queer and disabled writers are markedly more …","url":["https://arxiv.org/pdf/2412.04575"]}
{"year":"2024","title":"Predicting fraud in MD&A sections using deep learning","authors":["S Velloor Sivasubramanian, D Skillicorn - Journal of Business Analytics, 2024"],"snippet":"Conventional data analytic techniques have been successfully applied to detecting fraud in the Management’s Discussion and Analysis sections of company filings mandated by the SEC. Here, we investigate whether fraud detection can be …","url":["https://www.tandfonline.com/doi/abs/10.1080/2573234X.2024.2342773"]}
{"year":"2024","title":"Predicting semantic category of answers for question answering systems using transformers: a transfer learning approach","authors":["S CM, J Prakash, VS Alaparthi - Multimedia Tools and Applications, 2024"],"snippet":"… The model uses a data set of web extracted text that has been created with the help of the Common Crawl and preprocessed to remove short, duplicate, and non-English content, resulting in a corpus called \"Colossal Clean Crawled Corpus\" (C4). An …","url":["https://link.springer.com/article/10.1007/s11042-024-18609-x"]}
{"year":"2024","title":"PREDICTING TARGETS WITH SEC 8-K FILINGS","authors":["LOS NEW"],"snippet":"There are large financial benefits in predicting acquisitions, but so far no adequate method has been found to that end. In this research textual data from 8-K Filings is used to improve the predictive performance of three classification models. 8-Ks are …","url":["http://arno.uvt.nl/show.cgi?fid=171249"]}
{"year":"2024","title":"Predicting the Valence Rating of Russian Words Using Various Pre-trained Word Embeddings","authors":["VV Bochkarev, AV Savinkov, AV Shevlyakova - International Conference on Speech …, 2025"],"snippet":"In this work, we conducted a comparative testing of 20 sets of pre-trained vectors to computationally estimate valence ratings of words in the Russian language. The word valence was estimated using neural network predictors. A vector representing …","url":["https://link.springer.com/chapter/10.1007/978-3-031-78014-1_26"]}
{"year":"2024","title":"Prediction of Author's Profile basing on Fine-Tuning BERT model","authors":["B Bsir, N Khoufi, M Zrigui - Informatica, 2024"],"snippet":"… Indeed, XLMRoBERTa is the multilingual variant of RoBERTa trained with a multilingual MLM on one hundred languages, with more than two terabytes of filtered Common Crawl data.XLM-RoBERTa showed its superiority over BERT by its …","url":["https://informatica.si/index.php/informatica/article/download/4839/2718"]}
{"year":"2024","title":"Preemptive Answer\" Attacks\" on Chain-of-Thought Reasoning","authors":["R Xu, Z Qi, W Xu - arXiv preprint arXiv:2405.20902, 2024"],"snippet":"Large language models (LLMs) showcase impressive reasoning capabilities when coupled with Chain-of-Thought (CoT) prompting. However, the robustness of this approach warrants further investigation. In this paper, we introduce a novel scenario …","url":["https://arxiv.org/pdf/2405.20902"]}
{"year":"2024","title":"Preprocessing Techniques for Clustering Arabic Text: Challenges and Future Directions.","authors":["T Almutairi, S Saifuddin, R Alotaibi, S Sarhan, S Nassif - International Journal of …, 2024"],"snippet":"Arabic is a complex language for text analysis because of its orthographic features, rich synonyms, and semantic style. Thus, Arabic text must be prepared more carefully in the preprocessing stage for the analyzer to improve the quality of the …","url":["https://search.ebscohost.com/login.aspx?direct=true&profile=ehost&scope=site&authtype=crawler&jrnl=2158107X&AN=179442221&h=qvsPmn448gO8YbEqr4mLtelStB70sRWop2E%2BghiU300mGifmDLa%2Fy25xsTCXXOtqKpuW7NTWO8ECJUMOK54Qnw%3D%3D&crl=c"]}
{"year":"2024","title":"Preserving Privacy in Large Language Models: A Survey on Current Threats and Solutions","authors":["M Miranda, ES Ruzzetti, A Santilli, FM Zanzotto… - arXiv preprint arXiv …, 2024"],"snippet":"… In particular, in their experiments the language model generation is conditioned to some prompts that the attacker predefined: to maximize the probability of success of the attack, they choose prompts that are likely to be in the training data, like …","url":["https://arxiv.org/pdf/2408.05212"]}
{"year":"2024","title":"Pretraining and Updating Language-and Domain-specific Large Language Model: A Case Study in Japanese Business Domain","authors":["K Takahashi, T Omi, K Arima, T Ishigaki - arXiv preprint arXiv:2404.08262, 2024"],"snippet":"… , mC4, and Common Crawl. These datasets contribute to general knowledge, which is essential for diverse natural language processing tasks. … the proportion of clean domain-specific data, we aim to mitigate the impact of noisy data sources such …","url":["https://arxiv.org/pdf/2404.08262"]}
{"year":"2024","title":"Pretraining Data and Tokenizer for Indic LLM","authors":["R Kumar, S Kakde, D Rajput, D Ibrahim, R Nahata… - arXiv preprint arXiv …, 2024"],"snippet":"… Additionally, we perform deduplication on Common Crawl data to address the redundancy present in 70% of the crawled web pages. This study focuses on developing high-quality data, optimizing tokenization for our multilingual dataset for …","url":["https://arxiv.org/pdf/2407.12481"]}
{"year":"2024","title":"PRIVACY HARMS IN THE AI AGE","authors":["L WICKELL"],"snippet":"These problems run deeper than false accusations. Many AI models have trained on datasets that contain personal information, and every AI model is capable of regurgitating any data it has previously processed. In 2023, researchers …","url":["https://www.transparencycoalition.ai/s/PrivacyHarms-11-1.pdf"]}
{"year":"2024","title":"Privacy in Federated Learning","authors":["M Zhang - 2024"],"snippet":"The rise of Artificial Intelligence technology has raised concerns about the potential compromise of privacy due to the handling of personal data. Private AI prevents cybercrimes and falsehoods and protects human freedom and trust. While …","url":["https://search.proquest.com/openview/91d5aaac908f52e90696852232eb4acd/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
{"year":"2024","title":"Privacy issues in Large Language Models: A survey","authors":["H Kibriya, WZ Khan, A Siddiqa, MK Khan - Computers and Electrical Engineering, 2024"],"snippet":"In the fast-paced world of modern technology, the development of Large Language Models (LLMs) has increased drastically. However, this growth has also increased privacy concerns associated with these models. This paper investigates privacy …","url":["https://www.sciencedirect.com/science/article/pii/S0045790624006256"]}
{"year":"2024","title":"Probabilistic Language-Image Pre-Training","authors":["S Chun, W Kim, S Park, S Yun - arXiv preprint arXiv:2410.18857, 2024"],"snippet":"Vision-language models (VLMs) embed aligned image-text pairs into a joint space but often rely on deterministic embeddings, assuming a one-to-one correspondence between images and texts. This oversimplifies real-world relationships, which are …","url":["https://arxiv.org/pdf/2410.18857"]}
{"year":"2024","title":"Probability-Aware Word-Confusion-Network-To-Text Alignment Approach for Intent Classification","authors":["E Villatoro-Tello, S Madikeri, B Sharma, D Khalil… - ICASSP 2024-2024 IEEE …, 2024"],"snippet":"… The Language Model (LM) was trained with 34M utterances from publicly available English datasets including People’s Speech, Fisher, Switchboard, AMI, Wikitext103, and subsets of Common Crawl and Reddit datasets. The model was …","url":["https://ieeexplore.ieee.org/abstract/document/10445934/"]}
{"year":"2024","title":"Probing and enhancing the reliance of Transformer models on poetic information","authors":["A Abdibayev - 2023"],"snippet":"Transformer models have achieved remarkable success in the widest variety of domains, spanning not just a multitude of tasks within natural language processing, but also those in computer vision, speech, and reinforcement learning. The key to …","url":["https://digitalcommons.dartmouth.edu/cgi/viewcontent.cgi?article=1228&context=dissertations"]}
{"year":"2024","title":"Probing Critical Learning Dynamics of PLMs for Hate Speech Detection","authors":["S Masud, MA Khan, V Goyal, MS Akhtar, T Chakraborty - arXiv preprint arXiv …, 2024"],"snippet":"… Each variant is trained on a training corpus from Wikipedia, and Common-Crawl is curated and updated before the date associated with … that are pretrained on regular and latest Internet snapshots obtained via Common Crawl and Wikipedia …","url":["https://arxiv.org/html/2402.02144v1"]}
{"year":"2024","title":"Probing Large Language Models for Scalar Adjective Lexical Semantics and Scalar Diversity Pragmatics","authors":["F Lin, D Altshuler, JB Pierrehumbert - arXiv preprint arXiv:2404.03301, 2024"],"snippet":"… 2018) trained on 600B Common Crawl data as a baseline. For the baseline, we add the representations of strongest and weakest adjectives on s as ⃗s, then also rank cos(⃗a, ⃗s) for each a to calculate MRR. Here, we only report the results for the …","url":["https://arxiv.org/html/2404.03301v1"]}
{"year":"2024","title":"Probing the contents of semantic representations from text, behavior, and brain data using the psychNorms metabase","authors":["Z Hussain, R Mata, BR Newell, DU Wulff - arXiv preprint arXiv:2412.04936, 2024"],"snippet":"… Despite the diversity within data type and some algorithmic commonalities between types (eg, fastText CommonCrawl, SGSoftMax Input SWOW), we observe very clear clustering by data type (Figure 3) and only mild clustering based on the …","url":["https://arxiv.org/pdf/2412.04936"]}
{"year":"2024","title":"PRODIS-a speech database and a phoneme-based language model for the study of predictability effects in Polish","authors":["Z Malisz, J Foremski, M Kul - arXiv preprint arXiv:2404.10112, 2024"],"snippet":"We present a speech database and a phoneme-level language model of Polish. The database and model are designed for the analysis of prosodic and discourse factors and their impact on acoustic parameters in interaction with predictability effects. The …","url":["https://arxiv.org/pdf/2404.10112"]}
{"year":"2024","title":"Programming Every Example: Lifting Pre-training Data Quality like Experts at Scale","authors":["F Zhou, Z Wang, Q Liu, J Li, P Liu - arXiv preprint arXiv:2409.17115, 2024"],"snippet":"Large language model pre-training has traditionally relied on human experts to craft heuristics for improving the corpora quality, resulting in numerous rules developed to date. However, these rules lack the flexibility to address the unique characteristics …","url":["https://arxiv.org/pdf/2409.17115"]}
{"year":"2024","title":"Progress Report: Towards European LLMs","authors":["M Ali, M Fromm, K Thellmann, J Ebert, AA Weber… - arXiv preprint arXiv …, 2024"],"snippet":"… Dumps In this section, we outline the Common Crawl data utilized in our LLM training, detailing the cutoff dates and the data collection period. The dumps span multiple years, with varying distributions of weeks per year (cf. Table 7), which is …","url":["https://arxiv.org/pdf/2410.03730"]}
{"year":"2024","title":"Prometheus' Digital Fire: The Civic Responsibilities of Artificial Intelligence","authors":["JM Garon - 2024"],"snippet":"[Prometheus], the noble son of Iapetus outwitted [Zeus] and stole the far-seen gleam of unwearying fire in a hollow fennel stalk. And Zeus who thunders on high was stung in spirit, and his dear heart was angered when he saw amongst men the far-seen …","url":["https://kb.osu.edu/bitstreams/b856efe9-db61-4bd8-876c-e1402662d292/download"]}
{"year":"2024","title":"Prompt Optimization with EASE? Efficient Ordering-aware Automated Selection of Exemplars","authors":["Z Wu, X Lin, Z Dai, W Hu, Y Shu, SK Ng, P Jaillet… - arXiv preprint arXiv …, 2024"],"snippet":"… [2], it is highly likely that GPT-3 has been trained on common benchmark datasets potentially contained in Common Crawl due to data contamination. Hence, further providing high-quality in-context exemplars could hardly improve the performance of …","url":["https://arxiv.org/pdf/2405.16122"]}
{"year":"2024","title":"Prompting Change: ChatGPT's Impact on Digital Humanities Pedagogy–A Case Study in Art History","authors":["Q Guo - International Journal of Humanities and Arts …, 2024"],"snippet":"This article explores the transformative impact of ChatGPT, a Generative Pre-trained Transformers model, on humanities methodologies and its integration into a digital humanities (DH) course. The advent of ChatGPT enhances the capacity of people …","url":["https://www.euppublishing.com/doi/abs/10.3366/ijhac.2024.0321"]}
{"year":"2024","title":"Prompting Encoder Models for Zero-Shot Classification: A Cross-Domain Study in Italian","authors":["S Auriemma, M Miliani, M Madeddu, A Bondielli… - arXiv preprint arXiv …, 2024"],"snippet":"… We may suppose that this is because UmBERTo was trained on Common-Crawl, which also contains legal and administrative texts in its Italian section. Very high results are obtained by UmBERTo for PER entities, reaching 0.83 in our zero-shot …","url":["https://arxiv.org/pdf/2407.20654"]}
{"year":"2024","title":"Prospect of large language models and natural language processing for lung cancer diagnosis: A systematic review","authors":["A Garg, S Gupta, S Vats, P Handa, N Goel - Expert Systems"],"snippet":"Lung cancer, a leading cause of global mortality, demands a combat for its effective prevention, early diagnosis, and advanced treatment methods. Traditional diagnostic methods face limitations in accuracy and efficiency, necessitating …","url":["https://onlinelibrary.wiley.com/doi/abs/10.1111/exsy.13697"]}
{"year":"2024","title":"Protein-Protein Interaction Prediction","authors":["SM Hosseini - 2024"],"snippet":"Proteins are essential components of cellular processes, playing pivotal roles in various biological functions. Their interactions with other proteins are fundamental for maintaining cellular functionality, a phenomenon referred to as protein-protein …","url":["https://ir.lib.uwo.ca/cgi/viewcontent.cgi?article=13195&context=etd"]}
{"year":"2024","title":"PROXYQA: An Alternative Framework for Evaluating Long-Form Text Generation with Large Language Models","authors":["H Tan, Z Guo, Z Shi, L Xu, Z Liu, X Li, Y Wang, L Shang… - arXiv preprint arXiv …, 2024"],"snippet":"… Nevertheless, scaling the context window during the pretraining phase remains a daunting task as the computational demands surge quadratically with the length of the attention span, and a majority of texts within standard corpora, like Common …","url":["https://arxiv.org/pdf/2401.15042"]}
{"year":"2024","title":"Pruning Large Language Models with Semi-Structural Adaptive Sparse Training","authors":["W Huang, G Jian, Y Hu, J Zhu, J Chen - arXiv preprint arXiv:2407.20584, 2024"],"snippet":"Transformer-based Large Language Models (LLMs) have demonstrated remarkable success across various challenging tasks. However, the deployment of LLMs is hindered by their substantial parameter count and memory consumption. Recently …","url":["https://arxiv.org/pdf/2407.20584"]}
{"year":"2024","title":"PSILENCE: A Pseudonymization Tool for International Law","authors":["LA Cabrera-Diego, A Gheewala - Proceedings of the Workshop on Computational …, 2024"],"snippet":"Since the announcement of the GDPR, the pseudonymization of legal documents has become a high-priority task in many legal organizations. This means that for making public a document, it is necessary to redact the identity of certain entities …","url":["https://aclanthology.org/2024.caldpseudo-1.4.pdf"]}
{"year":"2024","title":"PSQE: Personalized Semantic Query Expansion for user-centric query disambiguation","authors":["O Baumann, M Schoenfeld - 2024"],"snippet":"… Furthermore, they enable explainable intelligent systems, in that the results of querying the embedding for similar terms relate directly to the training set, rather than webscale collections such as Common Crawl. To our knowledge, our work is …","url":["https://www.researchsquare.com/article/rs-4178030/latest.pdf"]}
{"year":"2024","title":"PSQS: Parallel Semantic Querying Service for Self-describing File Formats","authors":["C Niu, W Zhang, S Byna, Y Chen - 2023 IEEE International Conference on Big Data …, 2023"],"snippet":"… Typically, theseword representations are learned from a training dataset suchas the Common Crawl web corpus (840 billion tokens, 2.2million words) or Wikipedia 2014 (6 billion tokens, 400,000words). However, this assumption does not always …","url":["https://www.computer.org/csdl/proceedings-article/bigdata/2023/10386205/1TUOFedcdIQ"]}
{"year":"2024","title":"Psychology and Behaviour","authors":["S Nordhoff, M Hagenzieker"],"snippet":"… We used a large database of web text titled Common Crawl suitable for our purpose containing 300-dimensional word vectors for 600.000 words to identify 15 additional seed terms per subcategory (Pennington, Socher, &, Manning, nd). To …","url":["https://www.researchgate.net/profile/Sina-Nordhoff/publication/385716726_I_will_raise_my_hand_and_say_'I_over-trust_Autopilot'_I_use_it_too_liberally_-_Drivers'_reflections_on_their_use_of_partial_driving_automation_trust_and_perceived_safety/links/6732508669c07a411444a9cb/I-will-raise-my-hand-and-say-I-over-trust-Autopilot-I-use-it-too-liberally-Drivers-reflections-on-their-use-of-partial-driving-automation-trust-and-perceived-safety.pdf"]}
{"year":"2024","title":"Public Domain 12M: A Highly Aesthetic Image-Text Dataset with Novel Governance Mechanisms","authors":["J Meyer, N Padgett, C Miller, L Exline - arXiv preprint arXiv:2410.23144, 2024"],"snippet":"We present Public Domain 12M (PD12M), a dataset of 12.4 million high-quality public domain and CC0-licensed images with synthetic captions, designed for training text-to-image models. PD12M is the largest public domain image-text …","url":["https://arxiv.org/pdf/2410.23144"]}
{"year":"2024","title":"Public perception of the Chinese president's visit to Saudi Arabia and the China–Arab Summit: sentiment analysis of Arabic tweets","authors":["AAM Hassan - Social Network Analysis and Mining, 2024"],"snippet":"In recent years, China and Saudi Arabia have had frequent exchanges in the political and economic fields, and public opinion evaluation is an essential aspect of evaluating the two countries’ current relations. This paper analyzes tweets in Arabic …","url":["https://link.springer.com/article/10.1007/s13278-023-01174-w"]}
{"year":"2024","title":"PUBLIC-PRIVATE PARTNERSHIPS IN HEALTH SECTOR INNOVATION: LESSONS FROM AROUND THE WORLD","authors":["CC Ebulue, OR Ebulue, CS Ekesiobi - International Medical Science Research …, 2024"],"snippet":"Public-Private Partnerships (PPPs) have emerged as a crucial mechanism for fostering innovation in the health sector globally. This review encapsulates the lessons learned from diverse PPP models worldwide, highlighting their significance …","url":["https://www.fepbl.com/index.php/imsrj/article/view/1051/1274"]}
{"year":"2024","title":"PyLoomer-The Automated Weaving of Python Text","authors":["A Sahani, RB Trivedi, T Singh, SR Goyal - 2024 2nd International Conference on …, 2024"],"snippet":"The introduction of attention mechanisms has evolved NLP methodologies, giving rise to Large Language Models (LLMs) that excel in various sequence-to-sequence tasks like translation, question-answering, summarization, intent, and entity …","url":["https://ieeexplore.ieee.org/abstract/document/10532945/"]}
{"year":"2024","title":"Q-GaLore: Quantized GaLore with INT4 Projection and Layer-Adaptive Low-Rank Gradients","authors":["Z Zhang, A Jaiswal, L Yin, S Liu, J Zhao, Y Tian… - arXiv preprint arXiv …, 2024"],"snippet":"… The C4 dataset is a massive collection of Common Crawl’s web crawl corpus, meticulously filtered and cleaned to ensure highquality language modeling and training. It is widely used for pre-training large language models due to its diverse …","url":["https://arxiv.org/pdf/2407.08296"]}
{"year":"2024","title":"QARR-FSQA: Question-Answer Replacement and Removal Pretraining Framework for Few-Shot Question Answering","authors":["SW Tan, CP Lee, KM Lim, C Tee, A Alqahtani - IEEE Access, 2024"],"snippet":"In Natural Language Processing, creating training data for question answering (QA) systems typically requires significant effort and expertise. This challenge is amplified in few-shot scenarios where only a limited number of training samples are available …","url":["https://ieeexplore.ieee.org/iel8/6287639/6514899/10737355.pdf"]}
{"year":"2024","title":"Qilin-Med: Towards Advanced Chinese Medical Large Language Model","authors":["Q Ye, J Liu, D Chong, P Zhou, Y Hua, F Liu, M Cao…"],"snippet":"Integrating large language models (LLMs) into healthcare holds great potential but faces challenges. Pre-training LLMs from scratch for domains like medicine is resource-heavy and often unfeasible. On the other hand, sole reliance on …","url":["https://www.researchgate.net/profile/Meng_Cao31/publication/386599424_Qilin-Med_Towards_Advanced_Chinese_Medical_Large_Language_Model/links/67580a7098f61916184c803a/Qilin-Med-Towards-Advanced-Chinese-Medical-Large-Language-Model.pdf"]}
{"year":"2024","title":"Qtok: A Comprehensive Framework for Evaluating Multilingual Tokenizer Quality in Large Language Models","authors":["I Chelombitko, E Safronov, A Komissarov - arXiv preprint arXiv:2410.12989, 2024"],"snippet":"… On the flip side, this reveals issues with underrepresented languages, especially those outside of the most popular ones found in Common Crawl. It remains unclear where to source datasets for these languages, suggesting that we may need to …","url":["https://arxiv.org/pdf/2410.12989"]}
{"year":"2024","title":"Quality Does Matter: A Detailed Look at the Quality and Utility of Web-Mined Parallel Corpora","authors":["S Ranathunga, N de Silva, M Velayuthan, A Fernando… - arXiv preprint arXiv …, 2024"],"snippet":"… 2020) is a dataset created using 68 snapshots of CommonCrawl10. Document … of CommonCrawl. It contains around 4.5 billion parallel sentences across 576 language pairs. In building CCMatrix, it was assumed the aligned sentence could …","url":["https://arxiv.org/pdf/2402.07446"]}
{"year":"2024","title":"Quantifying Gender Bias in Arabic Pre-trained Language Models","authors":["W Alrajhi, H Al-Khalifa, AM Al-Salman - IEEE Access, 2024"],"snippet":"The current renaissance in the development of Arabic Pre-trained Language models (APLMs) has yielded significant advancement across many fields. Nevertheless, no study has explored the dimensions of gender bias in these models. It is argued that …","url":["https://ieeexplore.ieee.org/iel7/6287639/6514899/10537164.pdf"]}
{"year":"2024","title":"Quantifying Geospatial in the Common Crawl Corpus","authors":["I Ilyankou, M Wang, J Haworth, S Cavazzi - arXiv e-prints, 2024"],"snippet":"… Common Crawl corpus. However, the geospatial content within CC remains largely unexplored, impacting our understanding of LLMs' spatial reasoning. This paper investigates the prevalence of geospatial data in recent Common Crawl …","url":["https://ui.adsabs.harvard.edu/abs/2024arXiv240604952I/abstract"]}
{"year":"2024","title":"Quantifying semantic relatedness across base verbs and derivatives: English","authors":["S Kotowski, M Schäfer"],"snippet":"Most authors on derivational semantics agree that the meaning of complex words builds on components contributed by the base, components contributed by the word formation process, as well as contextual knowledge components. There is far less …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=2FMREQAAQBAJ&oi=fnd&pg=PA177&dq=commoncrawl&ots=7SANbmNBF-&sig=wYyosdRHtACTS64OFRq-8srldvY"]}
{"year":"2024","title":"Quantifying task-related gaze","authors":["K Walter, M Freeman, P Bex - Attention, Perception, & Psychophysics, 2024"],"snippet":"… For this study, we used the pretrained word vector Common Crawl (840B tokens, 2.2M vocab, cased, 300d vectors), which can be obtained at https://nlp.stanford.edu/projects/glove/. To utilize GloVe with the LabelMe images, we used it in conjunction with LASS …","url":["https://link.springer.com/article/10.3758/s13414-024-02883-w"]}
{"year":"2024","title":"Quantifying the Importance of Data Alignment in Downstream Model Performance","authors":["K Chawla, A Sahai, M DePavia, S Sundar, B Miranda - 2024"],"snippet":"Contrary to the conventional emphasis on dataset size, we explore the role of data alignment---an often overlooked aspect of data quality---in training capable Large Language Models (LLMs). To do so, we use the Task2Vec-based alignment …","url":["https://openreview.net/pdf?id=pXTDfeBIPj"]}
{"year":"2024","title":"Quantitative Analysis of the Relationship Between Optimal Learning Rate and Batch Size Scaling in Large Language Models","authors":["R Schneider, H Baumgartner, D Wohlgemuth"],"snippet":"… Publicly available large-scale text datasets were utilized, including Common Crawl, Wikipedia, and BooksCorpus, which provided diverse and extensive language data. These datasets were chosen for their rich linguistic content and their …","url":["https://osf.io/4f8hw/download"]}
{"year":"2024","title":"Query Obfuscation for Information Retrieval through Differential Privacy","authors":["G Faggioli, N Ferro"],"snippet":"Protecting the privacy of a user querying an Information Retrieval (IR) system is of utmost importance. The problem is exacerbated when the IR system is not cooperative in satisfying the user’s privacy requirements. To address this …","url":["https://www.dei.unipd.it/~ferro/papers/2024/ECIR2024-FF.pdf"]}
{"year":"2024","title":"Query of CC: Unearthing Large Scale Domain-Specific Knowledge from Public Corpora","authors":["Z Fei, Y Shao, L Li, Z Zeng, H Yan, X Qiu, D Lin - arXiv preprint arXiv:2401.14624, 2024"],"snippet":"… become increasingly rich, including the Pile, RedPajama, and Common Crawl. To ensure the diversity of data sources for retrieval, we constructed our retrieval corpus based on Common CrawlCommon Crawl is an open-source web crawler project …","url":["https://arxiv.org/pdf/2401.14624"]}
{"year":"2024","title":"Query Performance Prediction using Relevance Judgments Generated by Large Language Models","authors":["C Meng, N Arabzadeh, A Askari, M Aliannejadi… - arXiv preprint arXiv …, 2024"],"snippet":"Query performance prediction (QPP) aims to estimate the retrieval quality of a search system for a query without human relevance judgments. Previous QPP methods typically return a single scalar value and do not require the predicted …","url":["https://arxiv.org/html/2404.01012v1"]}
{"year":"2024","title":"Query Spelling Correction using Pre-trained Word Embeddings","authors":["G Lahmann, I Zelch"],"snippet":"… The GloVe word embeddings were trained on multiple dumps of Wikipedia, as well as on a Common Crawl corpus from 2014. Vector dimensions larger than 300 were empirically found to provide diminishing returns on semantic and syntactic …","url":["https://downloads.webis.de/theses/papers/lahmann_2024.pdf"]}
{"year":"2024","title":"QuRating: Selecting High-Quality Data for Training Language Models","authors":["A Wettig, A Gupta, S Malik, D Chen - arXiv preprint arXiv:2402.09739, 2024"],"snippet":"… We visualize the distributions for the cluster in CommonCrawl and C4 in Figure 7 in the appendix. They are similarly encouraging, eg, the clusters associated with cells, protein, gene and energy, climate, species are rated highly on required …","url":["https://arxiv.org/pdf/2402.09739"]}
{"year":"2024","title":"Qwen2. 5-Coder Technical Report","authors":["B Hui, J Yang, Z Cui, J Yang, D Liu, L Zhang, T Liu… - arXiv preprint arXiv …, 2024"],"snippet":"In this report, we introduce the Qwen2.5-Coder series, a significant upgrade from its predecessor, CodeQwen1.5. This series includes two models: Qwen2.5-Coder-1.5B and Qwen2.5-Coder-7B. As a code-specific model, Qwen2.5-Coder is built upon the …","url":["https://arxiv.org/pdf/2409.12186"]}
{"year":"2024","title":"Qwen2. 5-Math Technical Report: Toward Mathematical Expert Model via Self-Improvement","authors":["A Yang, B Zhang, B Hui, B Gao, B Yu, C Li, D Liu, J Tu… - arXiv preprint arXiv …, 2024"],"snippet":"In this report, we present a series of math-specific large language models: Qwen2.5-Math and Qwen2.5-Math-Instruct-1.5B/7B/72B. The core innovation of the Qwen2.5 series lies in integrating the philosophy of self-improvement throughout the entire pipeline …","url":["https://arxiv.org/pdf/2409.12122"]}
{"year":"2024","title":"R2GQA: Retriever-Reader-Generator Question Answering System to Support Students Understanding Legal Regulations in Higher Education","authors":["PTP Do, DND Cao, KQ Tran, K Van Nguyen - arXiv preprint arXiv:2409.02840, 2024"],"snippet":"In this article, we propose the R2GQA system, a Retriever-Reader-Generator Question Answering system, consisting of three main components: Document Retriever, Machine Reader, and Answer Generator. The Retriever module employs …","url":["https://arxiv.org/pdf/2409.02840"]}
{"year":"2024","title":"RAGViz: Diagnose and Visualize Retrieval-Augmented Generation","authors":["T Wang, J He, C Xiong - arXiv preprint arXiv:2411.01751, 2024"],"snippet":"Retrieval-augmented generation (RAG) combines knowledge from domain-specific sources into large language models to ground answer generation. Current RAG systems lack customizable visibility on the context documents and the model's …","url":["https://arxiv.org/pdf/2411.01751"]}
{"year":"2024","title":"RAID: A Shared Benchmark for Robust Evaluation of Machine-Generated Text Detectors","authors":["L Dugan, A Hwang, F Trhlik, JM Ludan, A Zhu, H Xu… - arXiv preprint arXiv …, 2024"],"snippet":"… The model was allegedly trained with a variety of data including the Common Crawl (fil- … Released on July 18th 2023, LLaMA 2 is the successor to the original LLaMA model which was trained on webpages from CommonCrawl, multilingual …","url":["https://arxiv.org/pdf/2405.07940"]}
{"year":"2024","title":"Ranking Generated Answers: On the Agreement of Retrieval Models with Humans on Consumer Health Questions","authors":["S Heineking, J Probst, D Steinbach, M Potthast… - arXiv preprint arXiv …, 2024"],"snippet":"… We therefore obtained only the original Web documents from CommonCrawl, discarded those containing fewer than 50 characters in the HTML body, and extracted plain text using the Resiliparse library.We were able to restore 6,692 Web …","url":["https://arxiv.org/pdf/2408.09831"]}
{"year":"2024","title":"Rapidly Developing High-quality Instruction Data and Evaluation Benchmark for Large Language Models with Minimal Human Effort: A Case Study on Japanese","authors":["Y Sun, Z Wan, N Ueda, S Yahata, F Cheng, C Chu… - arXiv preprint arXiv …, 2024"],"snippet":"The creation of instruction data and evaluation benchmarks for serving Large language models often involves enormous human annotation. This issue becomes particularly pronounced when rapidly developing such resources for a non-English …","url":["https://arxiv.org/pdf/2403.03690"]}
{"year":"2024","title":"Re-Mix: Optimizing Data Mixtures for Large Scale Imitation Learning","authors":["J Hejna, C Bhateja, Y Jian, K Pertsch, D Sadigh - arXiv preprint arXiv:2408.14037, 2024"],"snippet":"… Many breakthroughs in machine learning can be attributed to “Internet-scale” datasets, from the development of vision models like CLIP [1] to recent advancements in transformer-based language modeling powered by the Common …","url":["https://arxiv.org/pdf/2408.14037"]}
{"year":"2024","title":"Read-ME: Refactorizing LLMs as Router-Decoupled Mixture of Experts with System Co-Design","authors":["R Cai, Y Ro, GW Kim, P Wang, BE Bejnordi, A Akella…"],"snippet":"The proliferation of large language models (LLMs) has led to the adoption of Mixture-of-Experts (MoE) architectures that dynamically leverage specialized subnetworks for improved efficiency and performance. Despite their benefits, MoE models face significant …","url":["https://utns.cs.utexas.edu/assets/papers/neurips24-readme.pdf"]}
{"year":"2024","title":"Real-Time Continuous Tamil Dialect Speech Recognition and Summarization","authors":["S Saranya, B Bharathi, S Gomathy Dhanya… - Circuits, Systems, and …, 2024"],"snippet":"… With regards to the summarization module, the multilingual Text-to-Text Transfer Transformer (T5) [15] that was pre-trained on a new Common Crawl-based dataset covering 101 languages can be further fine-tuned on the downstream task of …","url":["https://link.springer.com/article/10.1007/s00034-024-02950-5"]}
{"year":"2024","title":"Real-Time Intelligent Detection System Designs for Web Phishing Attacks","authors":["S Asiri - 2024"],"snippet":"… First, they collected URLs using Common Crawl and extracted their domain names to build their vocabulary. Then, they combine this list of vocabulary with common English names. Next, they use the regular expression pattern [a-zA-Z]+|[0-9]+ …","url":["https://search.proquest.com/openview/22ddea7cb8048ff6015fd4868c8e7f5e/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
{"year":"2024","title":"Real-time phishing detection using deep learning methods by extensions","authors":["DM Linh, HD Hung, HM Chau, QS Vu, TN Tran - International Journal of Electrical …, 2024"],"snippet":"… [2] used two algorithms, random forest (RF) and long short-term memory (LSTM), to evaluate the PhishTank and Common Crawl datasets, achieving accuracies of 93.5% and 98.7%, respectively. Similarly, Kumar et al. [3] evaluated using the …","url":["https://www.researchgate.net/profile/Dam-Linh-4/publication/379571132_Real-time_phishing_detection_using_deep_learning_methods_by_extensions/links/660f6efc390c214cfd361601/Real-time-phishing-detection-using-deep-learning-methods-by-extensions.pdf"]}
{"year":"2024","title":"Real-World Robot Applications of Foundation Models: A Review","authors":["K Kawaharazuka, T Matsushima, A Gambardella… - arXiv preprint arXiv …, 2024"],"snippet":"… In terms of the data, the datasets for training LLMs are Internet-scale; for example, the pre-training of GPT-3 [47] uses CommonCrawl covering Internet data from years 2016 to 2019, which amounts to 45TB of compressed plain text and 410 billion …","url":["https://arxiv.org/pdf/2402.05741"]}
{"year":"2024","title":"Reasoning for fact verification using language models","authors":["M Kanaani - 2024"],"snippet":"In response to the proliferation of misinformation on social media platforms, this thesis introduces the Triple-R framework (Retriever, Ranker, Reasoner) to enhance fact-checking by leveraging the Web for evidence retrieval and generating …","url":["https://unbscholar.lib.unb.ca/bitstreams/4202b462-0a7a-47d2-b52e-927c6384ae44/download"]}
{"year":"2024","title":"Recent Advancements and Challenges of Turkic Central Asian Language Processing","authors":["Y Veitsman - arXiv preprint arXiv:2407.05006, 2024"],"snippet":"Research in the NLP sphere of the Turkic counterparts of Central Asian languages, namely Kazakh, Uzbek, Kyrgyz, and Turkmen, comes with the typical challenges of low-resource languages, like data scarcity and a general lack of linguistic resources …","url":["https://arxiv.org/pdf/2407.05006"]}
{"year":"2024","title":"Recent Advances in Generative AI and Large Language Models: Current Status, Challenges, and Perspectives","authors":["DH Hagos, R Battle, DB Rawat - arXiv preprint arXiv:2407.14962, 2024"],"snippet":"The emergence of Generative Artificial Intelligence (AI) and Large Language Models (LLMs) has marked a new era of Natural Language Processing (NLP), introducing unprecedented capabilities that are revolutionizing various domains. This paper …","url":["https://arxiv.org/pdf/2407.14962"]}
{"year":"2024","title":"Recent Advances in Large Language Models for Healthcare","authors":["K Nassiri, MA Akhloufi - BioMedInformatics, 2024"],"snippet":"Recent advances in the field of large language models (LLMs) underline their high potential for applications in a variety of sectors. Their use in healthcare, in particular, holds out promising prospects for improving medical practices. As we highlight in …","url":["https://www.mdpi.com/2673-7426/4/2/62"]}
{"year":"2024","title":"Recent advances in text embedding: A Comprehensive Review of Top-Performing Methods on the MTEB Benchmark","authors":["CAO Hongliu","H Cao - arXiv preprint arXiv:2406.01607, 2024"],"snippet":"… data: (post, comment) pairs from Reddit3, (question, upvoted answer) pairs from Stackexchange4, (entity name + section title, passage) pairs from English Wikipedia, (title, abstract) and citation pairs from Scientific papers [53], and (title, passage) pairs …","url":["https://arxiv.org/pdf/2406.01607","https://www.researchgate.net/profile/Hongliu-Cao/publication/380127334_Recent_advances_in_text_embedding_A_Comprehensive_Review_of_Top-Performing_Methods_on_the_MTEB_Benchmark/links/662becdf06ea3d0b740fe4c9/Recent-advances-in-text-embedding-A-Comprehensive-Review-of-Top-Performing-Methods-on-the-MTEB-Benchmark.pdf"]}
{"year":"2024","title":"Recognizing Textual Inference in Mongolian Bar Exam Questions","authors":["G Khaltarkhuu, B Batjargal, A Maeda - Applied Sciences, 2024"],"snippet":"This paper examines how to apply deep learning techniques to Mongolian bar exam questions. Several approaches that utilize eight different fine-tuned transformer models were demonstrated for recognizing textual inference in Mongolian bar exam …","url":["https://www.mdpi.com/2076-3417/14/3/1073"]}
{"year":"2024","title":"Reconstruction of Differentially Private Text Sanitization via Large Language Models","authors":["S Pang, Z Lu, H Wang, P Fu, Y Zhou, M Xue, B Li - arXiv preprint arXiv:2410.12443, 2024"],"snippet":"Differential privacy (DP) is the de facto privacy standard against privacy leakage attacks, including many recently discovered ones against large language models (LLMs). However, we discovered that LLMs could reconstruct the altered/removed privacy …","url":["https://arxiv.org/pdf/2410.12443"]}
{"year":"2024","title":"Recording First-person Experiences to Build a New Type of Foundation Model","authors":["D Barcari, D Gamez, A Grig - arXiv preprint arXiv:2408.02680, 2024"],"snippet":"… These models are trained on large amounts of text and image data scraped from the Internet - often accessed through the Common Crawl repository. Researchers and technology companies are starting to realize that this data source could become …","url":["https://arxiv.org/pdf/2408.02680"]}
{"year":"2024","title":"RedAgent: Red Teaming Large Language Models with Context-aware Autonomous Language Agent","authors":["H Xu, W Zhang, Z Wang, F Xiao, R Zheng, Y Feng, Z Ba… - arXiv preprint arXiv …, 2024"],"snippet":"Recently, advanced Large Language Models (LLMs) such as GPT-4 have been integrated into many real-world applications like Code Copilot. These applications have significantly expanded the attack surface of LLMs, exposing them to a variety of …","url":["https://arxiv.org/pdf/2407.16667"]}
{"year":"2024","title":"RedPajama: an Open Dataset for Training Large Language Models","authors":["M Weber, DY Fu, Q Anthony, Y Oren, S Adams…"],"snippet":"… our CommonCrawl dataset to approximately the same size as the LLaMA CommonCrawl … The LLaMA corpus includes the C4 dataset [46] to include diverse versions of CommonCrawl… scale is achieved by processing large parts of the …","url":["https://jalms.net/2411.12372v1/","https://openreview.net/pdf?id=lnuXaRpwvw"]}
{"year":"2024","title":"RedStone: Curating General, Code, Math, and QA Data for Large Language Models","authors":["Y Chang, L Cui, L Dong, S Huang, Y Huang, Y Huang… - arXiv preprint arXiv …, 2024"],"snippet":"… This study explores the untapped potential of Common Crawl as a comprehensive and flexible resource for pre-training LLMs, … from Common Crawl, applicable to both general domain data and domain-specific data. As shown in …","url":["https://arxiv.org/pdf/2412.03398"]}
{"year":"2024","title":"Reducing Risks Posed by Synthetic Content","authors":["N AI - 2024"],"snippet":"1 Summary Generative artificial intelligence (AI) technologies can generate realistic images, text, audio, video, as well as multimodal content. This enables novel applications with promising potential for good while also posing new risks to trust …","url":["https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=959123"]}
{"year":"2024","title":"Referring expression segmentation: from conventional to generalized","authors":["C Liu - 2024"],"snippet":"In recent years, many remarkable achievements have been made in the field of deep machine learning in various data modalities, such as image processing and natural language comprehension. Based on the good performance of deep neural …","url":["https://dr.ntu.edu.sg/bitstream/10356/175477/2/Thesis_Liu%20Chang_submit_compress.pdf"]}
{"year":"2024","title":"RegMix: Data Mixture as Regression for Language Model Pre-training","authors":["Q Liu, X Zheng, N Muennighoff, G Zeng, L Dou, T Pang… - arXiv preprint arXiv …, 2024"],"snippet":"… is taken from the C4 dataset [47] and supposed to share a similar distribution as Pile-CC since they are all derived from the CommonCrawl corpus. Since CommonCrawl is a collection of diverse domains, we would expect the correlation …","url":["https://arxiv.org/pdf/2407.01492"]}
{"year":"2024","title":"RELATE: A Modern Processing Platform for Romanian Language","authors":["V Păiş, R Ion, AM Avram, M Mitrofan, D Tufiş - arXiv preprint arXiv:2410.21778, 2024"],"snippet":"This paper presents the design and evolution of the RELATE platform. It provides a high-performance environment for natural language processing activities, specially constructed for Romanian language. Initially developed for text processing, it has …","url":["https://arxiv.org/pdf/2410.21778"]}
{"year":"2024","title":"Reliability Estimation of News Media Sources: Birds of a Feather Flock Together","authors":["S Burdisso, D Sánchez-Cortés, E Villatoro-Tello…"],"snippet":"Evaluating the reliability of news sources is a routine task for journalists and organizations committed to acquiring and disseminating accurate information. Recent research has shown that predicting sources’ reliability represents an …","url":["https://publications.idiap.ch/attachments/papers/2024/Burdisso_NAACL_2024.pdf"]}
{"year":"2024","title":"Reliability of large language models in managing odontogenic sinusitis clinical scenarios: a preliminary multidisciplinary evaluation","authors":["AM Saibene, F Allevi, C Calvo-Henriquez, A Maniaci… - European Archives of Oto …, 2024"],"snippet":"Purpose This study aimed to evaluate the utility of large language model (LLM) artificial intelligence tools, Chat Generative Pre-Trained Transformer (ChatGPT) versions 3.5 and 4, in managing complex otolaryngological clinical scenarios …","url":["https://link.springer.com/article/10.1007/s00405-023-08372-4"]}
{"year":"2024","title":"ReLU $^ 2$ Wins: Discovering Efficient Activation Functions for Sparse LLMs","authors":["Z Zhang, Y Song, G Yu, X Han, Y Lin, C Xiao, C Song… - arXiv preprint arXiv …, 2024"],"snippet":"… For the corpus used for calculating the sparsity statistics, we a mixture of texts from Wikipedia, Pile, and Common Crawl. The total number of tokens is about 217. Since we need to store the activation values of all neurons, we only use a part of the …","url":["https://arxiv.org/pdf/2402.03804"]}
{"year":"2024","title":"Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling","authors":["P Maini, S Seto, H Bai, D Grangier, Y Zhang, N Jaitly - arXiv preprint arXiv …, 2024"],"snippet":"… There are different versions of CommonCrawl data and our selection of C4 for pretraining is driven by driven by its size and quality. … The dataset is also derived from the CommonCrawl, however has a more stringent filtering process. Our …","url":["https://arxiv.org/pdf/2401.16380"]}
{"year":"2024","title":"Representation Bias of Adolescents in AI: A Bilingual, Bicultural Study","authors":["R Wolfe, A Dangol, B Howe, A Hiniker - arXiv preprint arXiv:2408.01961, 2024"],"snippet":"Popular and news media often portray teenagers with sensationalism, as both a risk to society and at risk from society. As AI begins to absorb some of the epistemic functions of traditional media, we study how teenagers in two countries speaking two …","url":["https://arxiv.org/pdf/2408.01961"]}
{"year":"2024","title":"Representation learning for computational sociopragmatics","authors":["C Zhang - 2024"],"snippet":"Natural Language Processing (NLP) emerges as a critical solution for analyzing, manipulating, and understanding human language automatically and computationally, enabling the processing of vast amounts of language data swiftly …","url":["https://open.library.ubc.ca/media/download/pdf/24/1.0445200/4"]}
{"year":"2024","title":"Representation Learning for Generative Models with Applications to Healthcare, Astronautics, and Aviation","authors":["VM Nguyen - 2024"],"snippet":"… Large Language Models (LLMs) like BERT are typically pre-trained on extensive open web datasets, such as the English Wikipedia [50], BookCorpus [180], and Common Crawl [126]. These datasets enable LLMs to develop a robust …","url":["https://repository.fit.edu/cgi/viewcontent.cgi?article=2464&context=etd"]}
{"year":"2024","title":"Representation Learning for Hierarchical Classification of Entity Titles","authors":["E Chistova - Proceedings of the 6th International Conference on …, 2023"],"snippet":"We present a method for effective title encoding for hierarchical classification in a large taxonomy. The method enables taxonomy-aware encoding in pre-trained text encoders, such as fastText and BERT, which are additionally fine-tuned for the …","url":["https://aclanthology.org/2023.icnlsp-1.4.pdf"]}
{"year":"2024","title":"Representing Online Handwriting for Recognition in Large Vision-Language Models","authors":["A Fadeeva, P Schlattner, A Maksai, M Collier… - arXiv preprint arXiv …, 2024"],"snippet":"The adoption of tablets with touchscreens and styluses is increasing, and a key feature is converting handwriting to text, enabling search, indexing, and AI assistance. Meanwhile, vision-language models (VLMs) are now the go-to solution …","url":["https://arxiv.org/pdf/2402.15307"]}
{"year":"2024","title":"Representing relational knowledge with language models","authors":["A Ushio - 2024"],"snippet":"Relational knowledge is the ability to recognize the relationship between instances, and it has an important role in human understanding a concept or commonsense reasoning. We, humans, structure our knowledge by understanding individual …","url":["https://orca.cardiff.ac.uk/id/eprint/168141/1/thesis_clean.pdf"]}
{"year":"2024","title":"Reproduction Rights, Databases and\" Generative\" Artificial Intelligence","authors":["C Meo - Orizzonti del Diritto Commerciale, 2024"],"snippet":"… È quanto accaduto nel caso di ChatGPT, che, almeno in una prima fase, è stato sviluppato da OpenAI sulla base di un dataset prodotto da Common Crawl. In un caso del genere, c'è quindi un'impresa che crea le copie, le immette in un database …","url":["https://heinonline.org/hol-cgi-bin/get_pdf.cgi?handle=hein.journals/oidldoco2024&section=29"]}
{"year":"2024","title":"Research and Application of Large Model-Based Intelligent Customer Service System","authors":["Y Xi - International Journal of Emerging Technologies and …, 2024"],"snippet":"With the rapid development of artificial intelligence technology, intelligent customer service systems have been widely used. This paper addresses the limitations of traditional intelligent customer service systems, such as limited language …","url":["https://www.ijetaa.com/article/download/114/15"]}
{"year":"2024","title":"Research on cross-lingual multi-label patent classification based on pre-trained model","authors":["Y Lu, L Chen, X Tong, Y Peng, H Zhu - Scientometrics, 2024"],"snippet":"Patent classification is an important part of the patent examination and management process. Using efficient and accurate automatic patent classification can significantly improve patent retrieval performance. Current monolingual patent classification …","url":["https://link.springer.com/article/10.1007/s11192-024-05024-0"]}
{"year":"2024","title":"Research on Document-Level Person Relation Extraction in Chinese","authors":["MC Hung, CH Chang, CJ Yeh - 2024"],"snippet":"… 劫ᰱಈຟⳣᒯፔ㽹㻿⌸ፔ劧ᓵ Gemini֊ GPT-3.5动ᜬෟ㉹ἶㆿ䑵㶈⌰㼑劫ઝ௶ⳣ તἶ Common Crawl ἧẤ⋭ᦎ⁠▏ⳣ⸐䅤 ὄ䩗֋⤂ᶷ䷫⌰㼑⸐ေౘ᥅㟪ᜋ䷧ᜬလ⌹ ⸐… ጃလᨛ૽ⳬ Common Crawl ત⚠◅劫ଡ଼ဓ䑛 䒋ᰱಈ⸐⌰㼑◭ㄒ֊ẻ඼Ὗ▊ᨛລ Golden Answers ⸐䅤ὄ䩗ଡ଼ᨐ劫 …","url":["https://easychair.org/publications/preprint/JCvB/open"]}
{"year":"2024","title":"Research Scholar (JRF), Department of Philosophy, The University of Burdwan, Golapbug","authors":["H Patra"],"snippet":"In these days, technology advances very rapidly. Today, we are at the doorstep of constructing a super-intelligent machine capable of mimicking almost all human activities. Initially, we took recourse to science and technology to transcend our …","url":["https://www.researchgate.net/profile/Hemnath-Patra/publication/381676386_A_Foundational_Study_on_the_Philosophy_of_Artificial_Intelligence_and_its_Relevant_Issues/links/667acf241dec0c3c6fa3e7de/A-Foundational-Study-on-the-Philosophy-of-Artificial-Intelligence-and-its-Relevant-Issues.pdf"]}
{"year":"2024","title":"ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models","authors":["J Baek, SK Jauhar, S Cucerzan, SJ Hwang - arXiv preprint arXiv:2404.07738, 2024"],"snippet":"Scientific Research, vital for improving human life, is hindered by its inherent complexity, slow pace, and the need for specialized experts. To enhance its productivity, we propose a ResearchAgent, a large language model-powered …","url":["https://arxiv.org/pdf/2404.07738"]}
{"year":"2024","title":"Responsible Multilingual Large Language Models: A Survey of Development, Applications, and Societal Impact","authors":["J Liu, B Fu - arXiv preprint arXiv:2410.17532, 2024"],"snippet":"Multilingual Large Language Models (MLLMs) represent a pivotal advancement in democratizing artificial intelligence across linguistic boundaries. While theoretical foundations are well-established, practical implementation guidelines remain …","url":["https://arxiv.org/pdf/2410.17532"]}
{"year":"2024","title":"Rethinking Higher Education Teaching and Assessment In-Line with AI Innovations: A Systematic Review and Meta-Analysis","authors":["JN Lyanda, SO Owidi, AM Simiyu - African Journal of Empirical Research, 2024"],"snippet":"With the rapid advancement of artificial intelligence (AI) technologies, higher education institutions are increasingly exploring innovative ways to rethink teaching and assessment practices. This research paper examines the implications of AI on …","url":["https://ajernet.net/ojs/index.php/ajernet/article/download/460/351"]}
{"year":"2024","title":"Retrieval Augmented Generation via Context Compression Techniques for Large Language Models","authors":["P Jiang, R Fan, Y Yong"],"snippet":"Natural language processing has seen lots of improvements, yet optimizing large-scale models to efficiently handle vast amounts of contextual data remains a critical challenge. The novel approach presented integrates advanced context compression …","url":["https://files.osf.io/v1/resources/ua6j5/providers/osfstorage/666b992ed835c435584cecda?action=download&direct&version=1"]}
{"year":"2024","title":"Retrieval-Based Grammatical Error Correction","authors":["JR Vasselli - 2024"],"snippet":"… a cleaned version of the common crawl to produce nearly 200 million ungrammatical sentences with a realistic distribution of errors. … CWEB consists of randomly selected texts from the first 18 dumps of the Common Crawl, which include …","url":["https://naist.repo.nii.ac.jp/record/2000298/files/R018806.pdf"]}
{"year":"2024","title":"Reuse, Don't Retrain: A Recipe for Continued Pretraining of Language Models","authors":["J Parmar, S Satheesh, M Patwary, M Shoeybi… - arXiv preprint arXiv …, 2024"],"snippet":"… In our English corpus, the Web Crawl data is sourced from Common Crawl (CC) snapshots while the remaining categories are comprised of high-quality sets. For instance, the miscellaneous category consists of BigScience ROOTS (Lachaux et al.…","url":["https://arxiv.org/pdf/2407.07263"]}
{"year":"2024","title":"Reverse Modeling in Large Language Models","authors":["S Yu, Y Xu, C Du, Y Zhou, M Qiu, Q Sun, H Zhang… - arXiv preprint arXiv …, 2024"],"snippet":"Humans are accustomed to reading and writing in a forward manner, and this natural bias extends to text understanding in auto-regressive large language models (LLMs). This paper investigates whether LLMs, like humans, struggle with reverse …","url":["https://arxiv.org/pdf/2410.09817"]}
{"year":"2024","title":"Revisión de modelos de lenguaje y aplicación a la automatización de tareas de oficina en empresas industriales","authors":["J Zamora Fraguas - 2023"],"snippet":"This project focuses on the evaluation and application of Large Language Models (LLMs) in natural language processing (NLP). The technical properties, advantages, and disadvantages of LLMs are analysed, highlighting their wide use in machine …","url":["https://repositorio.comillas.edu/xmlui/bitstream/handle/11531/78033/TFM_ZamoraFraguas%2CJacobo%20.pdf?sequence=1"]}
{"year":"2024","title":"Revisiting Adversarial Training at Scale","authors":["Z Wang, X Li, H Zhu, C Xie - arXiv preprint arXiv:2401.04727, 2024"],"snippet":"… DataComp-1B is a more recent dataset with about 1.3B samples filtered from a candidate pool of 12.8B image-text pairs from Common Crawl, which has been recorded to yield superior performance for contrastive training. To summarize, our …","url":["https://arxiv.org/pdf/2401.04727"]}
{"year":"2024","title":"Revisiting Joke Comprehension with Surprisal and Contextual Similarity: Implication from N400 and P600 Components","authors":["H Xu, M Nakanishi, S Coulson - Proceedings of the Annual Meeting of the Cognitive …, 2024"],"snippet":"… Specifically, we used the version with a 2.2 million word vocabulary and 300-dimensional vectors trained on 840 billion tokens from the Common Crawl corpus. The contextual vector of all the words preceding the final word in each sentence was computed by …","url":["https://escholarship.org/content/qt01n9j76q/qt01n9j76q_noSplash_25244bf314716cf3a964d313018efad3.pdf"]}
{"year":"2024","title":"Revisiting Pre-training of Embedding Layers in Transformer-based Neural Machine Translation","authors":["M Neishi, N Yoshinaga - Journal of Natural Language Processing, 2024"],"snippet":"Recent trends in the pre-training and fine-tuning paradigm have made significant advances in several natural language processing tasks, including machine translation (MT), particularly for low-resource situations. However, it is reported that …","url":["https://www.jstage.jst.go.jp/article/jnlp/31/2/31_534/_pdf"]}
{"year":"2024","title":"Revisiting SMoE Language Models by Evaluating Inefficiencies with Task Specific Expert Pruning","authors":["S Sarkar, L Lausen, V Cevher, S Zha, T Brox, G Karypis - arXiv preprint arXiv …, 2024"],"snippet":"… It is sourced from the Common Crawl, a web archive that captures vast amounts of text data from the internet. We … the Common Crawl, covering 108 languages [46]. It is a subset of the Colossal Clean Crawled Corpus (C4), which itself is a cleaned …","url":["https://arxiv.org/pdf/2409.01483"]}
{"year":"2024","title":"Revolutionizing College English Reading with ChatGPT: Current Predicaments and Future Directions","authors":["W Li, Y Tang, S Wang - Transactions on Social Science, Education and …, 2024"],"snippet":"… The training data mainly includes website data in Common Crawl, two internet-based books corpora, and Englishlanguage Wikipedia [11]. ChatGPT trains a large amount of Internet information without distinguishing the true from the false and unifying …","url":["http://wepub.org/index.php/TSSEHR/article/download/2552/2773"]}
{"year":"2024","title":"Revolutionizing Urdu Sentiment Analysis: Harnessing the Power of XLM-R and GPT-2","authors":["MR Ashraf, M Hussain, MA Jaffar, WY Ramay… - IEEE Access, 2024"],"snippet":"… In our proposed approach XLM-R leverages much larger CommonCrawl web data across 100 languages and uses a larger 250k SentencePiece vocabulary to improve subword coverage of Urdu Text. Beyond masked language modeling, XLM-R …","url":["https://ieeexplore.ieee.org/iel8/6287639/6514899/10600706.pdf"]}
{"year":"2024","title":"Rho-1: Not All Tokens Are What You Need","authors":["Z Lin, Z Gou, Y Gong, X Liu, Y Shen, R Xu, C Lin… - arXiv preprint arXiv …, 2024"],"snippet":"Previous language model pre-training methods have uniformly applied a next-token prediction loss to all training tokens. Challenging this norm, we posit that \"Not all tokens in a corpus are equally important for language model training\". Our initial …","url":["https://arxiv.org/pdf/2404.07965"]}
{"year":"2024","title":"Risk Mitigation Strategies for the Open Foundation Model Value Chain","authors":["M Srikumar, K Chmielinski, J Chang"],"snippet":"Policymakers worldwide are designing interventions to ensure AI development is safe and responsible. In the EU, the newly formed AI Office is drafting codes of practice for general purpose AI models, while in the US, state legislatures are …","url":["https://partnershiponai.org/wp-content/uploads/dlm_uploads/2024/07/open-foundation-model-risk-mitigation_rev3-1.pdf"]}
{"year":"2024","title":"Risks, Causes, and Mitigations of Widespread Deployments of Large Language Models (LLMs): A Survey","authors":["MN Sakib, MA Islam, R Pathak, MM Arifin - arXiv preprint arXiv:2408.04643, 2024"],"snippet":"Recent advancements in Large Language Models (LLMs), such as ChatGPT and LLaMA, have significantly transformed Natural Language Processing (NLP) with their outstanding abilities in text generation, summarization, and classification …","url":["https://arxiv.org/pdf/2408.04643"]}
{"year":"2024","title":"RLHF Can Speak Many Languages: Unlocking Multilingual Preference Optimization for LLMs","authors":["J Dang, A Ahmadian, K Marchisio, J Kreutzer, A Üstün… - arXiv preprint arXiv …, 2024"],"snippet":"Preference optimization techniques have become a standard final stage for training state-of-art large language models (LLMs). However, despite widespread adoption, the vast majority of work to-date has focused on first-class citizen languages like …","url":["https://arxiv.org/pdf/2407.02552"]}
{"year":"2024","title":"Roberta-LightGBM: A hybrid model of deep fake detection with pre-trained and binary classification","authors":["V Rajkumar - INFOCOMP Journal of Computer Science, 2024"],"snippet":"In May 2023, a fake image of an explosion near the Pentagon gained widespread social media traction. It dragged down US markets momentarily, perhaps marking the first time an artificial intelligence (AI)-generated image has affected the market …","url":["http://177.105.60.18/index.php/infocomp/article/view/3060/612"]}
{"year":"2024","title":"RoBERTaNET: Enhanced RoBERTa Transformer Based Model for Cyberbullying Detection with GloVe Features","authors":["F Alrowais, AA Jamjoom, H Karamti, M Umer, S Alsubai… - IEEE Access, 2024"],"snippet":"… 3) FastText FastText is a word illustration library, that encompasses 300dimensional 2 million common crawl words, resulting in 600 billion word vectors [31]. Particularly, hand-crafted ngrams are used as features alongside solo words. Its straightforward …","url":["https://ieeexplore.ieee.org/iel7/6287639/6514899/10495045.pdf"]}
{"year":"2024","title":"Robust Neural Machine Translation for Abugidas by Glyph Perturbation","authors":["H Kaing, C Ding, H Tanaka, M Utiyama - Proceedings of the 18th Conference of the …, 2024"],"snippet":"Neural machine translation (NMT) systems are vulnerable when trained on limited data. This is a common scenario in low-resource tasks in the real world. To increase robustness, a solution is to intently add realistic noise in the training phase. Noise …","url":["https://aclanthology.org/2024.eacl-short.27.pdf"]}
{"year":"2024","title":"RoCode: A Dataset for Measuring Code Intelligence from Problem Definitions in Romanian","authors":["A Cosma, B Iordache, P Rosso - arXiv preprint arXiv:2402.13222, 2024"],"snippet":"… Even if code is present in the dataset (from Common Crawl), it is described in English and comments and documentation are in English. The same argument can be made for mathematics and other scientific disciplines. A large, highly curated and …","url":["https://arxiv.org/pdf/2402.13222"]}
{"year":"2024","title":"RoMath: A Mathematical Reasoning Benchmark in Romanian","authors":["A Cosma, AM Bucur, E Radoi - arXiv preprint arXiv:2409.11074, 2024"],"snippet":"… For pretraining, the general approach is to filter Common Crawl web pages and PDFs to obtain high quality math tokens. For instance, … 2024b) that would arise from dumps such as Common Crawl. Figure 1 showcases our approach. After …","url":["https://arxiv.org/pdf/2409.11074"]}
{"year":"2024","title":"ROME: Memorization Insights from Text, Probability and Hidden State in Large Language Models","authors":["B Li, Q Zhao, L Wen - arXiv preprint arXiv:2403.00510, 2024"],"snippet":"Probing the memorization of large language models holds significant importance. Previous works have established metrics for quantifying memorization, explored various influencing factors, such as data duplication, model size, and prompt length …","url":["https://arxiv.org/pdf/2403.00510"]}
{"year":"2024","title":"RoQLlama: A Lightweight Romanian Adapted Language Model","authors":["GA Dima, AM Avram, CG Crăciun, DC Cercel - arXiv preprint arXiv:2410.04269, 2024"],"snippet":"The remarkable achievements obtained by open-source large language models (LLMs) in recent years have predominantly been concentrated on tasks involving the English language. In this paper, we aim to advance the performance of Llama2 …","url":["https://arxiv.org/pdf/2410.04269"]}
{"year":"2024","title":"RU22Fact: Optimizing Evidence for Multilingual Explainable Fact-Checking on Russia-Ukraine Conflict","authors":["Y Zeng, X Ding, Y Zhao, X Li, J Zhang, C Yao, T Liu… - arXiv preprint arXiv …, 2024"],"snippet":"Fact-checking is the task of verifying the factuality of a given claim by examining the available evidence. High-quality evidence plays a vital role in enhancing fact-checking systems and facilitating the generation of explanations that are understandable to …","url":["https://arxiv.org/html/2403.16662v1"]}
{"year":"2024","title":"RuBia: A Russian Language Bias Detection Dataset","authors":["V Grigoreva, A Ivanova, I Alimova, E Artemova - arXiv preprint arXiv:2403.17553, 2024"],"snippet":"Warning: this work contains upsetting or disturbing content. Large language models (LLMs) tend to learn the social and cultural biases present in the raw pre-training data. To test if an LLM's behavior is fair, functional datasets are employed, and due to their …","url":["https://arxiv.org/pdf/2403.17553"]}
{"year":"2024","title":"Rule-based Data Selection for Large Language Models","authors":["X Li, M Gao, Z Zhang, C Yue, H Hu - arXiv preprint arXiv:2410.04715, 2024"],"snippet":"… We compute their Pearson correlation and observe positive values for both IMDB and CommonCrawl datasets (see Figures 2a and 2b). … results than rating without rules, no matter applied to general data like CommonCrawl or domain-specific data …","url":["https://arxiv.org/pdf/2410.04715"]}
{"year":"2024","title":"Safety cases for frontier AI","authors":["MD Buhl, G Sett, L Koessler, J Schuett, M Anderljung - arXiv preprint arXiv …, 2024"],"snippet":"As frontier artificial intelligence (AI) systems become more capable, it becomes more important that developers can explain why their systems are sufficiently safe. One way to do so is via safety cases: reports that make a structured argument, supported …","url":["https://arxiv.org/pdf/2410.21572"]}
{"year":"2024","title":"Sailor: Open Language Models for South-East Asia","authors":["L Dou, Q Liu, G Zeng, J Guo, J Zhou, W Lu, M Lin - arXiv preprint arXiv:2404.03608, 2024"],"snippet":"We present Sailor, a family of open language models ranging from 0.5B to 7B parameters, tailored for South-East Asian (SEA) languages. These models are continually pre-trained from Qwen1.5, a great language model for multilingual use …","url":["https://arxiv.org/pdf/2404.03608"]}
{"year":"2024","title":"SALT: Sales Autocompletion Linked Business Tables Dataset","authors":["T Klein, C Biehl, M Costa, J Kolk, J Hoffart - NeurIPS 2024 Third Table Representation …"],"snippet":"Foundation models, particularly those that incorporate Transformer architectures, have demonstrated exceptional performance in domains such as natural language processing and image processing. Adapting these models to structured data, like …","url":["https://openreview.net/pdf?id=UZbELpkWIr"]}
{"year":"2024","title":"Sampling-based Pseudo-Likelihood for Membership Inference Attacks","authors":["M Kaneko, Y Ma, Y Wata, N Okazaki - arXiv preprint arXiv:2404.11262, 2024"],"snippet":"… 2023): LLaMA-2 employs English CommonCrawl, C4, Github, Wikipedia, Books, ArXiv, and StackExchange as pre-training datasets. … or filtered to contain predominantly English text, but a small amount of non-English data is still present …","url":["https://arxiv.org/pdf/2404.11262"]}
{"year":"2024","title":"Scaffold-BPE: Enhancing Byte Pair Encoding with Simple and Effective Scaffold Token Removal","authors":["H Lian, Y Xiong, J Niu, S Mo, Z Su, Z Lin, P Liu, H Chen… - arXiv preprint arXiv …, 2024"],"snippet":"… The Pile is composed of 22 diverse and high-quality datasets, the models trained on which significantly outperform both raw and filtered Common Crawl [10] models. The data distribution for our model training is identical to those described in the …","url":["https://arxiv.org/pdf/2404.17808"]}
{"year":"2024","title":"Scaffolding learning: From specific to generic with large language models","authors":["DS Yin, X Yin - PloS one, 2024"],"snippet":"… In the past decade many large models are first trained on a generic dataset (such as ImageNet [7] or CommonCrawl), and then fine-tuned … A model could be pre-trained on a huge dataset such as ImageNet [7] or CommonCrawl, in order to give it a …","url":["https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0310409"]}
{"year":"2024","title":"Scalable Distributed String Sorting","authors":["F Kurpicz, P Mehnert, P Sanders, M Schimek - arXiv preprint arXiv:2404.16517, 2024"],"snippet":"… While different sampling and group assignment techniques may improve character balance, the CommonCrawl data set contains many duplicated strings (eg, standard legal disclaimers) which are always assigned to a single PE and cannot be …","url":["https://arxiv.org/pdf/2404.16517"]}
{"year":"2024","title":"Scalable Pre-training of Large Autoregressive Image Models","authors":["A El-Nouby, M Klein, S Zhai, MA Bautista, A Toshev… - arXiv preprint arXiv …, 2024"],"snippet":"This paper introduces AIM, a collection of vision models pre-trained with an autoregressive objective. These models are inspired by their textual counterparts, ie, Large Language Models (LLMs), and exhibit similar scaling properties. Specifically …","url":["https://arxiv.org/pdf/2401.08541"]}
{"year":"2024","title":"Scalable Range Search over Temporal and Numerical Expressions","authors":["V Ohr, D Gupta - The 10th ACM SIGIR/The 14th International …"],"snippet":"… a subset of Common Crawl amounting to … Common Crawl, published as C4 [30]. This document collection consists of approximately 13.81 million documents. The fourth and final document collection we use is the entire C4-En corpus derived from …","url":["https://openreview.net/pdf?id=84vTskBRPU"]}
{"year":"2024","title":"Scaling A Simple Approach to Zero-Shot Speech Recognition","authors":["J Zhao, V Pratap, M Auli - arXiv preprint arXiv:2407.17852, 2024"],"snippet":"… Figure 2 Accuracy on FLEURS dev languages when increasing the amount of CommonCrawl text data to build lexicons and unigram LMs compared to using in-domain text data (FLEURS-topline; 3k utterances). … Data is drawn from CommonCrawl (CC; …","url":["https://arxiv.org/pdf/2407.17852"]}
{"year":"2024","title":"Scaling and Renormalization in Statistical Learning","authors":["AB Atanasov - 2024"],"snippet":"This thesis develops a theoretical framework for understanding the scaling properties of information processing systems in the regime of large data, large model size, and large computational resources. The goal is to develop an …","url":["https://search.proquest.com/openview/2b5d023183b1fd7616dec14afd7c7afc/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
{"year":"2024","title":"Scaling Diffusion Language Models via Adaptation from Autoregressive Models","authors":["S Gong, S Agarwal, Y Zhang, J Ye, L Zheng, M Li, C An… - arXiv preprint arXiv …, 2024"],"snippet":"Diffusion Language Models (DLMs) have emerged as a promising new paradigm for text generative modeling, potentially addressing limitations of autoregressive (AR) models. However, current DLMs have been studied at a smaller scale compared to …","url":["https://arxiv.org/pdf/2410.17891"]}
{"year":"2024","title":"Scaling Laws for Data Filtering--Data Curation cannot be Compute Agnostic","authors":["S Goyal, P Maini, ZC Lipton, A Raghunathan, JZ Kolter - arXiv preprint arXiv …, 2024"],"snippet":"… As we train for longer, the accuracy gains using the LAION-filtering subset that filters the common crawl to 10% of its initial size plateau. Surprisingly, even no-filtering of the common crawl is better than the popular LAION-filtering after seeing more …","url":["https://arxiv.org/pdf/2404.07177"]}
{"year":"2024","title":"Scaling Laws for Multilingual Language Models","authors":["Y He, A Benhaim, B Patra, P Vaddamanu, S Ahuja… - arXiv preprint arXiv …, 2024"],"snippet":"We propose a novel scaling law for general-purpose decoder-only language models (LMs) trained on multilingual data, addressing the problem of balancing languages during multilingual pretraining. A primary challenge in studying multilingual scaling …","url":["https://arxiv.org/pdf/2410.12883"]}
{"year":"2024","title":"Scaling Laws for Predicting Downstream Performance in LLMs","authors":["Y Chen, B Huang, Y Gao, Z Wang, J Yang, H Ji - arXiv preprint arXiv:2410.08527, 2024"],"snippet":"Precise estimation of downstream performance in large language models (LLMs) prior to training is essential for guiding their development process. Scaling laws analysis utilizes the statistics of a series of significantly smaller sampling language …","url":["https://arxiv.org/pdf/2410.08527"]}
{"year":"2024","title":"Scaling neural machine translation to 200 languages","authors":["Nature, 2024"],"snippet":"… To overcome this problem, we created training datasets through global bitext mining in publicly available web content (drawn from repositories such as CommonCrawl). The underlying idea of our bitext mining approach is first to learn a …","url":["https://www.nature.com/articles/s41586-024-07335-x"]}
{"year":"2024","title":"Scaling Retrieval-Based Language Models with a Trillion-Token Datastore","authors":["R Shao, J He, A Asai, W Shi, T Dettmers, S Min… - arXiv preprint arXiv …, 2024"],"snippet":"Scaling laws with respect to the amount of training data and the number of parameters allow us to predict the cost-benefit trade-offs of pretraining language models (LMs) in different configurations. In this paper, we consider another …","url":["https://arxiv.org/pdf/2407.12854"]}
{"year":"2024","title":"ScalingFilter: Assessing Data Quality through Inverse Utilization of Scaling Laws","authors":["R Li, Y Wei, M Zhang, N Yu, H Hu, H Peng - arXiv preprint arXiv:2408.08310, 2024"],"snippet":"… We begin with five CommonCrawl … CommonCrawl data with no more than 25B tokens. Each dataset was used to train meta-models for 1 epoch. The results demonstrate that all experiments outperform the baseline of random selection. Training …","url":["https://arxiv.org/pdf/2408.08310"]}
{"year":"2024","title":"sCambiaMenti at ACTI: Ensemble model with majority voting for Automatic Conspiracy Detection","authors":["S Bianco, D Salusso - EVALITA Proceedings of the Eighth Evaluation …, 2024"],"snippet":"In this paper we describe the methodology that we have implemented to solve the subtask A of the Automatic Conspiracy Detection (ACTI) task (EVALITA 2023). We have developed different classifiers and then used a majority voting approach to …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=ZLfuEAAAQBAJ&oi=fnd&pg=PA271&dq=commoncrawl&ots=BBnDdqOBAj&sig=Hn5VYj3sI8L2xkD1qqoIQsmOQOw"]}
{"year":"2024","title":"ScenicNL: Generating Probabilistic Scenario Programs from Natural Language","authors":["K Elmaaroufi, D Shanker, A Cismaru… - First Conference on Language …"],"snippet":"… Most of these model’s are fine-tuned variants of a foundational model that was trained on a wider body of text such as Common Crawl. For instance Codex is ”a GPT language model fine-tuned on publicly available code from GitHub” and it’s …","url":["https://openreview.net/pdf?id=MNLAbfZwh2"]}
{"year":"2024","title":"SchemaPile: A Large Collection of Relational Database Schemas","authors":["T Döhmen, R Geacu, M Hulsebos, S Schelter - … of the ACM on Management of Data, 2024"],"snippet":"… such as the aforementioned code dataset The Stack [25] or web crawls such as CommonCrawl [12] as alternative data sources. Furthermore, enterprises could adapt our data … Common Crawl – a free, open repository of web crawl data that …","url":["https://dl.acm.org/doi/pdf/10.1145/3654975"]}
{"year":"2024","title":"School of Computing","authors":["MD Wiciak"],"snippet":"This paper delves into the realm of code completion, specifically focusing on Masked Language Modelling (MLM) tasks within the context of software development. Code completion, a pivotal feature in enhancing developer productivity …","url":["https://michaelwiciak.com/static/media/Dissertation.d2451bcb.pdf"]}
{"year":"2024","title":"Science Out of Its Ivory Tower: Improving Accessibility with Reinforcement Learning","authors":["H Wang, J Clark, H McKelvey, L Sterman, Z Gao, Z Tian… - arXiv preprint arXiv …, 2024"],"snippet":"A vast amount of scholarly work is published daily, yet much of it remains inaccessible to the general public due to dense jargon and complex language. To address this challenge in science communication, we introduce a reinforcement …","url":["https://arxiv.org/pdf/2410.17088"]}
{"year":"2024","title":"SCIR-MT's Submission for WMT24 General Machine Translation Task","authors":["B Li, Z Ye, Y Huang, X Feng, B Qin"],"snippet":"This paper introduces the submission of SCIR research center of Harbin Institute of Technology participating in the WMT24 machine translation evaluation task of constrained track for English to Czech. Our approach involved a rigorous process of …","url":["https://www2.statmt.org/wmt24/pdf/2024.wmt-1.21.pdf"]}
{"year":"2024","title":"Scoping: Towards Streamlined Entity Collections for Multi-Sourced Entity Resolution with Self-Supervised Agents","authors":["L Traeger, A Behrend, G Karabatis"],"snippet":"Linking multiple entities to a real-world object is a time-consuming and error-prone task. Entity Resolution (ER) includes techniques for vectorizing entities (signature), grouping similar entities into partitions (blocking), and matching entity pairs based …","url":["https://www.scitepress.org/Papers/2024/126075/126075.pdf"]}
{"year":"2024","title":"Screening Articles for Systematic Reviews with ChatGPT","authors":["E Syriani, I David, G Kumar"],"snippet":"… ChatGPT is a Chatbot Generative Pre-trained Transformer that employs an auto-regressive language model pre-trained on large datasets with bil250 lions of tokens from CommonCrawl, Wikipedia, and other publicly available text sources. ChatGPT relies …","url":["https://istvandavid.com/files/ChatGPT-Screening-SR-COLA.pdf"]}
{"year":"2024","title":"SD-WEAT: Towards Robustly Measuring Bias in Input Embeddings for Artificial Intelligence Language Models","authors":["MA Gray - 2024"],"snippet":"Artificial intelligence (AI) is rapidly transforming industries and markets, from healthcare to entertainment, revolutionizing decision-making processes. However, as AI grow more influential, they also risk amplifying existing biases, potentially …","url":["https://search.proquest.com/openview/27e7cd9894ea378b1d47b3f770cf250d/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
{"year":"2024","title":"SD-WEAT: Towards Robustly Measuring Bias in Input Embeddings","authors":["M Gray, L Wu - International Conference on Human-Computer …, 2024"],"snippet":"… 300d” from the Stanford NLP Group [9], which was trained on 840 billion tokens from Common Crawl data and generates 300-dimension vectors. Moreover, other input embedding methods, including those of BERT [10, 11], SciBERT [12, 13], and …","url":["https://link.springer.com/chapter/10.1007/978-3-031-62110-9_5"]}
{"year":"2024","title":"SEACrowd: A Multilingual Multimodal Data Hub and Benchmark Suite for Southeast Asian Languages","authors":["GI Winata, R Zhang, F Koto, ZX Yong, S Cahyawijaya","H Lovenia, R Mahendra, SM Akbar, LJV Miranda… - arXiv preprint arXiv …, 2024"],"snippet":"Southeast Asia (SEA) is a region rich in linguistic diversity and cultural variety, with over 1,300 indigenous languages and a population of 671 million people. However, prevailing AI models suffer from a significant lack of representation of texts, images …","url":["https://arxiv.org/pdf/2406.10118","https://www.researchgate.net/profile/Holy-Lovenia-2/publication/386184297_SEACrowd_A_Multilingual_Multimodal_Data_Hub_and_Benchmark_Suite_for_Southeast_Asian_Languages/links/67591b666150084b45f9f30c/SEACrowd-A-Multilingual-Multimodal-Data-Hub-and-Benchmark-Suite-for-Southeast-Asian-Languages.pdf"]}
{"year":"2024","title":"SeaLLMs 3: Open Foundation and Chat Multilingual Large Language Models for Southeast Asian Languages","authors":["W Zhang, HP Chan, Y Zhao, M Aljunied, J Wang, C Liu… - arXiv preprint arXiv …, 2024"],"snippet":"Large Language Models (LLMs) have shown remarkable abilities across various tasks, yet their development has predominantly centered on high-resource languages like English and Chinese, leaving low-resource languages underserved …","url":["https://arxiv.org/pdf/2407.19672"]}
{"year":"2024","title":"Searching, navigating, and querying arguments and debates: tools, languages and methodologies","authors":["G Flouris, J Lawrence, D Zografistou"],"snippet":"Recent developments in Web technologies have transformed Web users from passive consumers to active creators of digital content. As users see the Web as a means to enable dialogical exchange, debating, and commenting on products …","url":["http://users.ics.forth.gr/~fgeo/files/HOFA3_ArgQuerying.pdf"]}
{"year":"2024","title":"Second Language (Arabic) Acquisition of LLMs via Progressive Vocabulary Expansion","authors":["J Zhu, H Hunag, Z Lin, J Liang, Z Tang, K Almubarak…"],"snippet":"This paper addresses the critical need for democratizing large language models (LLM) in the Arab world, a region that has seen slower progress in developing models comparable to state-of-the-art offerings like GPT-4 or ChatGPT 3.5, due to a …","url":["https://huggingface.co/FreedomIntelligence/AceGPT-v1.5-13B-Chat/resolve/main/Second_Language_(Arabic)_Acquisition_of_LLMs_via_Progressive_Vocabulary_Expansion.pdf"]}
{"year":"2024","title":"Secret Collusion Among Generative AI Agents","authors":["SR Motwani, M Baranchuk, M Strohmeier, V Bolina… - arXiv preprint arXiv …, 2024"],"snippet":"Recent capability increases in large language models (LLMs) open up applications in which teams of communicating generative AI agents solve joint tasks. This poses privacy and security challenges concerning the unauthorised sharing of information …","url":["https://arxiv.org/pdf/2402.07510"]}
{"year":"2024","title":"SECTION ALIGNMENT TO DETECT DOCUMENT LINKS EFFICIENTLY","authors":["J Stegink"],"snippet":"When searching for information, users often use search engines like Google1 or Bing2. These search engines have access to a wealth of publicly available information. To make finding the information even simpler and for processing and …","url":["https://research.ou.nl/files/82441158/Stegink_J_IM9906_SE_AF_Scriptie_PURE.pdf"]}
{"year":"2024","title":"Secured Weight Release for Large Language Models via Taylor Expansion","authors":["G Wang, YN Chuang, R Tang, S Zhong, J Yuan, H Jin…"],"snippet":"Ensuring the security of released large language models (LLMs) poses a significant dilemma, as existing mechanisms either compromise ownership rights or raise data privacy concerns. To address this dilemma, we introduce TaylorMLP to protect the …","url":["https://www.researchgate.net/profile/Guanchu-Wang-3/publication/381662847_Secured_Weight_Release_for_Large_Language_Models_via_Taylor_Expansion/links/6679b8451846ca33b84f83ab/Secured-Weight-Release-for-Large-Language-Models-via-Taylor-Expansion.pdf"]}
{"year":"2024","title":"Security strategies for AI systems in Industry 4.0","authors":["JA Bairaktaris, A Johannssen, KP Tran - Quality and Reliability Engineering International"],"snippet":"… A common approach in AI systems involves using vast amounts of data, nearly a trillion words, from datasets like “Common Crawl” to train models. Common Crawl assembles its extensive dataset through web crawling, which begins with a list of …","url":["https://onlinelibrary.wiley.com/doi/abs/10.1002/qre.3678"]}
{"year":"2024","title":"SeeClick: Harnessing GUI Grounding for Advanced Visual GUI Agents","authors":["K Cheng, Q Sun, Y Chu, F Xu, Y Li, J Zhang, Z Wu - arXiv preprint arXiv:2401.10935, 2024"],"snippet":"… We collected approximately 300k web pages from the latest Common Crawl repository 2 to serve as our training data for web UI. For each webpage, we collect two types of elements from the HTML code: (1) elements that display visible text …","url":["https://arxiv.org/pdf/2401.10935"]}
{"year":"2024","title":"Seeds of Stereotypes: A Large-Scale Textual Analysis of Race and Gender Associations with Diseases in Online Sources","authors":["L Hyldig Hansen, N Andersen, J Gallifant, LG McCoy… - arXiv e-prints, 2024","LH Hansen, N Andersen, J Gallifant, LG McCoy… - arXiv preprint arXiv …, 2024"],"snippet":"… Methods We conducted a large-scale textual analysis using a dataset comprising diverse web sources, including Arxiv, Wikipedia, and Common Crawl. The study analyzed the context in which various diseases are discussed alongside markers of …","url":["https://arxiv.org/pdf/2405.05049","https://ui.adsabs.harvard.edu/abs/2024arXiv240505049H/abstract"]}
{"year":"2024","title":"Selecting Large Language Model to Fine-tune via Rectified Scaling Law","authors":["H Lin, B Huang, H Ye, Q Chen, Z Wang, S Li, J Ma… - arXiv preprint arXiv …, 2024"],"snippet":"The ever-growing ecosystem of LLMs has posed a challenge in selecting the most appropriate pre-trained model to fine-tune amidst a sea of options. Given constrained resources, fine-tuning all models and making selections afterward is …","url":["https://arxiv.org/pdf/2402.02314"]}
{"year":"2024","title":"Selective Metric Differential Privacy for Language Models","authors":["A Maratkhan - 2023"],"snippet":"… We used a pre-trained GloVe model trained on Common Crawl data with 840B tokens with a 2.2M vocabulary size for the privatization mechanism. We chose to utilize this model because it has a large vocabulary and is case-sensitive. Since GPT-2 …","url":["https://digital.lib.washington.edu/researchworks/bitstream/handle/1773/51067/Maratkhan_washington_0250O_26461.pdf?sequence=1"]}
{"year":"2024","title":"Self-Augmented In-Context Learning for Unsupervised Word Translation","authors":["Y Li, A Korhonen, I Vulić - arXiv preprint arXiv:2402.10024, 2024"],"snippet":"… 2017): the version pretrained on Wikipedia7 is used for XLING and the version pretrained with Wikipedia plus Common Crawl8 is used for PanLex-BLI, as recommended by XLING and PanLex-BLI, respectively. The same WEs are used for …","url":["https://arxiv.org/pdf/2402.10024"]}
{"year":"2024","title":"Self-Supervised Pre-Training with Joint-Embedding Predictive Architecture Boosts ECG Classification Performance","authors":["K Weimann, TOF Conrad - arXiv preprint arXiv:2410.13867, 2024"],"snippet":"Accurate diagnosis of heart arrhythmias requires the interpretation of electrocardiograms (ECG), which capture the electrical activity of the heart. Automating this process through machine learning is challenging due to the need for …","url":["https://arxiv.org/pdf/2410.13867"]}
{"year":"2024","title":"SEMANT-Feature Group Selection Utilizing FastText-Based Semantic Word Grouping, Scoring, and Modeling Approach for Text Classification","authors":["D Voskergian, B Bakir-Gungor, M Yousef - International Conference on Database and …, 2024"],"snippet":"Text classification presents a challenge due to its high-dimensional feature space. As such, devising an effective feature selection scheme is essential. In this study, we present SEMANT, a novel hybrid filter-wrapper feature selection method that utilizes …","url":["https://link.springer.com/chapter/10.1007/978-3-031-68312-1_5"]}
{"year":"2024","title":"SEMANTIC MATCHING FOR DATA CATALOGS","authors":["S Sheen - 2024"],"snippet":"Modern organizations have a lot of data, and more is coming. This data is often spread across the entire organization, appearing in various forms, such as CSV files, databases, PPTX slides, emails, etc. To organize and manage the various forms of …","url":["https://asset.library.wisc.edu/1711.dl/75YVXSFWZNMHR84/R/file-cf8dd.pdf"]}
{"year":"2024","title":"Semantic-Aware Methods for the Analysis of Bias and Underrepresentation in Language Resources","authors":["MA Stranisci - 2024"],"snippet":"… Within this research I did not analyze Common Crawl5, even if it is mentioned in some LMs papers. This is because it is not a proper … CC-News is a snapshot of news texts derived from the CommonCrawl initiative9) that has been exploited for …","url":["https://iris.unito.it/bitstream/2318/1995551/2/tesi_stranisci.pdf"]}
{"year":"2024","title":"Semantic-guided spatio-temporal attention for few-shot action recognition","authors":["J Wang, B Liu - Applied Intelligence, 2024"],"snippet":"… We utilize GloVe [49] to extract text embeddings for action labels, which is pre-trained on Common Crawl dataset of 840B tokens. For labels with multiple words, we average the embeddings of all their words. Finally, one action label is represented …","url":["https://link.springer.com/article/10.1007/s10489-024-05294-4"]}
{"year":"2024","title":"Semantically Enriched Cross-Lingual Sentence Embeddings for Crisis-related Social Media Texts","authors":["R Lamsal, MR Read, S Karunasekera - arXiv preprint arXiv:2403.16614, 2024"],"snippet":"Tasks such as semantic search and clustering on crisis-related social media texts enhance our comprehension of crisis discourse, aiding decision-making and targeted interventions. Pre-trained language models have advanced performance in …","url":["https://arxiv.org/pdf/2403.16614"]}
{"year":"2024","title":"Semi-Automated Classification of Adverse Events in Alzheimer's Disease Clinical Trials","authors":["GA Jimenez-Maggiora - 2024"],"snippet":"Investigators conducting clinical trials have an ethical, scientific, and regulatory obligation to protect the safety of trial participants. Traditionally, safety monitoring includes manual review and coding of adverse event data by expert clinicians. Our …","url":["https://search.proquest.com/openview/ac9aa19a78bd62396f5f7d6167aa0f93/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
{"year":"2024","title":"Semi-Automated Coding for Conflict Mediation Research: Database Development","authors":["E D'Amico - 2024"],"snippet":"… In plain terms, our database employs a combination of Common Crawl and real-time APIs from major news websites to gather comprehensive event data. Common Crawl (2008) is a vast archive that regularly scans the internet, collecting articles …","url":["https://era.ed.ac.uk/bitstream/handle/1842/42939/Semi-Automated-Coding-for-Conflict-Mediation-Research-DIGITAL.pdf?sequence=1&isAllowed=y"]}
{"year":"2024","title":"Semiotics of Machinic Co-Enunciation","authors":["E D'Armenio, A Deliège, MG Dondero"],"snippet":"1 In this paper, we propose a semiotic study on generative artificial intelligences, considering the work of Midjourney and DALL· E. 1 The aim is to frame their functioning from a semiotic point of view and to describe the operations that can be …","url":["https://www.researchgate.net/profile/Enzo-Darmenio/publication/383859338_Semiotics_of_Machinic_Co-Enunciation_About_Generative_Models_Midjourney_and_DALLE/links/66dd5a90bd20173667bf81ee/Semiotics-of-Machinic-Co-Enunciation-About-Generative-Models-Midjourney-and-DALLE.pdf"]}
{"year":"2024","title":"SEN-CTD: semantic enhancement network with content-title discrepancy for fake news detection","authors":["J Fang, K Ma, Y Qiu, K Ji, Z Chen, B Yang - International Journal of Web Information …, 2024"],"snippet":"Purpose The discrepancy between the content of an article and its title is a key characteristic of fake news. Current methods for detecting fake news often ignore the significant difference in length between the content and its title. In addition, relying …","url":["https://www.emerald.com/insight/content/doi/10.1108/IJWIS-04-2024-0116/full/html"]}
{"year":"2024","title":"SeNSe: embedding alignment via semantic anchors selection","authors":["L Malandri, F Mercorio, M Mezzanzanica, F Pallucchini - International Journal of Data …, 2024"],"snippet":"Word embeddings have proven extremely useful across many NLP applications in recent years. Several key linguistic tasks, such as machine translation and transfer learning, require comparing distributed representations of words belonging to …","url":["https://link.springer.com/article/10.1007/s41060-024-00522-z"]}
{"year":"2024","title":"SENTA: Sentence Simplification System for Slovene","authors":["A Žagar, M Klemen, M Robnik-Šikonja, I Kosem - Proceedings of the 2024 Joint …, 2024"],"snippet":"… It uses sentence-level paraphrase data obtained by mining paraphrases from Common Crawl in combination with controllable generation mechanisms to adjust the length and lexical complexity of a simplified candidate. …","url":["https://aclanthology.org/2024.lrec-main.1279.pdf"]}
{"year":"2024","title":"Sentence Embeddings for Massively Multilingual Speech and Text Processing","authors":["PA Duquenne - 2024"],"snippet":"… CommonCrawl raw text data corresponds to partial snapshots of the internet totalling terabytes of text data extracted from web pages in many languages. The authors used the open-source FAISS library (Johnson et al. 2019) in order to …","url":["https://theses.hal.science/tel-04573934/document"]}
{"year":"2024","title":"Sentence Level Analysis Model for Phishing Detection Using KNN","authors":["L Sawe, J Gikandi, J Kamau, D Njuguna"],"snippet":"Phishing emails have experienced a rapid surge in cyber threats globally, especially following the emergence of the COVID-19 pandemic. This form of attack has led to substantial financial losses for numerous organizations. Although various models …","url":["https://www.researchgate.net/profile/Lindah-Sawe/publication/377242106_Sentence_Level_Analysis_Model_for_Phishing_Detection_Using_KNN/links/659d3bd62468df72d305fd90/Sentence-Level-Analysis-Model-for-Phishing-Detection-Using-KNN.pdf"]}
{"year":"2024","title":"Sentiment Analysis and Rating Prediction for App Reviews Using Transformer-based Models","authors":["G ESER, C SAHIN - 2024"],"snippet":"In this study, we present the sentiment analysis of Spotify app reviews, the implementation of Natural Language Processing (NLP) methods, and the use of transformer-based models including BERT, DistilBERT, RoBERTa, and XLM-RoBERTa …","url":["https://www.researchgate.net/profile/Goekberk-Eser/publication/381887825_Sentiment_Analysis_and_Rating_Prediction_for_App_Reviews_Using_Transformer-based_Models/links/6683dc522aa57f3b82663ba8/Sentiment-Analysis-and-Rating-Prediction-for-App-Reviews-Using-Transformer-based-Models.pdf"]}
{"year":"2024","title":"Sentiment Analysis Based on RoBERTa for Amazon Review: An Empirical Study on Decision Making","authors":["X Guo - arXiv preprint arXiv:2411.00796, 2024"],"snippet":"In this study, we leverage state-of-the-art Natural Language Processing (NLP) techniques to perform sentiment analysis on Amazon product reviews. By employing transformer-based models, RoBERTa, we analyze a vast dataset to derive sentiment …","url":["https://arxiv.org/pdf/2411.00796"]}
{"year":"2024","title":"Sentiment Analysis of Low-Resource Yorùbá Tweets Using Fine-Tuned Bert Models","authors":["VT Odumuyiwa, OO Shoyemi, AE Fagoroye - University of Ibadan Journal of Science …, 2024"],"snippet":"Sentiment analysis in low-resource languages poses a notable challenge because of the scarcity of labelled data and language-specific models. This study addresses this challenge of Yorùbá sentiment analysis using fine-tuned variants of Bidirectional …","url":["http://journals.ui.edu.ng/index.php/uijslictr/article/download/1463/1142"]}
{"year":"2024","title":"Sentiment Analysis of Solar Energy in US Cities: A 10-Year Analysis Using Transformer-Based Deep Learning","authors":["S Kim, C Soderman, L Sang - 2024"],"snippet":"This study examines US public sentiment toward solar energy from 2013 to 2022, analyzing 8 million social media posts using RoBERTa, a transformer-based deep learning algorithm. Sentiment has generally been positive but has declined since …","url":["https://www.researchsquare.com/article/rs-5050458/latest.pdf"]}
{"year":"2024","title":"Sentiment analysis on the issue of COVID-19 vaccination using LSTM and fasttext","authors":["WN Dewani, Y Azhar, N Hayatin - AIP Conference Proceedings, 2024"],"snippet":"… The fasttext model is the result of a word vector previously trained from Common Crawl and Indonesian language Wikipedia data from Facebook. This model is trained using the Continuous Bag of Words (CBOW) method with position weight [13] …","url":["https://pubs.aip.org/aip/acp/article/2927/1/060017/3279268"]}
{"year":"2024","title":"Sentiment Triplet Extraction with Multi-view Contrastive Learning","authors":["W Wu, D Wang, M Wang, S Feng, Y Zhang - IEEE Transactions on Affective …, 2024"],"snippet":"… And Common Crawl refers to a dataset obtained from the Common Crawl project, which is a web archive that freely provides a large collection of web page data, here CC25, mC4 and C4 specify a specific version or subset of the Common Crawl data …","url":["https://www.computer.org/csdl/journal/ta/5555/01/10812814/22UpG2nVm5a"]}
{"year":"2024","title":"SENTIMENTAL REFLECTION OF GLOBAL CRISES: CZECH AND UKRAINIAN VIEWS ON POPULAR EVENTS THROUGH THE PRISM OF INTERNET …","authors":["KHZ JOUKL"],"snippet":"Social media have become a part of our lives, and their use helps us learn about events and comment on them with certain emotions. The purpose of our study was to determine the most frequent tone (positive, negative, neutral) of comments on …","url":["https://www.ceeol.com/content-files/document-1324211.pdf"]}
{"year":"2024","title":"Sequence-Level Analysis of Leakage Risk of Training Data in Large Language Models","authors":["T Tiwari, GE Suh - arXiv preprint arXiv:2412.11302, 2024"],"snippet":"… We perform this study on two pre-trained models, LLaMa and OPT, trained on the Common Crawl and Pile respectively. We discover that 1) Extraction rate, the predominant metric used in prior quantification work, underestimates the threat of …","url":["https://arxiv.org/pdf/2412.11302"]}
{"year":"2024","title":"Sequence-to-Sequence Architectures: Encoder-Decoders and Decoders","authors":["PM Nugues - … for Natural Language Processing: Programming with …, 2024"],"snippet":"The transformer consisted originally of two parts: the encoder and the decoder. This chapter describes this complete structure and, to make it concrete, illustrates it with a machine-translation program in PyTorch. For sake of feasibility, we replace the word …","url":["https://link.springer.com/chapter/10.1007/978-3-031-57549-5_17"]}
{"year":"2024","title":"SETEM: Self-ensemble training with Pre-trained Language Models for Entity Matching","authors":["H Ding, C Dai, Y Wu, W Ma, H Zhou - Knowledge-Based Systems, 2024"],"snippet":"… This benchmark is constructed by extracting schema.org data from the Common Crawl and using the following attributes: brand, title, currency and price. The WDC Products benchmark consists of overall nine training, nine validation and nine test …","url":["https://www.sciencedirect.com/science/article/pii/S0950705124003435"]}
{"year":"2024","title":"SHAKTI: A 2.5 Billion Parameter Small Language Model Optimized for Edge AI and Low-Resource Environments","authors":["SAG Shakhadri, K KR, R Aralimatti - arXiv preprint arXiv:2410.11331, 2024"],"snippet":"We introduce Shakti, a 2.5 billion parameter language model specifically optimized for resource-constrained environments such as edge devices, including smartphones, wearables, and IoT systems. Shakti combines high-performance NLP …","url":["https://arxiv.org/pdf/2410.11331"]}
{"year":"2024","title":"Shapley Values-Powered Framework for Fair Reward Split in Content Produced by GenAI","authors":["A Glinsky, A Sokolsky - arXiv preprint arXiv:2403.09700, 2024"],"snippet":"… DATACOMP introduces a new candidate pool of 12.8 billion image-text pairs sourced from Common Crawl, which is broader than the collection in LAION-5B. This extensive pool offers a more diverse base for dataset creation. Unlike LAION-5B …","url":["https://arxiv.org/pdf/2403.09700"]}
{"year":"2024","title":"ShieldGemma: Generative AI Content Moderation Based on Gemma","authors":["W Zeng, Y Liu, R Mullins, L Peran, J Fernandez… - arXiv preprint arXiv …, 2024"],"snippet":"We present ShieldGemma, a comprehensive suite of LLM-based safety content moderation models built upon Gemma2. These models provide robust, state-of-the-art predictions of safety risks across key harm types (sexually explicit, dangerous …","url":["https://arxiv.org/pdf/2407.21772"]}
{"year":"2024","title":"Short-text topic modeling with dual reinforcement from internal and external semantics","authors":["J Wang, L Chen, Z Zhang, J He, X Zhou - International Journal of Machine Learning …, 2024"],"snippet":"… We use a 300 dimensional Common Crawl version for all of the four datasets. For Oscars, we additionally use a 200 dimensional Twitter … Since we use two versions of GloVe word embeddings (ie, Common Crawl version and Twitter version) for the …","url":["https://link.springer.com/article/10.1007/s13042-024-02427-6"]}
{"year":"2024","title":"Should we stay silent on violence? An ensemble approach to detect violent incidents in Spanish social media texts","authors":["D Sharma, V Gupta, VK Singh, D Pinto - Natural Language Processing"],"snippet":"… For training, more than two terabytes of filtered CommonCrawl data was used. The implementation of XLM-RoBERTa includes a preprocessing step, as described earlier. After preprocessing the data, the tweets are tokenized using the XLM-RoBERTa …","url":["https://www.cambridge.org/core/services/aop-cambridge-core/content/view/243DABD3D3CEF992351407B50A69FAAE/S2977042424000256a.pdf/div-class-title-should-we-stay-silent-on-violence-an-ensemble-approach-to-detect-violent-incidents-in-spanish-social-media-texts-div.pdf"]}
{"year":"2024","title":"SIGN LANGUAGE RECOGNITION OF WORDS AND SENTENCE PREDICTION USING LSTM AND NLP","authors":["R GAIKWAD, L ADMUTHE - Journal of Theoretical and Applied Information …, 2024"],"snippet":"… The dataset used for the training of the T5 model is the C4 dataset called as Colossal Clean Crawled Corpus which is collected from Common Crawl, a publicly available web archive. It consists of 750 GB clean English text scraped from the …","url":["http://www.jatit.org/volumes/Vol102No4/20Vol102No4.pdf"]}
{"year":"2024","title":"Silencing the Risk, Not the Whistle: A Semi-automated Text Sanitization Tool for Mitigating the Risk of Whistleblower Re-Identification","authors":["D Staufer, F Pallas, B Berendt - arXiv preprint arXiv:2405.01097, 2024"],"snippet":"Whistleblowing is essential for ensuring transparency and accountability in both public and private sectors. However, (potential) whistleblowers often fear or face retaliation, even when reporting anonymously. The specific content of their …","url":["https://arxiv.org/pdf/2405.01097"]}
{"year":"2024","title":"SimLESS: A Secure Deduplication System over Similar Data in Cloud Media Sharing","authors":["M Song, Z Hua, Y Zheng, T Xiang, X Jia - IEEE Transactions on Information Forensics …, 2024"],"snippet":"With the growing popularity of cloud computing, sharing media data through the cloud has become a common practice. Due to high information redundancy, media data take up a significant amount of storage space. Moreover, similar media data …","url":["https://ieeexplore.ieee.org/abstract/document/10480626/"]}
{"year":"2024","title":"SimLLM: Calculating Semantic Similarity in Code Summaries using a Large Language Model-Based Approach","authors":["X Jin, Z Lin - Proceedings of the ACM on Software Engineering, 2024"],"snippet":"Code summaries are pivotal in software engineering, serving to improve code readability, maintainability, and collaboration. While recent advancements in Large Language Models (LLMs) have opened new avenues for automatic code …","url":["https://dl.acm.org/doi/pdf/10.1145/3660769"]}
{"year":"2024","title":"Simple and Scalable Strategies to Continually Pre-train Large Language Models","authors":["A Ibrahim, B Thérien, K Gupta, ML Richter, Q Anthony… - arXiv preprint arXiv …, 2024"],"snippet":"… We then generate a fixed token-length response for each of the models trained German Common Crawl. As a baseline, we also evaluate … of German-language outputs from the models trained on German Common Crawl when compared to the …","url":["https://arxiv.org/pdf/2403.08763"]}
{"year":"2024","title":"Simulating Policy Impacts: Developing a Generative Scenario Writing Method to Evaluate the Perceived Effects of Regulation","authors":["J Barnett, K Kieslich, N Diakopoulos - arXiv preprint arXiv:2405.09679, 2024"],"snippet":"… They utilize proprietary datasets as well as opensource web data such as the continuously growing Common Crawl, which contains more than 250 billion pages of over a decade’s worth of textual content. While these models primarily learn how …","url":["https://arxiv.org/pdf/2405.09679"]}
{"year":"2024","title":"Simulating Subjects: The Promise and Peril of AI Stand-ins for Social Agents and Interactions","authors":["AC Kozlowski, JA Evans"],"snippet":"Large Language Models (LLMs), through their exposure to massive collections of online text, learn to reproduce the perspectives and linguistic styles of diverse social and cultural groups. This capability suggests a powerful social scientific application–the …","url":["https://files.osf.io/v1/resources/vp3j2/providers/osfstorage/66df759cf0c5422fed1eaeae?action=download&direct&version=2"]}
{"year":"2024","title":"Single Cells Are Biological Tokens: Towards Cell Language Models","authors":["H Wen - 2024"],"snippet":"The rapid advancement of single-cell technologies allows for simultaneous measurement of multiple molecular features within individual cells, providing unprecedented multimodal data through single-cell multi-omics and spatial omics …","url":["https://search.proquest.com/openview/4a8bb7008693c584334f0ac855eae486/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
{"year":"2024","title":"Single Layer Single Gradient Unlearning","authors":["Z Cai, Y Tan, MS Asif - arXiv preprint arXiv:2407.11867, 2024"],"snippet":"… Large-scale web scrapers, such as Common Crawl, archive billions of webpages monthly, providing massive data sources to train such revolutionary AI models. While these large unsupervised datasets significantly enhance performance under …","url":["https://arxiv.org/pdf/2407.11867"]}
{"year":"2024","title":"Single Parent Family: A Spectrum of Family Members from a Single Pre-Trained Foundation Model","authors":["H Hajimolahoseini, M Hassanpour, F Ataiefard, B Chen… - arXiv preprint arXiv …, 2024"],"snippet":"This paper introduces a novel method of Progressive Low Rank Decomposition (PLRD) tailored for the compression of large language models. Our approach leverages a pre-trained model, which is then incrementally decompressed to smaller sizes using …","url":["https://arxiv.org/pdf/2406.19995"]}
{"year":"2024","title":"SiTSE: Sinhala Text Simplification Dataset and Evaluation","authors":["S Ranathunga, R Sirithunga, H Rathnayake, L De Silva… - arXiv preprint arXiv …, 2024"],"snippet":"Text Simplification is a task that has been minimally explored for low-resource languages. Consequently, there are only a few manually curated datasets. In this paper, we present a human curated sentence-level text simplification dataset for the …","url":["https://arxiv.org/pdf/2412.01293"]}
{"year":"2024","title":"Sketch Grammar for Japanese","authors":["J ROHÁČEK"],"snippet":"Sketch Grammar is a formalism used to extract frequent word collocations from text corpora. This thesis aims at analyzing the current sketch grammar for Japanese used in the Sketch Engine corpus manager and implementing a new version with …","url":["https://is.muni.cz/th/edx6h/thesis_Archive.pdf"]}
{"year":"2024","title":"SkillMatch: Evaluating Self-supervised Learning of Skill Relatedness","authors":["JJ Decorte, J Van Hautte, T Demeester, C Develder - arXiv preprint arXiv:2410.05006, 2024"],"snippet":"… For the generic fastText vectors, we use cc.en.300.bin, a 300-dimensional vector model trained on Common Crawl and Wikipedia [4]. To train their domain-specific versions, we use a dataset of 755k job ads, also from 2024. Note that these are not included …","url":["https://arxiv.org/pdf/2410.05006"]}
{"year":"2024","title":"SlamaTrain–Representative Training Dataset for Slavonic Large Language Models","authors":["M Medveď, R Sabol, A Horák"],"snippet":"… However, most of the largest collections are based on Common Crawl [12] that, naturally reflecting the proportions of texts available on-line, are imbalanced in favor of English and … Patel, JM: Introduction to Common Crawl Datasets, pp. 277–324 …","url":["https://www.sketchengine.eu/wp-content/uploads/SlamaTrain%E2%80%93-Representative-Training-Dataset-for-Slavonic-Large-Language-Models-25_33.pdf"]}
{"year":"2024","title":"Slight Corruption in Pre-training Data Makes Better Diffusion Models","authors":["H Chen, Y Han, D Misra, X Li, K Hu, D Zou… - arXiv preprint arXiv …, 2024"],"snippet":"… For example, Stable Diffusion [26] was pre-trained on LAION-2B [17], which contains billion-scale image-text pairs collected from Common Crawl [27]. Despite the heavy filtering mechanisms used in collecting pre-training datasets [17, 28], they …","url":["https://arxiv.org/pdf/2405.20494"]}
{"year":"2024","title":"Slovak morphological tokenizer using the Byte-Pair Encoding algorithm","authors":["D Držík, F Forgac - PeerJ Computer Science, 2024"],"snippet":"This study introduces a new approach to text tokenization, SlovaK Morphological Tokenizer (SKMT), which integrates the morphology of the Slovak language into the training process using the Byte-Pair Encoding (BPE) algorithm. Unlike conventional …","url":["https://peerj.com/articles/cs-2465/"]}
{"year":"2024","title":"Small Language Models and Large Language Models in Oppositional thinking analysis: Capabilities and Biases and Challenges","authors":["Á Huertas-García, C Martí-González, J Muñoz… - Working Notes of CLEF, 2024"],"snippet":"The proliferation of misinformation and conspiracy theories needs robust methods to differentiate legitimate critical discourse from harmful conspiratorial narratives. This study investigates discerning critical messages from conspiracy theories within …","url":["https://ceur-ws.org/Vol-3740/paper-248.pdf"]}
{"year":"2024","title":"Small Language Models for Emotion Recognition in Polish Stock Market Investor Opinions","authors":["B Koptyra, M Oleksy, E Dziecioł, J Kocon"],"snippet":"In this paper, we explore the application of small language models for emotion recognition in Polish stock market investor opinions. Emotion recognition has been shown to enhance stock price prediction models by providing meaningful text …","url":["https://sentic.net/sentire2024koptyra.pdf"]}
{"year":"2024","title":"Small Language Models: Survey, Measurements, and Insights","authors":["Z Lu, X Li, D Cai, R Yi, F Liu, X Zhang, ND Lane, M Xu - arXiv preprint arXiv …, 2024"],"snippet":"… • RedPajama [21] (1.2T tokens): includes over 100B text documents coming from 84 CommonCrawl snapshots and processed using the … • DCLM-baseline [39] (1.35T tokens): a standardized corpus extracted from Common Crawl, effective pretraining …","url":["https://arxiv.org/pdf/2409.15790"]}
{"year":"2024","title":"Small Models, Big Insights: Leveraging Slim Proxy Models To Decide When and What to Retrieve for LLMs","authors":["J Tan, Z Dou, Y Zhu, P Guo, K Fang, JR Wen - arXiv preprint arXiv:2402.12052, 2024"],"snippet":"The integration of large language models (LLMs) and search engines represents a significant evolution in knowledge acquisition methodologies. However, determining the knowledge that an LLM already possesses and the knowledge that requires the …","url":["https://arxiv.org/pdf/2402.12052"]}
{"year":"2024","title":"Smaller Can Be Better: Efficient Data Selection for Pre-training Models","authors":["G Fang, S Wang, M Wang, Y Yang, H Huang - Asia-Pacific Web (APWeb) and Web …, 2024"],"snippet":"To reduce the resource consumption for pre-training models on large-scale corpora, existing research has primarily focused on refining network architectures and training methods. Nevertheless, the concomitant cost tends to be expensive. This …","url":["https://link.springer.com/chapter/10.1007/978-981-97-7232-2_22"]}
{"year":"2024","title":"Smaller Language Models are Better Zero-shot Machine-Generated Text Detectors","authors":["N Mireshghallah, J Mattern, S Gao, R Shokri… - Proceedings of the 18th …, 2024"],"snippet":"As large language models are becoming more embedded in different user-facing services, it is important to be able to distinguish between human-written and machine-generated text to verify the authenticity of news articles, product reviews, etc. Thus, in this paper …","url":["https://aclanthology.org/2024.eacl-short.25.pdf"]}
{"year":"2024","title":"Smart Automation Using LLM","authors":["P Ethape, R Kane, G Gadekar, S Chimane - International Research Journal of …, 2023"],"snippet":"… Such large-scale models can ingest massive amounts of data, often from the internet, but also from sources such as the Common Crawl, which comprises more than 50 billion web pages, and Wikipedia, which has approximately 57 million pages. …","url":["https://search.proquest.com/openview/1c46974bac0d8d641a04a889011c8299/1?pq-origsite=gscholar&cbl=5314840"]}
{"year":"2024","title":"Smart Bilingual Focused Crawling of Parallel Documents","authors":["C García-Romero, M Esplà-Gomis, F Sánchez-Martínez - arXiv preprint arXiv …, 2024"],"snippet":"Crawling parallel texts $\\unicode{x2014}$texts that are mutual translations$\\unicode{x2014}$ from the Internet is usually done following a brute-force approach: documents are massively downloaded in an unguided process, and only a fraction of them end up …","url":["https://arxiv.org/pdf/2405.14779"]}
{"year":"2024","title":"Smart Shields against Cyber Threats: Machine Learning-Driven Phishing URL Detection","authors":["SA Karim, MJ Islam, IH Farabi - 2024"],"snippet":"Phishing attacks remain a prevalent cybersecurity threat, exploiting vulnerabilities in digital platforms to compromise sensitive user data. This paper introduces a novel machine learning-based framework for phishing URL detection, combining …","url":["https://www.researchgate.net/profile/Md-Islam-2394/publication/387060278_Smart_Shields_against_Cyber_Threats_Machine_Learning-Driven_Phishing_URL_Detection/links/675df174ebc8f97970307849/Smart-Shields-against-Cyber-Threats-Machine-Learning-Driven-Phishing-URL-Detection.pdf"]}
{"year":"2024","title":"SmartPretrain: Model-Agnostic and Dataset-Agnostic Representation Learning for Motion Prediction","authors":["Y Zhou, H Shao, L Wang, SL Waslander, H Li, Y Liu - arXiv preprint arXiv:2410.08669, 2024"],"snippet":"Predicting the future motion of surrounding agents is essential for autonomous vehicles (AVs) to operate safely in dynamic, human-robot-mixed environments. However, the scarcity of large-scale driving datasets has hindered the development …","url":["https://arxiv.org/pdf/2410.08669"]}
{"year":"2024","title":"SMMF: Square-Matricized Momentum Factorization for Memory-Efficient Optimization","authors":["K Park, S Lee - arXiv preprint arXiv:2412.08894, 2024"],"snippet":"We propose SMMF (Square-Matricized Momentum Factorization), a memory-efficient optimizer that reduces the memory requirement of the widely used adaptive learning rate optimizers, such as Adam, by up to 96%. SMMF enables flexible and efficient …","url":["https://arxiv.org/pdf/2412.08894"]}
{"year":"2024","title":"Smoky Quartz: A Transparent Bilingual Large Language Model","authors":["Q Huang, C Zhang, M Tao, J Lin, S Huang, Y Feng"],"snippet":"Recent advancements in large-scale models have been remarkable; however, a significant challenge persists in their lack of transparency, particularly concerning the training data utilized. This obscurity raises concerns about potential data leaks …","url":["https://andrewzhe.github.io/figs/A_Transparent_Binlingual_LLM.pdf"]}
{"year":"2024","title":"SMW Cloud: A Corpus of Domain-Specific Knowledge Graphs from Semantic MediaWikis","authors":["D Dobriy, M Beno, A Polleres"],"snippet":"Semantic wikis have become an increasingly popular means of collaboratively managing Knowledge Graphs. They are powered by platforms such as Semantic MediaWiki and Wikibase, both of which enable MediaWiki to store and publish …","url":["https://2024.eswc-conferences.org/wp-content/uploads/2024/04/146640477.pdf"]}
{"year":"2024","title":"Social Evolution of Published Text and The Emergence of Artificial Intelligence Through Large Language Models and The Problem of Toxicity and Bias","authors":["A Khan, P Saravanan, SK Venkatesan - arXiv preprint arXiv:2402.07166, 2024"],"snippet":"We provide a birds eye view of the rapid developments in AI and Deep Learning that has led to the path-breaking emergence of AI in Large Language Models. The aim of this study is to place all these developments in a pragmatic broader historical social …","url":["https://arxiv.org/pdf/2402.07166"]}
{"year":"2024","title":"Social Media Sentiment Analysis on Multilingual Dataset","authors":["SY Chou - 2024"],"snippet":"This thesis presents using unlabeled data and soft targets from a LLM to train a pre-trained model for sentiment analysis. Inspired by the study “What do LLMs Know about Financial Markets? A Case Study on Reddit Market Sentiment Analysis” by Deng et …","url":["https://www.diva-portal.org/smash/get/diva2:1888601/FULLTEXT01.pdf"]}
{"year":"2024","title":"SocialQuotes: Learning Contextual Roles of Social Media Quotes on the Web","authors":["J Palowitch, H Alvari, M Kazemi, T Amin, F Radlinski - arXiv preprint arXiv …, 2024"],"snippet":"… We build and release SocialQuotes1, a data set computed from the Common Crawl with over 32M social media quotes, accompanied by role labels for 8.3k quotes obtained from human annotators. 3. We validate our main hypothesis with …","url":["https://arxiv.org/pdf/2407.16007"]}
{"year":"2024","title":"Sociolinguistically Informed Interpretability: A Case Study on Hinglish Emotion Classification","authors":["K Tatariya, H Lent, J Bjerva, M de Lhoneux - arXiv preprint arXiv:2402.03137, 2024"],"snippet":"Emotion classification is a challenging task in NLP due to the inherent idiosyncratic and subjective nature of linguistic expression, especially with code-mixed data. Pre-trained language models (PLMs) have achieved high performance for many tasks and …","url":["https://arxiv.org/pdf/2402.03137"]}
{"year":"2024","title":"SoftDedup: an Efficient Data Reweighting Method for Speeding Up Language Model Pre-training","authors":["N He, W Xiong, H Liu, Y Liao, L Ding, K Zhang, G Tang… - arXiv preprint arXiv …, 2024"],"snippet":"… In summary, our experiments on the RedPajama CommonCrawl dataset substantiate that the soft deduplication method is capable of reducing perplexity and enhancing the accuracy of downstream tasks more efficiently compared to the …","url":["https://arxiv.org/pdf/2407.06654"]}
{"year":"2024","title":"SoK: SSO-MONITOR—The Current State and Future Research Directions in Single Sign-On Security Measurements","authors":["L Jannett, M Westers, T Wich, C Mainka, A Mayer…"],"snippet":"Single Sign-On (SSO) with OAuth 2.0 and OpenID Connect 1.0 is essential for user authentication and authorization on the Internet. Billions of users rely on SSO services provided by Google, Facebook, and Apple. For large-scale measurements …","url":["https://nerd2.nrw/wp-content/uploads/2024/05/sso-monitor.pdf"]}
{"year":"2024","title":"Some Considerations for the Preservation of Endangered Languages Using Low-Resource Machine Translation","authors":["A Kho, DS Pham, S Soon, KY Chan - Australasian Joint Conference on Artificial …, 2024"],"snippet":"While widespread languages remain actively prevalent in digital mediums, endangered languages such as Indigenous Australian languages, are often scarce in textual resources and lack a substantial digital presence. This diminishes the …","url":["https://link.springer.com/chapter/10.1007/978-981-96-0348-0_10"]}
{"year":"2024","title":"Somesite I Used To Crawl: Awareness, Agency and Efficacy in Protecting Content Creators From AI Crawlers","authors":["E Liu, E Luo, S Shan, GM Voelker, BY Zhao, S Savage - arXiv preprint arXiv …, 2024"],"snippet":"… We used the robots.txt files crawled by the Common Crawl from 2022 to 2024. We find that the coverage of the Common Crawl robots.txt data is approximately 83%. Ultimately, for sites that did not return a 200 or 404 HTTP status code to Common …","url":["https://arxiv.org/pdf/2411.15091"]}
{"year":"2024","title":"Sonnet or Not, Bot? Poetry Evaluation for Large Models and Datasets","authors":["M Walsh, A Preus, M Antoniak - arXiv preprint arXiv:2406.18906, 2024"],"snippet":"… About 30% of our poems are found in the Common Crawl data included in Dolma, with the C4 dataset close behind. Wikipedia and Semantic Scholar contain the fewest detected poems. Overall, if at least one line from a poem is detected, it is …","url":["https://arxiv.org/pdf/2406.18906"]}
{"year":"2024","title":"Sourceformer: Tool Integration into Transformer Large Language Models Through Source Code","authors":["E Richmond, N Herndon"],"snippet":"LLMs have been shown to use tools well. By allowing specific tools to increase the capabilities that LLMs struggle with, these models can become much more useful. Previous works use handcrafted examples of simple tool use during self-training …","url":["https://elir.net/static/sourceformer.pdf"]}
{"year":"2024","title":"Spanning the Spectrum of Hatred Detection: A Persian Multi-Label Hate Speech Dataset with Annotator Rationales","authors":["Z Delbari, NS Moosavi, MT Pilehvar - Proceedings of the AAAI Conference on …, 2024"],"snippet":"With the alarming rise of hate speech in online communities, the demand for effective NLP models to identify instances of offensive language has reached a critical point. However, the development of such models heavily relies on the …","url":["https://ojs.aaai.org/index.php/AAAI/article/view/29743/31279"]}
{"year":"2024","title":"Sparsing Law: Towards Large Language Models with Greater Activation Sparsity","authors":["Y Luo, C Song, X Han, Y Chen, C Xiao, Z Liu, M Sun - arXiv preprint arXiv …, 2024"],"snippet":"Activation sparsity denotes the existence of substantial weakly-contributed elements within activation outputs that can be eliminated, benefiting many important applications concerned with large language models (LLMs). Although promoting …","url":["https://arxiv.org/pdf/2411.02335"]}
{"year":"2024","title":"Spatial Language Understanding: Deep Learning, Reasoning, and Evaluation","authors":["RM Mazrae - 2024"],"snippet":"… Pretrained language models (PLM) are large neural network models that have been trained on vast amounts of text data such as the entire text of Wikipedia or the Common Crawl web corpus in a un/supervised way. These models use transformers …","url":["https://search.proquest.com/openview/cc3bd0ab4bf604e29ca3f08c777c0969/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
{"year":"2024","title":"Speaker independent recognition of low-resourced multilingual Arabic spoken words through hybrid fusion","authors":["S Mehra, V Ranga, R Agarwal, S Susan - Multimedia Tools and Applications, 2024"],"snippet":"This article introduces a supervised strategy designed to enhance spoken word recognition within the constraints of a resource-limited multilingual dataset, specifically focusing on the Arabic language. Notably, existing methodologies often …","url":["https://link.springer.com/article/10.1007/s11042-024-18804-w"]}
{"year":"2024","title":"Speaker Intimacy Estimation in Chat-Talks Based on Verbal and Non-Verbal Information","authors":["Y Chiba, A Ito - IEEE Access, 2024"],"snippet":"Conversations based on mutual intimacy are critical for maintaining positive relationships. A detailed understanding of speaker relationships in dialogues enhances various applications, such as information recommendation systems. Such …","url":["https://ieeexplore.ieee.org/iel8/6287639/6514899/10770211.pdf"]}
{"year":"2024","title":"Specialising and Analysing Instruction-Tuned and Byte-Level Language Models for Organic Reaction Prediction","authors":["J Pang, I Vulić - arXiv preprint arXiv:2405.10625, 2024"],"snippet":"Transformer-based encoder-decoder models have demonstrated impressive results in chemical reaction prediction tasks. However, these models typically rely on pretraining using tens of millions of unlabelled molecules, which can be time-consuming …","url":["https://arxiv.org/pdf/2405.10625"]}
{"year":"2024","title":"Specialized Language Models with Cheap Inference from Limited Domain Data","authors":["D Grangier, A Katharopoulos, P Ablin, A Hannun - arXiv preprint arXiv:2402.01093, 2024"],"snippet":"Large language models have emerged as a versatile tool but are challenging to apply to tasks lacking large inference budgets and large in-domain training sets. This work formalizes these constraints and distinguishes four important variables …","url":["https://arxiv.org/pdf/2402.01093"]}
{"year":"2024","title":"Spectra: A Comprehensive Study of Ternary, Quantized, and FP16 Language Models","authors":["A Kaushal, T Pandey, T Vaidhya, A Bhagat, I Rish - arXiv preprint arXiv:2407.12327, 2024"],"snippet":"Post-training quantization is the leading method for addressing memory-related bottlenecks in LLM inference, but unfortunately, it suffers from significant performance degradation below 4-bit precision. An alternative approach involves …","url":["https://arxiv.org/pdf/2407.12327"]}
{"year":"2024","title":"Speculative Enquiries: The third annual conference of the European Culture and Technology Laboratory.","authors":["C Vaughan, M Koutsomichalis - 2024"],"snippet":"… The collective work of our writing is published on the internet through Common Crawl, for example, which contributes substantially to its corpus. But interestingly, most of the generative Large Language Models like ChatGPT and Gemini demur …","url":["https://arrow.tudublin.ie/cgi/viewcontent.cgi?article=1006&context=eutpressbooks"]}
{"year":"2024","title":"SPHINX-X: Scaling Data and Parameters for a Family of Multi-modal Large Language Models","authors":["D Liu, R Zhang, L Qiu, S Huang, W Lin, S Zhao, S Geng… - Forty-first International Conference …","P Gao, R Zhang, C Liu, L Qiu, S Huang, W Lin, S Zhao… - arXiv preprint arXiv …, 2024"],"snippet":"… Specifically, we first collect large-scale PDF datasets from Common Crawl 1 and arXiv websites. Then, we utilize PyMuPDF 2 to get the rendering results of each page in the PDF file and also save all the text annotations along with their bounding …","url":["https://arxiv.org/pdf/2402.05935","https://openreview.net/pdf?id=tDMlQkJRhZ"]}
{"year":"2024","title":"Spike No More: Stabilizing the Pre-training of Large Language Models","authors":["S Takase, S Kiyono, S Kobayashi, J Suzuki - arXiv preprint arXiv:2312.16903, 2023"],"snippet":"… 2020) that consists of clean English texts extracted from Common Crawl7 as our LLM pre-training corpus. We also used the separated part of C4 as our validation data. We used GPT-2 vocabulary (Radford et al.… https://commoncrawl.org/ …","url":["https://arxiv.org/pdf/2312.16903"]}
{"year":"2024","title":"SPML: A DSL for Defending Language Models Against Prompt Attacks","authors":["RK Sharma, V Gupta, D Grossman - arXiv preprint arXiv:2402.11755, 2024"],"snippet":"… The pre-training data included trillions of tokens sourced from publicly available datasets, such as Common Crawl, Wikipedia, and public domain books from Project Gutenberg. We use the versions with 7 billion and 13 billion parameters, available …","url":["https://arxiv.org/pdf/2402.11755"]}
{"year":"2024","title":"Sports, crisis, and social media: a Twitter-based exploration of the Tokyo Olympics in the COVID-19 era","authors":["V Mehra, P Singh, S Bharany, RS Sawhney - Social Network Analysis and Mining, 2024"],"snippet":"The global landscape underwent a transformative shift due to the unexpected arrival of the COVID-19 pandemic, disrupting various aspects of life, including the staging of sports events. Notably, the Tokyo Olympics, a renowned international sports …","url":["https://link.springer.com/article/10.1007/s13278-024-01218-9"]}
{"year":"2024","title":"Spotting LLMs With Binoculars: Zero-Shot Detection of Machine-Generated Text","authors":["A Hans, A Schwarzschild, V Cherepanova, H Kazemi… - arXiv preprint arXiv …, 2024"],"snippet":"… When evaluating Binoculars on samples from languages that are not well represented in Common Crawl data (standard LLM pretraining data), we find that false-positives rates remain low, which is highly desirable from a harm reduction …","url":["https://arxiv.org/pdf/2401.12070"]}
{"year":"2024","title":"SRBerta—A Transformer Language Model for Serbian Cyrillic Legal Texts","authors":["M Bogdanović, J Kocić, L Stoimenov - Information, 2024"],"snippet":"… CommonCrawl [5] is a collection of texts whose size is measured in petabytes. This collection was … , CommonCrawl contains texts of lower quality, so development teams often resorted to processing texts before training and extracting …","url":["https://www.mdpi.com/2078-2489/15/2/74"]}
{"year":"2024","title":"Stacking Your Transformers: A Closer Look at Model Growth for Efficient LLM Pre-Training","authors":["W Du, T Luo, Z Qiu, Z Huang, Y Shen, R Cheng, Y Guo… - arXiv preprint arXiv …, 2024"],"snippet":"LLMs are computationally expensive to pre-train due to their large scale. Model growth emerges as a promising approach by leveraging smaller models to accelerate the training of larger ones. However, the viability of these model growth …","url":["https://arxiv.org/pdf/2405.15319"]}
{"year":"2024","title":"Stage-1 Report: Everything everywhere all at once? Exploring the richness of visual experience beyond words","authors":["L Qianchen, M Yamada, Y Aizawa, N Tsuchiya"],"snippet":"In consciousness research, understanding the nature and mechanism of visual experience has been one of the most debated topics. For humans, vision is arguably the primary sensory modality to understand the environment (Cole & Balcetis, 2021) …","url":["https://osf.io/2z85g/download"]}
{"year":"2024","title":"StarCoder 2 and The Stack v2: The Next Generation","authors":["A Lozhkov, R Li, LB Allal, F Cassano, J Lamy-Poirier… - arXiv preprint arXiv …, 2024"],"snippet":"The BigCode project, an open-scientific collaboration focused on the responsible development of Large Language Models for Code (Code LLMs), introduces StarCoder2. In partnership with Software Heritage (SWH), we build The Stack v2 on …","url":["https://arxiv.org/pdf/2402.19173"]}
{"year":"2024","title":"Stars, Stripes, and Silicon: Unravelling the ChatGPT's All-American, Monochrome, Cis-centric Bias","authors":["F Torrielli - arXiv preprint arXiv:2410.13868, 2024"],"snippet":"This paper investigates the challenges associated with bias, toxicity, unreliability, and lack of robustness in large language models (LLMs) such as ChatGPT. It emphasizes that these issues primarily stem from the quality and diversity of data on …","url":["https://arxiv.org/pdf/2410.13868"]}
{"year":"2024","title":"State of NLP in Kenya: A Survey","authors":["CJ Amol, EA Chimoto, RD Gesicho, AM Gitau, NA Etori… - arXiv preprint arXiv …, 2024"],"snippet":"Kenya, known for its linguistic diversity, faces unique challenges and promising opportunities in advancing Natural Language Processing (NLP) technologies, particularly for its underrepresented indigenous languages. This survey provides a …","url":["https://arxiv.org/pdf/2410.09948"]}
{"year":"2024","title":"State of Title IX: A Knowledge Base for Title IX Documentation","authors":["P Sharma - 2024"],"snippet":"Knowledge bases play a vital role in the modern world, offering a systematic and structured approach to integrate various entities, concepts, rules, and relationships associated with real-world information. In this study, we aggregated the official Title …","url":["https://escholarship.org/content/qt4m26w5xn/qt4m26w5xn_noSplash_79a0bfb4e1e4ff8800a61976451ffc95.pdf"]}
{"year":"2024","title":"Statistical dataset evaluation: A case study on named entity recognition","authors":["C Wang, Q Dong, X Wang, Z Sui - Natural Language Processing"],"snippet":"Datasets serve as crucial training resources and model performance trackers. However, existing datasets have exposed a plethora of problems, inducing biased models and unreliable evaluation results. In this paper, we propose a model-agnostic …","url":["https://www.cambridge.org/core/services/aop-cambridge-core/content/view/BF7FA3EF95004830F233CF5D743D98B2/S2977042424000372a.pdf/statistical-dataset-evaluation-a-case-study-on-named-entity-recognition.pdf"]}
{"year":"2024","title":"Steward: Natural Language Web Automation","authors":["B Tang, KG Shin - arXiv preprint arXiv:2409.15441, 2024"],"snippet":"… They subsequently created WebAgent [17], another HTMLT5 type language model combined with a Flan-U-PaLM [8] program synthesis model trained on CommonCrawl [3] HTML and web interaction data. Their specially trained 540B parameter …","url":["https://arxiv.org/pdf/2409.15441"]}
{"year":"2024","title":"STFL: Utilizing a Semi-Supervised, Transfer-Learning, Federated-Learning Approach to Detect Phishing URL Attacks","authors":["I Sakazi, E Grolman, Y Elovici, A Shabtai - 2024 International Joint Conference on …, 2024"],"snippet":"Phishing attacks are continually changing, so machine learning detection models must be continuously updated by collecting new URL data from users without compromising their privacy. Existing approaches for the detection of phishing URLs …","url":["https://ieeexplore.ieee.org/abstract/document/10650184/"]}
{"year":"2024","title":"Stochastic Remembering and Distributed Mnemonic Agency: Recalling Twentieth Century Activists with ChatGPT","authors":["R Smit, T Smits, S Merrill - Memory Studies Review, 2024"],"snippet":"This paper introduces the concept of stochastic remembering and uses two prompt engineering techniques to critically examine the text generated by ai chatbots. These techniques–step-by-step prompting and chain of thought reasoning–are then …","url":["https://brill.com/view/journals/mesr/aop/article-10.1163-29498902-202400015/article-10.1163-29498902-202400015.xml"]}
{"year":"2024","title":"Strategies for Corpus Development for Low‐Resource Languages: Insights from Nepal","authors":["BK Bal, B Prasain, RR Ghimire, P Acharya - Automatic Speech Recognition and …, 2024"],"snippet":"… 25 whereas the monolingual dataset were derived from Wikipedia and Common Crawl for languages under consideration. They also experimented with four variations of training settings: fully supervised, fully unsupervised, semisupervised …","url":["https://onlinelibrary.wiley.com/doi/abs/10.1002/9781394214624.ch15"]}
{"year":"2024","title":"Stratified Graph Indexing for E cient Search in Deep Descriptor Databases","authors":["MMM Rahman, J Tešić"],"snippet":"Searching for unseen objects in extensive visual archives is challenging, demanding efficient indexing methods that can support meaningful similarity retrievals. This research paper presents the Stratified Graph (SG) approach for …","url":["https://assets-eu.researchsquare.com/files/rs-3755685/v1_covered_f45aeee7-a4a1-4495-a934-9a6ef6256e8e.pdf"]}
{"year":"2024","title":"Strengthening the WiC: New Polysemy Dataset in Hindi and Lack of Cross Lingual Transfer","authors":["H Dubossarsky, F Dairkee - Proceedings of the 2024 Joint International Conference …, 2024"],"snippet":"… TB of filtered CommonCrawl data as opposed to mBERT which was trained on Wikipedia data, and reported to outperform mBERT in a variety of cross-lingual benchmarks like XNLI, MLQA and NER. HindiBERT is a monolingual model trained …","url":["https://aclanthology.org/2024.lrec-main.1332.pdf"]}
{"year":"2024","title":"Structured Packing in LLM Training Improves Long Context Utilization","authors":["K Staniszewski, S Tworkowski, S Jaszczur… - arXiv preprint arXiv …, 2023"],"snippet":"Recent advances in long-context Large Language Models (LCLMs) have generated significant interest, especially in applications such as querying scientific research papers. However, their potential is often limited by inadequate context utilization. We …","url":["https://arxiv.org/pdf/2312.17296"]}
{"year":"2024","title":"Studies in conversational AI: multilingual capabilities, world knowledge, and evaluation strategies","authors":["M De Bruyn - 2024"],"snippet":"This thesis studies the evolving landscape of conversational AI. The main research objective is to improve the conversational abilities of conversational agents, with a focus on integrating real-time knowledge and expanding multilingual capabil-ities …","url":["https://repository.uantwerpen.be/docstore/d:irua:21301"]}
{"year":"2024","title":"Studying Peer Effects in Divergent Thinking: Theory and Method","authors":["CH Wong, I Juvina, PS Popescu"],"snippet":"In designing technology that supports user learning, an important first step is to understand how interactions among humans shape mutual learning. Much qualitative research in the realm of peer-assisted learning (PAL) has advanced the …","url":["https://rochi.utcluj.ro/articole/11/RoCHI2023-Wong.pdf"]}
{"year":"2024","title":"Stuffed Mamba: State Collapse and State Capacity of RNN-Based Long-Context Modeling","authors":["Y Chen, X Zhang, S Hu, X Han, Z Liu, M Sun - arXiv preprint arXiv:2410.07145, 2024"],"snippet":"… Data We start from RedPajama-V2 (Computer, 2023), an open dataset with 30T tokens extracted from CommonCrawl4, and we perform deduplication to ensure data quality. During evaluation, we sample documents longer than 16K tokens and …","url":["https://arxiv.org/pdf/2410.07145"]}
{"year":"2024","title":"SUBLLM: A Novel Efficient Architecture with Token Sequence Subsampling for LLM","authors":["Q Wang, Y Yuan, X Yang, R Zhang, K Zhao, W Liu… - arXiv preprint arXiv …, 2024"],"snippet":"While Large Language Models (LLMs) have achieved remarkable success in various fields, the efficiency of training and inference remains a major challenge. To address this issue, we propose SUBLLM, short for Subsampling-Upsampling-Bypass …","url":["https://arxiv.org/pdf/2406.06571"]}
{"year":"2024","title":"Super donors and super recipients: Studying cross-lingual transfer between high-resource and low-resource languages","authors":["VPESE Voloshina, T Shavrina, A Panchenko"],"snippet":"Despite the increasing popularity of multilingualism within the NLP community, numerous languages continue to be underrepresented due to the lack of available resources. Our work addresses this gap by introducing experiments on cross-lingual …","url":["https://aclanthology.org/2024.loresmt-1.10.pdf?utm_referrer=https%3A%2F%2Fdzen.ru%2Fmedia%2Fid%2F654b8c1170ee9a5893b37f67%2F66dd313b3957cd360b98680e"]}
{"year":"2024","title":"Supervised Learning","authors":["ER Vankov, K Gadhoumi - Statistical Methods in Epilepsy, 2024"],"snippet":"… A corpus such as Common Crawl, which contains roughly 840 billion tokens of over two million unique words, provides such scale. There are other corpora used in these unsupervised processes, one such common candidate being a collection of all …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=Khj5EAAAQBAJ&oi=fnd&pg=PT331&dq=commoncrawl&ots=zkHFEaxxbb&sig=j_lgK0J9A3vlHt3tIE3yX5TTAK8"]}
{"year":"2024","title":"SuRe: Summarizing Retrievals using Answer Candidates for Open-domain QA of LLMs","authors":["J Kim, J Nam, S Mo, J Park, SW Lee, M Seo, JW Ha… - arXiv preprint arXiv …, 2024"],"snippet":"Large language models (LLMs) have made significant advancements in various natural language processing tasks, including question answering (QA) tasks. While incorporating new information with the retrieval of relevant passages is a promising …","url":["https://arxiv.org/pdf/2404.13081"]}
{"year":"2024","title":"Surface Aesthetics: The Secret Formula of Prompting","authors":["MT De Rosa Palmini, LJ Wagner - 2024"],"snippet":"… OpenPageRank is a website ranking metrics system that draws on open source data provided by Common Crawl and Common Search. While there are many indicators to rank a website popularity, the page rank calculated by OpenPageRank …","url":["https://cos.bibl.th-koeln.de/files/1268/DeRosaPalminiWagner2024-rrrreflect.pdf"]}
{"year":"2024","title":"Surfacing Text Changes in Archived Webpages","authors":["L Frew - 2024"],"snippet":"… Common Crawl datasets started in 2008, and are collected monthly at the present time. The most recent Common Crawl from July 2024 contains 2.5 billion webpages. Large datasets, like ClueWeb and CommonCrawl, crawl at different points in time …","url":["https://digitalcommons.odu.edu/cgi/viewcontent.cgi?article=1181&context=computerscience_etds"]}
{"year":"2024","title":"Suri: Multi-constraint Instruction Following for Long-form Text Generation","authors":["CM Pham, S Sun, M Iyyer - arXiv preprint arXiv:2406.19371, 2024"],"snippet":"Existing research on instruction following largely focuses on tasks with simple instructions and short responses. In this work, we explore multi-constraint instruction following for generating long-form text. We create Suri, a dataset with 20K human-written …","url":["https://arxiv.org/pdf/2406.19371"]}
{"year":"2024","title":"Survey of Cultural Awareness in Language Models: Text and Beyond","authors":["S Pawar, J Park, J Jin, A Arora, J Myung, S Yadav…"],"snippet":"Large-scale deployment of large language models (LLMs) in various applications, such as chatbots and virtual assistants, requires LLMs to be culturally sensitive to the user to ensure inclusivity. Culture has been widely studied in psychology and …","url":["https://openreview.net/pdf?id=3gg6GHhuvi"]}
{"year":"2024","title":"Survey of different Large Language Model Ar-chitectures: Trends, Benchmarks, and Challenges","authors":["M SHAO, A BASIT, R KARRI, M SHAFIQUE - structure"],"snippet":"Large Language Models (LLMs) represent a class of deep learning models adept at understanding natural language and generating coherent text in response to prompts or queries. These models significantly surpass conventional neural …","url":["https://www.researchgate.net/profile/Minghao_Shao2/publication/383976933_Survey_of_different_Large_Language_Model_Architectures_Trends_Benchmarks_and_Challenges/links/66e2d320f84dd1716ce79f85/Survey-of-different-Large-Language-Model-Architectures-Trends-Benchmarks-and-Challenges.pdf"]}
{"year":"2024","title":"Survey of Large Multimodal Model Datasets, Application Categories and Taxonomy","authors":["P Pattnayak, HL Patel, B Kumar, A Agarwal, I Banerjee… - arXiv preprint arXiv …, 2024"],"snippet":"Multimodal learning, a rapidly evolving field in artificial intelligence, seeks to construct more versatile and robust systems by integrating and analyzing diverse types of data, including text, images, audio, and video. Inspired by the human ability …","url":["https://arxiv.org/pdf/2412.17759"]}
{"year":"2024","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","authors":["GO Nnadi, F Bertini - arXiv preprint arXiv:2412.17165, 2024"],"snippet":"… To extend the input data for large-scale news article generation, similar articles are sourced from the Common Crawl News dataset. The WCEP dataset is well-aligned with real-world industrial use cases, making it suitable for training and evaluating …","url":["https://arxiv.org/pdf/2412.17165"]}
{"year":"2024","title":"Survey On Enhancing Dialogue Agent Alignment via MiniLLM with Targeted Human Assessments","authors":["MS Mahajan, MC Vaidya, BL Narware, DR Yemde…"],"snippet":"This paper presents the development of a com-pact and effective language model inspired by the LLaMA architecture. Our focus was on constructing this model based on the fundamental principles of LLaMA, which have influenced our architectural …","url":["http://imanagerpublications.com/assets/pubarticles/1730198642Survey_On_Enhancing_Dialogue_Agent_Alignment_via_MiniLLM_with_Targeted_Human_Assessments.pdf"]}
{"year":"2024","title":"Survey on Semantic Interpretation of Tabular Data: Challenges and Directions","authors":["M Cremaschi, B Spahiu, M Palmonari, E Jimenez-Ruiz - arXiv preprint arXiv …, 2024"],"snippet":"Tabular data plays a pivotal role in various fields, making it a popular format for data manipulation and exchange, particularly on the web. The interpretation, extraction, and processing of tabular information are invaluable for knowledge-intensive …","url":["https://arxiv.org/pdf/2411.11891"]}
{"year":"2024","title":"Surveying Model Collapse: Empirics, Universality, and Implications","authors":["AC Arulandu"],"snippet":"… In the real world, generative outputs pollute the common crawl via accumulation, not replacement; while the real training data diminishes in proportion, as portrayed in Figure 5, it remains available for training at any generation, potentially allowing …","url":["https://arulandu.com/assets/pdf/am254-model-collapse.pdf"]}
{"year":"2024","title":"Surveying the Effects of Quality, Diversity, and Complexity in Synthetic Data From Large Language Models","authors":["A Havrilla, A Dai, L O'Mahony, K Oostermeijer, V Zisler… - arXiv preprint arXiv …, 2024"],"snippet":"Synthetic data generation with Large Language Models is a promising paradigm for augmenting natural data over a nearly infinite range of tasks. Given this variety, direct comparisons among synthetic data generation algorithms are scarce, making …","url":["https://arxiv.org/pdf/2412.02980"]}
{"year":"2024","title":"SWEb: A Large Web Dataset for the Scandinavian Languages","authors":["T Norlund, T Isbister, AC Gyllensten, PD Santos… - arXiv preprint arXiv …, 2024"],"snippet":"… SWEb is the result of running our proposed pipeline on 98 Common Crawl snapshots. SWEb contains … Common Crawl, we want to implement this step early to filter out all non-relevant content. We use CCNet to identify Scandinavian …","url":["https://arxiv.org/pdf/2410.04456"]}
{"year":"2024","title":"SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding","authors":["H Li, C Tian, J Shao, X Zhu, Z Wang, J Zhu, W Dou… - arXiv preprint arXiv …, 2024"],"snippet":"The remarkable success of Large Language Models (LLMs) has extended to the multimodal domain, achieving outstanding performance in image understanding and generation. Recent efforts to develop unified Multimodal Large Language …","url":["https://arxiv.org/pdf/2412.09604"]}
{"year":"2024","title":"Synthetic continued pretraining","authors":["Z Yang, N Band, S Li, E Candès, T Hashimoto - arXiv preprint arXiv:2409.07431, 2024"],"snippet":"Pretraining on large-scale, unstructured internet text has enabled language models to acquire a significant amount of world knowledge. However, this knowledge acquisition is data-inefficient -- to learn a given fact, models must be trained on …","url":["https://arxiv.org/pdf/2409.07431"]}
{"year":"2024","title":"Synthetic Data Generation and Joint Learning for Robust Code-Mixed Translation","authors":["S Soni, A Kunchukuttan, T Chakraborty, MS Akhtar - arXiv preprint arXiv …, 2024"],"snippet":"The widespread online communication in a modern multilingual world has provided opportunities to blend more than one language (aka code-mixed language) in a single utterance. This has resulted a formidable challenge for the computational …","url":["https://arxiv.org/pdf/2403.16771"]}
{"year":"2024","title":"Synthetic data in biomedicine via generative artificial intelligence","authors":["B van Breugel, T Liu, D Oglic, M van der Schaar - Nature Reviews Bioengineering, 2024"],"snippet":"The creation and application of data in biomedicine and healthcare often face privacy constraints, bias, distributional shifts, underrepresentation of certain groups and data scarcity. Some of these challenges may be addressed by synthetic data …","url":["https://www.nature.com/articles/s44222-024-00245-7"]}
{"year":"2024","title":"System for News Summarizing Using a Neural Network Algorithm","authors":["A Akhmedova, I Zhazhneva, G Galimov - 2024 International Russian Automation …, 2024"],"snippet":"This paper presents implementation of a system for summarizing news using a neural network algorithm. Relevance of the development of this system is due to the need for users to receive news in a concise form, while maintaining objectivity and …","url":["https://ieeexplore.ieee.org/abstract/document/10694002/"]}
{"year":"2024","title":"Systematic Evaluation of Linear Transformations for Cross-lingual Semantic Spaces","authors":["A Mištera, T Brychcín, J Šmíd - 2024"],"snippet":"In the field of natural language understanding (NLU), a fundamental element is the representation of word meanings, a process that is integral to a wide range of applications. These applications span numerous domains including machine …","url":["https://www.researchsquare.com/article/rs-3913165/latest.pdf"]}
{"year":"2024","title":"Systematic exploration and in-depth analysis of ChatGPT architectures progression","authors":["D Banik, N Pati, A Sharma - Artificial Intelligence Review, 2024"],"snippet":"The fast evolution of artificial intelligence frameworks has resulted in the creation of increasingly sophisticated large language models (LLM), ChatGPT being the most famous one. This study paper dives into this LLM with a case study of ChatGPT’s …","url":["https://link.springer.com/article/10.1007/s10462-024-10832-0"]}
{"year":"2024","title":"T5G2P: Text-to-Text Transfer Transformer based Grapheme-to-Phoneme Conversion","authors":["M Řezáčková, D Tihelka, J Matoušek - IEEE/ACM Transactions on Audio, Speech …, 2024"],"snippet":"… For the Czech language, we collected the CommonCrawl corpus at the end of August 2020. It contains 47.9GB of clean text, 20.5 million … Similarly, for both Russian and German we collected CommonCrawl corpus in the season from August …","url":["https://ieeexplore.ieee.org/abstract/document/10592637/"]}
{"year":"2024","title":"Tübingen-CL at SemEval-2024 Task 1: Ensemble Learning for Semantic Relatedness Estimation","authors":["L Zhang, Ç Çöltekin - Proceedings of the 18th International Workshop on …, 2024"],"snippet":"The paper introduces our system for SemEval-2024 Task 1, which aims to predict the relatedness of sentence pairs. Operating under the hypothesis that semantic relatedness is a broader concept that extends beyond mere similarity of sentences …","url":["https://aclanthology.org/2024.semeval-1.147.pdf"]}
{"year":"2024","title":"TabDPT: Scaling Tabular Foundation Models","authors":["J Ma, V Thomas, R Hosseinzadeh, H Kamkari… - arXiv preprint arXiv …, 2024"],"snippet":"The challenges faced by neural networks on tabular data are well-documented and have hampered the progress of tabular foundation models. Techniques leveraging in-context learning (ICL) have shown promise here, allowing for dynamic adaptation to unseen …","url":["https://arxiv.org/pdf/2410.18164"]}
{"year":"2024","title":"Table Representation Learning","authors":["M Hulsebos - 2024"],"snippet":"The increasing amount of data being collected, stored, and analyzed, induces a need for efficient, scalable, and robust methods to handle this data. Representation learning, ie, the practice of leveraging neural networks to obtain generic vector …","url":["https://pure.uva.nl/ws/files/155198398/Thesis.pdf"]}
{"year":"2024","title":"Tackling an Unbalanced Dataset for Classifying Indonesian E-Commerce Reviews Using Multi Word Embedding Model","authors":["R Adi, BR Irnawan, J Li - 2023 Eighth International Conference on Informatics …, 2023"],"snippet":"… Our research used a pre-trained FastText that was trained on Indonesian Common Crawl and Wikipedia provided by [24]. 3) GloVe: GloVe is an unsupervised algorithm that can produce a vector representation of words created by [22]. Besides …","url":["https://ieeexplore.ieee.org/abstract/document/10381997/"]}
{"year":"2024","title":"Tackling the Problem of Multilingualism in Voice Assistants","authors":["S Sabharwal, R Sahni - 2024"],"snippet":"… from the C4 dataset - a vast collection of English text from Common Crawl, totaling around 750GB. The model's strengths lie in its unified … This multilingual model was pre-trained on a dataset derived from Common Crawl, encompassing an …","url":["https://aipublications.com/uploads/issue_files/1IJEEC-SEP20241-Tackling.pdf"]}
{"year":"2024","title":"Take the Bull by the Horns: Hard Sample-Reweighted Continual Training Improves LLM Generalization","authors":["X Chen, Z Wang, D Sow, J Yang, T Chen, Y Liang… - arXiv preprint arXiv …, 2024"],"snippet":"… subset of the Common Crawl’s web crawl corpus. More recently, LLaMA (Touvron et al.… datasets to encompass multiple domains such as Common Crawl, C4, and source codes from … contents are mostly unintelligible” in the Common Crawl. All …","url":["https://arxiv.org/html/2402.14270v1"]}
{"year":"2024","title":"Tamil Language Computing: the Present and the Future","authors":["K Sarveswaran - arXiv preprint arXiv:2407.08618, 2024"],"snippet":"This paper delves into the text processing aspects of Language Computing, which enables computers to understand, interpret, and generate human language. Focusing on tasks such as speech recognition, machine translation, sentiment …","url":["https://arxiv.org/pdf/2407.08618"]}
{"year":"2024","title":"Task Oriented In-Domain Data Augmentation","authors":["X Liang, X Hu, S Zuo, Y Gong, Q Lou, Y Liu, SL Huang… - arXiv preprint arXiv …, 2024"],"snippet":"Large Language Models (LLMs) have shown superior performance in various applications and fields. To achieve better performance on specialized domains such as law and advertisement, LLMs are often continue pre-trained on in-domain data …","url":["https://arxiv.org/pdf/2406.16694"]}
{"year":"2024","title":"Tasneef: A Fast and Effective Hybrid Representation Approach for Arabic Text Classification","authors":["M Louail, CKM Hamdi-Cherif, A Hamdi-Cherif - IEEE Access, 2024"],"snippet":"The Arabic language role in actual global affairs entails sophisticated natural language processing techniques, especially in text classification. This paper presents Tasneef as a novel hybrid approach to tackle computational challenges by …","url":["https://ieeexplore.ieee.org/iel8/6287639/6514899/10654296.pdf"]}
{"year":"2024","title":"TEA+: A Novel Temporal Graph Random Walk Engine With Hybrid Storage Architecture","authors":["C Huan, Y Liu, H Zhang, S Song, S Pandey, S Chen… - ACM Transactions on Architecture …"],"snippet":"Many real-world networks are characterized by being temporal and dynamic, wherein the temporal information signifies the changes in connections, such as the addition or removal of links between nodes. Employing random walks on these …","url":["https://dl.acm.org/doi/pdf/10.1145/3652604"]}
{"year":"2024","title":"Team Aditya at EXIST 2024—Detecting Sexism In Multilingual Tweets Using Contrastive Learning Approach","authors":["A Shah, A Gokhale - Working Notes of CLEF, 2024"],"snippet":"Due to the growing impact of social media, the necessity for automated mechanisms that can identify sexism and other forms of disrespectful and hateful conduct is rising, aiming to create a more inclusive and respectful digital space. However, it poses …","url":["https://ceur-ws.org/Vol-3740/paper-112.pdf"]}
{"year":"2024","title":"Team OpenWebSearch at CLEF 2024: LongEval","authors":["D Alexander, M Fröbe, G Hendriksen, F Schlatt… - 2024"],"snippet":"We describe the OpenWebSearch group’s participation in the CLEF 2024 LongEval IR track. Our submitted runs explore how historical data from the past can be transferred into future retrieval systems. Therefore, we incorporate relevance …","url":["https://downloads.webis.de/publications/papers/alexander_2024.pdf"]}
{"year":"2024","title":"Technical Report: Small Language Model for Japanese Clinical and Medicine","authors":["S Watanabe - arXiv preprint arXiv:2412.16423, 2024"],"snippet":"This report presents a small language model (SLM) for Japanese clinical and medicine, named NCVC-slm-1. This 1B parameters model was trained using Japanese text classified to be of high-quality. Moreover, NCVC-slm-1 was …","url":["https://arxiv.org/pdf/2412.16423"]}
{"year":"2024","title":"TeClass: A Human-Annotated Relevance-based Headline Classification and Generation Dataset for Telugu","authors":["G Kanumolu, L Madasu, N Surange, M Shrivastava - arXiv preprint arXiv:2404.11349, 2024"],"snippet":"… 2019) is a multilingual version of the RoBERTa model, and it was pre-trained on a vast 2.5TB CommonCrawl dataset, which included text from 100 languages. For our experiments, we utilized the xlm-roberta-base variant, boasting 270 million parameters. …","url":["https://arxiv.org/pdf/2404.11349"]}
{"year":"2024","title":"TelcoLM: collecting data, adapting, and benchmarking language models for the telecommunication domain","authors":["C Barboule, VP Huynh, A Bufort, Y Chabot, G Damnati… - arXiv preprint arXiv …, 2024"],"snippet":"… For documents collected in Common Crawl, PDFMiner is used to extract the texts. To further assess the relevance and quality of the texts extracted, the Zephyr-7b (Tunstall et al., 2023) model was prompted to classify whether a text is linked to the …","url":["https://arxiv.org/pdf/2412.15891"]}
{"year":"2024","title":"Tele-FLM Technical Report","authors":["X Li, Y Yao, X Jiang, X Fang, C Wang, X Liu, Z Wang… - arXiv preprint arXiv …, 2024"],"snippet":"… CommonCrawl1 is often considered to be a repository containing diverse human experience … CommonCrawl are primarily concentrated in the English segment, with the Chinese content exhibiting relatively lower information density and quality …","url":["https://arxiv.org/pdf/2404.16645"]}
{"year":"2024","title":"Tele-LLMs: A Series of Specialized Large Language Models for Telecommunications","authors":["A Maatouk, KC Ampudia, R Ying, L Tassiulas - arXiv preprint arXiv:2409.05314, 2024"],"snippet":"… is the Common Crawl dataset, which comprises web archives from across the internet. To avoid issues with duplicates, non-English content, and potential profanity found in raw dumps, we utilized the refined web dataset [26]. This curated …","url":["https://arxiv.org/pdf/2409.05314"]}
{"year":"2024","title":"TelecomGPT: A Framework to Build Telecom-Specfic Large Language Models","authors":["H Zou, Q Zhao, Y Tian, L Bariah, F Bader, T Lestable… - arXiv preprint arXiv …, 2024"],"snippet":"Large Language Models (LLMs) have the potential to revolutionize the Sixth Generation (6G) communication networks. However, current mainstream LLMs generally lack the specialized knowledge in telecom domain. In this paper, for the …","url":["https://arxiv.org/pdf/2407.09424"]}
{"year":"2024","title":"Tell me a story: a framework for critically investigating AI language models","authors":["L Munn, L Henrickson - Learning, Media and Technology, 2024"],"snippet":"Large language models are rapidly being rolled out into high-stakes fields like healthcare, law, and education. However, understanding of their design considerations, operational logics, and implicit biases remains limited. How might …","url":["https://www.tandfonline.com/doi/pdf/10.1080/17439884.2024.2327024"]}
{"year":"2024","title":"TEMA: Token Embeddings Mapping for Enriching Low-Resource Language Models","authors":["R Zevallos, N Bel, M Farrús - Proceedings of the 2024 Conference on Empirical …, 2024"],"snippet":"The objective of the research we present is to remedy the problem of the low quality of language models for low-resource languages. We introduce an algorithm, the Token Embedding Mapping Algorithm (TEMA), that maps the token embeddings of a …","url":["https://aclanthology.org/2024.emnlp-main.638.pdf"]}
{"year":"2024","title":"Temporal Blind Spots in Large Language Models","authors":["J Wallat, A Jatowt, A Anand - arXiv preprint arXiv:2401.12078, 2024"],"snippet":"… A mixture of training datasets has been used: a filtered version of CommonCrawl, an expanded version of WebText [44], two not further specified internet-based book corpora, and the English Wikipedia. The most recent information in text-davinci-003’s …","url":["https://arxiv.org/pdf/2401.12078"]}
{"year":"2024","title":"Temporally-Varied News Headline Generation with GPT-3","authors":["V Graf, E Tian, R Zhu"],"url":["https://richardzhu123.github.io/assets/pdf/Temporally-Varied_News_Headline_Generation_with_GPT-3.pdf"]}
{"year":"2024","title":"Terra: A Multimodal Spatio-Temporal Dataset Spanning the Earth","authors":["W Chen, X Hao, Y Liang - The Thirty-eight Conference on Neural Information …"],"snippet":"Since the inception of our planet, the meteorological environment, as reflected through spatio-temporal data, has always been a fundamental factor influencing human life, socio-economic progress, and ecological conservation. A …","url":["https://openreview.net/pdf?id=I0zpivK0A0"]}
{"year":"2024","title":"Testing and Adapting the Representational Abilities of Large Language Models on Folktales in Low-Resource Languages","authors":["JA Meaney, B Alex, W Lamb - Proceedings of the 4th International Conference on …, 2024"],"snippet":"Folktales are a rich resource of knowledge about the society and culture of a civilisation. Digital folklore research aims to use automated techniques to better understand these folktales, and it relies on abstract representations of the textual …","url":["https://aclanthology.org/2024.nlp4dh-1.31.pdf"]}
{"year":"2024","title":"Testing proportional sentence analogies on SATS: from vector offsets to conditional generation","authors":["Y Blain-Montesano, P Langlais - 2024"],"snippet":"… 23], SBERT9 [18], and summed embeddings from the English Common Crawl CBOW FastText embeddings [24]. We use the Base checkpoint for all models where applicable. To the second point, we examine three vector solvers: 3CosAdd, a …","url":["https://iarml2024-ijcai.loria.fr/files/2024/07/iarml-article-langlais.pdf"]}
{"year":"2024","title":"TEXAS INTELLECTUAL PROPERTY LAW JOURNAL","authors":["J Nacht, A Neill, J Thomas, E Lee, KE Noonan… - 2024"],"snippet":"… 4t Common Crawl contains information from over 250 billion web pages since 2007 using web crawlers … in Common Crawl was filtered before being incorporated into GPT-3 to maintain a higher level of quality for training purposes.Websites …","url":["https://heinonline.org/hol-cgi-bin/get_pdf.cgi?handle=hein.journals/tipj32&section=13"]}
{"year":"2024","title":"Text classification for private procurement: a survey and an analysis of future trends","authors":["F Bellomi, M Cristani - Information Technology and Management, 2024"],"snippet":"… A widely used base of these techniques is the Common Crawl, an open source collection of textual (and also diverse) datasets coming from the web that can be used as a basis for similarity analysis [14]. Recently, the common crawl has also …","url":["https://link.springer.com/article/10.1007/s10799-024-00444-z"]}
{"year":"2024","title":"Text Emotion Recognition Using Fast Text Word Embedding in Bi-Directional Gated Recurrent Unit","authors":["C Akalya Devi, D Karthika Renuka, T Harisudhan…"],"snippet":"Emotions are states of readiness in the mind that result from evaluations of one's own thinking or events. Although almost all of the important events in our lives are marked by emotions, the nature, causes, and effects of emotions are some of the …","url":["https://imanagerpublications.com/assets/htmlfiles/JIT11(4)September-November202219119.html"]}
{"year":"2024","title":"Text Filtering Classifiers for Medium-Resource Languages","authors":["J Daðason, H Loftsson - Proceedings of the 2024 Joint International Conference …, 2024"],"snippet":"… Online texts are often obtained from large datasets, such as those published by Common Crawl (CC).The GPT-3 model was pre-trained on 499B tokens, 410B of which were obtained from CC (Brown et al.… The Icelandic Common Crawl Corpus (IC3) …","url":["https://aclanthology.org/2024.lrec-main.1372.pdf"]}
{"year":"2024","title":"Text Generation Models for Luxembourgish with Limited Data: A Balanced Multilingual Strategy","authors":["A Plum, T Ranasinghe, C Purschke - arXiv preprint arXiv:2412.09415, 2024"],"snippet":"This paper addresses the challenges in developing language models for less-represented languages, with a focus on Luxembourgish. Despite its active development, Luxembourgish faces a digital data scarcity, exacerbated by Luxembourg's …","url":["https://arxiv.org/pdf/2412.09415"]}
{"year":"2024","title":"Text Generation: A Systematic Literature Review of Tasks, Evaluation, and Challenges","authors":["J Becker, JP Wahle, B Gipp, T Ruas - arXiv preprint arXiv:2405.15604, 2024"],"snippet":"Text generation has become more accessible than ever, and the increasing interest in these systems, especially those using large language models, has spurred an increasing number of related publications. We provide a systematic literature review …","url":["https://arxiv.org/pdf/2405.15604"]}
{"year":"2024","title":"TEXT SUMMARIZATION SYSTEM USING NATURAL LANGUAGE PROCESSING AND MACHINE LEARNING","authors":["M NARAYAN - 2023"],"snippet":"Information overload, caused by the rapid growth of the Internet, has become a significant issue. The abundance of information available online necessitates the simplification of relevant content through summarization. Manual summarization of …","url":["http://dspace.dtu.ac.in:8080/jspui/bitstream/repository/20400/1/MANEESH%20NARAYAN%20M.Tech..pdf"]}
{"year":"2024","title":"Text to SQL Transformation Using LLM: A Comparative Research of T5, Seq2Seq, and SQLNet Models","authors":["Z Shaikhiyeva, M Mansurova, G Amirkhanova - 2024 9th International Conference on …, 2024"],"snippet":"The transformation of natural language text into SQL queries is a critical task in the domain of natural language processing and database management. This paper presents a comparative analysis of three prominent models: T5 (Text-to-Text …","url":["https://ieeexplore.ieee.org/abstract/document/10773579/"]}
{"year":"2024","title":"Text-to-text generative approach for enhanced complex word identification","authors":["P Śliwiak, SAA Shah - Neurocomputing, 2024"],"snippet":"This paper presents a novel approach for solving the Complex Word Identification (CWI) task using the text-to-text generative model. The CWI task involves identifying complex words in text, which is a challenging Natural Language Processing task. To …","url":["https://www.sciencedirect.com/science/article/pii/S0925231224012724"]}
{"year":"2024","title":"TextGram: Towards a Better Domain-Adaptive Pretraining","authors":["O Dhekane, S Hiwarkhedkar, R Joshi, A Ladkat - … , Perundurai, Erode, India, December 6–8 …"],"snippet":"… The RealNews Dataset is a large corpus of news articles scraped from Common Crawl [16]. It consists of 5000 news domains that are indexed by Google news. IMDb Movie Reviews is a binary sentiment analysis dataset made up of 50000 reviews …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=Rs0DEQAAQBAJ&oi=fnd&pg=PA161&dq=commoncrawl&ots=l6SKt6PjDk&sig=eAtYThwZwGzNMXk0LzGOBEGThUM"]}
{"year":"2024","title":"TextHawk2: A Large Vision-Language Model Excels in Bilingual OCR and Grounding with 16x Fewer Tokens","authors":["YQ Yu, M Liao, J Zhang, J Wu - arXiv preprint arXiv:2410.05261, 2024"],"snippet":"… We also use PDFPlumber to extract text lines from Common Crawl PDFs. To improving English handwriting recognition, we incorporate RenderedText (StabilityAI & LAION, 2023). Additional end-to-end OCR datasets, including ArT (Chng et al …","url":["https://arxiv.org/pdf/2410.05261"]}
{"year":"2024","title":"Textual Coverage of Eventive Entries in Lexical Semantic Resources","authors":["E Fucikova, CF Alcaina, J Hajic, Z Urešová - Proceedings of the 2024 Joint …, 2024"],"snippet":"This short paper focuses on the coverage of eventive entries (verbs, predicates, etc.) of some well-known lexical semantic resources when applied to random running texts taken from the internet. While coverage gaps are often reported for manually …","url":["https://aclanthology.org/2024.lrec-main.1375.pdf"]}
{"year":"2024","title":"Textual emotion detection–A systematic literature review","authors":["V Truong - 2024"],"snippet":"Textual emotion detection is a critical area of study with significant applications in business, education, and healthcare. Despite substantial theoretical advancements over the years, there is a notable gap in the practical implementation of these …","url":["https://www.researchsquare.com/article/rs-4673385/latest.pdf"]}
{"year":"2024","title":"The advantages of context specific language models: the case of the Erasmian Language Model","authors":["J Gonçalves, N Jelicic, M Murgia, E Stamhuis - arXiv preprint arXiv:2408.06931, 2024"],"snippet":"… The dominant trend in improving language models seems to be based on scaling up the number of parameters (eg GPT4 has approximately 1.7 trillion parameters) or the amount of training data fed into the model (eg the Common Crawl dataset …","url":["https://arxiv.org/pdf/2408.06931"]}
{"year":"2024","title":"The African Woman is Rhythmic and Soulful: An Investigation of Implicit Biases in LLM Open-ended Text Generation","authors":["S Lim, M Pérez-Ortiz - 2024"],"snippet":"This paper investigates the subtle and often concealed biases present in Large Language Models (LLMs), focusing on implicit biases that may remain despite passing explicit bias tests. Implicit biases are significant because they influence the …","url":["https://www.researchsquare.com/article/rs-5283007/latest"]}
{"year":"2024","title":"The African Woman is Rhythmic and Soulful: Evaluation of Open-ended Generation for Implicit Biases","authors":["S Lim - arXiv preprint arXiv:2407.01270, 2024"],"snippet":"This study investigates the subtle and often concealed biases present in Large Language Models (LLMs), which, despite passing explicit bias tests, can still exhibit implicit biases akin to those observed in humans who profess egalitarian beliefs yet …","url":["https://arxiv.org/pdf/2407.01270"]}
{"year":"2024","title":"The AI Companion in Education: Analyzing the Pedagogical Potential of ChatGPT in Computer Science and Engineering","authors":["Z He, T Nguyen, T Miari, M Aliasgari, S Rafatirad…"],"snippet":"… ChatGPT3 employs a pre-trained large language model [29] trained over the Common Crawl dataset [30]. During its training process, it first preprocess data from the Common Crawl dataset, data quality is refined by eliminating irrelevant or noisy …","url":["https://www.researchgate.net/profile/Zhangying-He/publication/380210828_The_AI_Companion_in_Education_Analyzing_the_Pedagogical_Potential_of_ChatGPT_in_Computer_Science_and_Engineering/links/663175407091b94e93e9cf70/The-AI-Companion-in-Education-Analyzing-the-Pedagogical-Potential-of-ChatGPT-in-Computer-Science-and-Engineering.pdf"]}
{"year":"2024","title":"The AI Did My Job Well","authors":["CM Moran, M Coward"],"snippet":"Artificial intelligence (AI), an idea first proposed back in 1955 (McCarthy, Minsky, & Rochester) seemingly has burst into public consciousness nearly 70 years later. Like the chained prisoners emerging from Plato’s allegorical cave, many of us find …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=HtIDEQAAQBAJ&oi=fnd&pg=PA15&dq=commoncrawl&ots=Wd6CuXLoH8&sig=E1TnJeb3liWF_UQel1vg_9SX-fA"]}
{"year":"2024","title":"The Aranea Corpora Family: Ten+ Years of Processing Web-Crawled Data","authors":["V Benko - International Conference on Text, Speech, and …, 2024"],"snippet":"Aranea is a project to create a family of web-crawled corpora for languages taught at Slovak Universities. Since 2013, more than two dozen languages have been added to the project: they are often represented with Gigaword+ size corpora and …","url":["https://link.springer.com/chapter/10.1007/978-3-031-70563-2_5"]}
{"year":"2024","title":"The Bangla/Bengali Seed Dataset Submission to the WMT24 Open Language Data Initiative Shared Task","authors":["F Ahmed, N Venkateswaran, S Moeller"],"snippet":"We contribute a seed dataset for the Bangla/Bengali language as part of the WMT24 Open Language Data Initiative shared task. We validate the quality of the dataset against a mined and automatically aligned dataset (NLLBv1) and two other existing …","url":["https://www2.statmt.org/wmt24/pdf/2024.wmt-1.42.pdf"]}
{"year":"2024","title":"The BEA 2024 Shared Task on the Multilingual Lexical Simplification Pipeline","authors":["M Shardlow, F Alva-Manchego, RT Batista-Navarro… - … on Innovative Use of NLP for …, 2024"],"snippet":"We report the findings of the 2024 Multilingual Lexical Simplification Pipeline shared task. We released a new dataset comprising 5,927 instances of lexical complexity prediction and lexical simplification on common contexts across 10 languages, split …","url":["https://aclanthology.org/2024.bea-1.51.pdf"]}
{"year":"2024","title":"The Blue Behemoth","authors":["L Blackett, R Rocklynne - Dentist"],"snippet":"Pretraining on large-scale, unstructured internet text enables language models to acquire a significant amount of world knowledge. However, this knowledge acquisition is data-inefficient---to learn a fact, models must be trained on hundreds to …","url":["https://openreview.net/pdf?id=07yvxWDSla"]}
{"year":"2024","title":"The bounded intelligence of AI: Superficiality and deceivability","authors":["H Ma, M Su - Organizational Dynamics, 2024"],"snippet":"… A 2024 study by the Pew Research Center found that, in their sample of about one million webpages from the Internet archive Common Crawl collected between 2013 and October 2023, a quarter were no longer accessible (showing 404 Not …","url":["https://www.sciencedirect.com/science/article/pii/S0090261624000731"]}
{"year":"2024","title":"The Case For Data Centre Hyperloops","authors":["G López-Paradís, IM Hair, S Kannan, R Rabbat… - 2024 ACM/IEEE 51st …, 2024","G López-Paradıs, IM Hair, S Kannan, R Rabbat…"],"snippet":"Data movement is a hot-button topic today, with workloads like machine learning (ML) training, graph processing, and data analytics consuming datasets as large as 30PB. Such a dataset would take almost a week to transfer at 400gbps while consuming …","url":["https://ieeexplore.ieee.org/abstract/document/10609637/","https://jbalkind.github.io/docs/dhl_camera_ready.pdf"]}
{"year":"2024","title":"The Case for Developing a Foundation Model for Planning-like Tasks from Scratch","authors":["B Srivastava, V Pallagani - arXiv preprint arXiv:2404.04540, 2024"],"snippet":"Foundation Models (FMs) have revolutionized many areas of computing, including Automated Planning and Scheduling (APS). For example, a recent study found them useful for planning problems: plan generation, language translation, model …","url":["https://arxiv.org/html/2404.04540v1"]}
{"year":"2024","title":"The Case for Nurturing AI Literacy in Law Schools","authors":["S Migliorini, JI Moreira - Asian Journal of Legal Education, 2024"],"snippet":"The debate surrounding the permissibility of generative artificial intelligence (AI) tools in legal education has garnered widespread attention. However, this discourse has largely oscillated between the advantages and disadvantages of generative AI …","url":["https://journals.sagepub.com/doi/abs/10.1177/23220058241265613"]}
{"year":"2024","title":"The correlation between nativelike selection and prototypicality: a multilingual onomasiological case study using semantic embedding","authors":["H Zhang - arXiv preprint arXiv:2405.13529, 2024"],"snippet":"In native speakers' lexical choices, a concept can be more readily expressed by one expression over another grammatical one, a phenomenon known as nativelike selection (NLS). In previous research, arbitrary chunks such as collocations have …","url":["https://arxiv.org/pdf/2405.13529"]}
{"year":"2024","title":"The Dark Side of Dataset Scaling: Evaluating Racial Classification in Multimodal Models","authors":["A Birhane, S Dehdashtian, VU Prabhu, V Boddeti - arXiv preprint arXiv:2405.04623, 2024"],"snippet":"… This is particularly important in the context of multimodal datasets whose main source is the World Wide Web, condensed and packaged as the Common Crawl dump, which is known to exhibit numerous drawbacks. In this paper, we evaluate the …","url":["https://arxiv.org/pdf/2405.04623"]}
{"year":"2024","title":"The Dark Side of Language Models: Exploring the Potential of LLMs in Multimedia Disinformation Generation and Dissemination","authors":["D Barman, Z Guo, O Conlan - Machine Learning with Applications, 2024"],"snippet":"Disinformation - the deliberate spread of false or misleading information poses a significant threat to our society by undermining trust, exacerbating polarization, and manipulating public opinion. With the rapid advancement of artificial intelligence and …","url":["https://www.sciencedirect.com/science/article/pii/S2666827024000215"]}
{"year":"2024","title":"THE DETERMINANTS OF SOFTWARE DEVELOPERS'INTENTION TO ADOPT CHAT GPT AS PROGRAMMING INFORMATION MEDIA","authors":["ID WIRAWAN, T OKTAVIA - Journal of Theoretical and Applied Information …, 2024"],"snippet":"In the digital era, technology is developing rapidly. One of them in the field of artificial intelligence is chatbots. A chatbot is a computer program designed to stimulate conversation or interactive communication with (human) users via text …","url":["http://www.jatit.org/volumes/Vol102No22/11Vol102No22.pdf"]}
{"year":"2024","title":"The diagnostic and triage accuracy of the GPT-3 artificial intelligence model: an observational study","authors":["DM Levine, R Tuwani, B Kompa, A Varma… - The Lancet Digital Health, 2024"],"snippet":"… GPT-3 is one of the largest AI models ever created, containing over 175 billion model parameters, and was trained on approximately 570 gigabytes of data from the common crawl dataset, which contains nearly all unstructured text available on the …","url":["https://www.thelancet.com/journals/landig/article/PIIS2589-7500(24)00097-9/fulltext"]}
{"year":"2024","title":"The effect of generative artificial intelligence on managerial behavior across functions","authors":["ST OZTURK"],"snippet":"GAI is becoming readily available and easily accessible for those who are willing to take advantage of it. As a result, the world is witnessing a transformation regarding how managers perform their daily tasks. This study aims to understand the …","url":["https://thesis.unipd.it/bitstream/20.500.12608/62859/1/Ozturk_Safak_Tanir.pdf"]}
{"year":"2024","title":"THE ENHANCEMENT OF OPEN DATA USABILITY BY DEFINING A CATEGORIZATION METHOD BASED ON THE OPEN DATA PORTAL METADATA","authors":["MBF Gligorijević"],"snippet":"Due to numerous data transparency and open government initiatives, a large volume of data was published on open data portals. To make it more accessible and visible, these portals have introduced data filtering by category, tags, format …","url":["https://www.elfak.ni.ac.rs/downloads/informacije/studenti/doktorske-magistarske/2023/dus-uni-frtunic-gligorijevic-b-milena-2023-sa-napomenom.pdf"]}
{"year":"2024","title":"The ethical situation of DALL-E 2","authors":["E Hogea, J Rocafortf - arXiv preprint arXiv:2405.19176, 2024"],"snippet":"A hot topic of Artificial Intelligence right now is image generation from prompts. DALL-E 2 is one of the biggest names in this domain, as it allows people to create images from simple text inputs, to even more complicated ones. The company that made this …","url":["https://arxiv.org/pdf/2405.19176"]}
{"year":"2024","title":"The Ethics and Challenges of Legal Personhood for AI","authors":["HKB Forrest - Ethics, 2024"],"snippet":"Hon. Katherine B. Forrest (Fmr.) abstract. AI’s increasing cognitive abilities will raise challenges for judges.“Legal personhood” is a flexible and political concept that has evolved throughout American history. In determining whether to expand that concept …","url":["https://www.yalelawjournal.org/pdf/ForrestYLJForumEssay_at8hdu63.pdf"]}
{"year":"2024","title":"The Evolution of Multimodal Model Architectures","authors":["SN Wadekar, A Chaurasia, A Chadha, E Culurciello - arXiv preprint arXiv:2405.17927, 2024"],"snippet":"This work uniquely identifies and characterizes four prevalent multimodal model architectural patterns in the contemporary multimodal landscape. Systematically categorizing models by architecture type facilitates monitoring of developments in …","url":["https://arxiv.org/pdf/2405.17927"]}
{"year":"2024","title":"The Fill-Mask Association Test (FMAT): Measuring Propositions in Natural Language","authors":["HWS Bao - Journal of Personality and Social Psychology, 2024","L Lin, B Wang, X Wang, ZX Wang, A Wiśniowski…"],"snippet":"Recent advances in large language models are enabling the computational intelligent analysis of psychology in natural language. Here, the Fill-Mask Association Test (FMAT) is introduced as a novel and integrative method leveraging …","url":["https://files.osf.io/v1/resources/bgsxr/providers/osfstorage/66189ed0943bee4457dfec9e?action=download&direct&version=2","https://psychbruce.github.io/paper/Bao_Accepted_JPSP_FMAT_Manuscript.pdf"]}
{"year":"2024","title":"The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale","authors":["G Penedo, H Kydlíček, A Lozhkov, M Mitchell, C Raffel… - arXiv preprint arXiv …, 2024"],"snippet":"… In this work, we introduce FineWeb, a 15-trillion token dataset derived from 96 Common Crawl snapshots that produces better-performing LLMs than other open pretraining datasets. To advance the understanding of how best to curate high-quality …","url":["https://arxiv.org/pdf/2406.17557"]}
{"year":"2024","title":"The Future of Chatbots: Survey on Generative Pretrained Models, Ernie, and Gemini","authors":["A Raut, J Katti - 2024 International Conference on Innovations and …, 2024"],"snippet":"The evolution of chatbots from rule-based, retrieval-based, contextual systems, to hybrid and generative AIpowered models. It aimsto solve complex natural language processing and task-specific challenges. The finding explores innovative self-attention …","url":["https://ieeexplore.ieee.org/abstract/document/10616356/"]}
{"year":"2024","title":"The Future of Data Science in Materials Science","authors":["P Chundi, V Bommanapally, V Gadhamshetty - Machine Learning in 2D Materials …, 2023"],"snippet":"… GPT-3 is an autoregressive model built with 96 layers [31], increased embedding vector dimension of 12888, trained with 175B parameters on five datasets including Common crawl, WebText2, Books1, Books2, and Wikipedia. Though GPT-3 has …","url":["https://www.taylorfrancis.com/chapters/edit/10.1201/9781003132981-12/future-data-science-materials-science-parvathi-chundi-vidya-bommanapally-venkataramana-gadhamshetty"]}
{"year":"2024","title":"The Future of Intelligent Healthcare: A Systematic Analysis and Discussion on the Integration and Impact of Robots Using Large Language Models for Healthcare","authors":["S Pashangpour, G Nejat - Robotics, 2024"],"snippet":"… Namely, datasets used for training LLMs such as Common Crawl contain petabytes of data [260]. Therefore, it is not possible to have complete human oversight over the data cleaning process. Hence, this is why heuristic methods are …","url":["https://www.mdpi.com/2218-6581/13/8/112"]}
{"year":"2024","title":"The future","authors":["F Geeraert, M Kurzmeier, LA Denis, V Schafer… - The Routledge Companion …, 2024"],"snippet":"Friedel Geeraert: I hope that we will be able to continue the work that was started in the WARCnet network in the context of a new research framework in Europe, and beyond, thereby helping to promote the value of web archives for research. As an …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=RLYyEQAAQBAJ&oi=fnd&pg=PA422&dq=commoncrawl&ots=ebVn40Yl74&sig=Qrca330ShARSe4wyj10jzGpndgQ"]}
{"year":"2024","title":"The Good and The Bad: Exploring Privacy Issues in Retrieval-Augmented Generation (RAG)","authors":["S Zeng, J Zhang, P He, Y Xing, Y Liu, H Xu, J Ren… - arXiv preprint arXiv …, 2024"],"snippet":"… 2021), we randomly select chunks from the Common Crawl dataset to serve as the {information} component. … 2021), we randomly select chunks from the Common Crawl dataset to serve as the {information} component. Due to the random …","url":["https://arxiv.org/pdf/2402.16893"]}
{"year":"2024","title":"The High Stakes of AI Ethics: Evaluating OpenAI's Potential Shift to “NSFW” Content and Other Concerns","authors":["L Thompson"],"snippet":"… These address concerns surrounding the dubious curation practices used to generate these datasets, the sordid quality of alt-text data available on the world wide web, the problematic content of the CommonCrawl dataset often used as a …","url":["https://endsexualexploitation.org/wp-content/uploads/Rapid-Assessment-Report_OpenAI_July-2024_FINAL.pdf"]}
{"year":"2024","title":"The Impact of Demonstrations on Multilingual In-Context Learning: A Multidimensional Analysis","authors":["M Zhang, V Gautam, M Wang, JO Alabi, X Shen… - arXiv preprint arXiv …, 2024"],"snippet":"… The order of languages follows their data ratio in the CommonCrawl corpus10 from high-resource to low-resource. We observe large variations in model performance across different languages. For instance, there exists a large …","url":["https://arxiv.org/pdf/2402.12976"]}
{"year":"2024","title":"The Impact of Element Ordering on LM Agent Performance","authors":["W Chi, A Talwalkar, C Donahue - arXiv preprint arXiv:2409.12089, 2024"],"snippet":"… In our approach, we leverage common crawl [3] to train an object detection model [16] that detects interactable UI elements specifically for agents. To the best of our knowledge, the elements detected through these approaches are ordered arbitrarily (eg …","url":["https://arxiv.org/pdf/2409.12089"]}
{"year":"2024","title":"The Impact of Geometric Complexity on Neural Collapse in Transfer Learning","authors":["M Munn, B Dherin, J Gonzalvo - arXiv preprint arXiv:2405.15706, 2024"],"snippet":"Many of the recent remarkable advances in computer vision and language models can be attributed to the success of transfer learning via the pre-training of large foundation models. However, a theoretical framework which explains this empirical …","url":["https://arxiv.org/pdf/2405.15706"]}
{"year":"2024","title":"The Impact of Infrastructure: Considerations of Generative AI in the Classroom","authors":["ES Kehlenbach - Journal of Political Science Education, 2024"],"snippet":"How are we to grapple with the increasing intrusion of technology in the classroom? What considerations need to be addressed before we begin bringing advanced technological systems like ChatGPT into our classroom spaces? A close attention to …","url":["https://www.tandfonline.com/doi/abs/10.1080/15512169.2024.2359439"]}
{"year":"2024","title":"The impact of language family on D2T generation in under-resourced languages","authors":["G Christopoulos - 2024"],"snippet":"The paper delves deep into the challenges and methods of generating text from structured data(RDF triples) for under-resourced languages based on the WebNLG challenge. The main question of this paper is to assess how important language …","url":["https://studenttheses.uu.nl/bitstream/handle/20.500.12932/46903/Georgios_Christopoulos_MSc_Thesis.pdf?sequence=1"]}
{"year":"2024","title":"The Impact of Online Censorship on LLMs","authors":["M Ahmed, J Knockel - Free and Open Communications on the Internet, 2024"],"snippet":"… the Common Crawl contains censored content, there may be downstream effects on the models. To investigate whether the Common Crawl … Of which, we found pages indexed from 325 of the censored websites in the Common Crawl dataset that …","url":["https://petsymposium.org/foci/2024/foci-2024-0006.pdf"]}
{"year":"2024","title":"The Impact of OpenAI on the Work Environment located in Finland","authors":["J Laiho, K Varttila - 2023"],"snippet":"In the modern era, technology has undergone a rapid transformation that touches every aspect of our lives. At the forefront of this transformation stands artificial intelligence (AI), a field rapidly evolving through groundbreaking innovations, and …","url":["https://www.theseus.fi/bitstream/handle/10024/818052/Laiho_Varttila.pdf?sequence=2"]}
{"year":"2024","title":"The Influence of ChatGpt on Students' Opportunistic Behavior and Reduced Effort","authors":["BG Grilo - 2024"],"snippet":"This study challenges the assumption that students become less invested in tasks once they achieve an average grade using AI tools like ChatGPT, this leads to growing concerns about students overreliance on ChatGPT to complete their tasks …","url":["https://search.proquest.com/openview/b4090bb22008e016a8cc7a9ef1e66ea5/1?pq-origsite=gscholar&cbl=2026366&diss=y"]}
{"year":"2024","title":"The influence of noise traders on the Vietnamese stock market","authors":["NT Hoài - Tạp chí Khoa học Thăng Long: Khoa học Ứng dụng, 2024"],"snippet":"The study examines the impact of noise trading on stock returns. The investor sentiment index is constructed as a representative of noise trading. This index is extracted from the social network Facebook and the mainstream online newspapers …","url":["https://science.thanglong.edu.vn/index.php/vola/article/download/135/112"]}
{"year":"2024","title":"the landscape to quantify creative","authors":["IU Haq, M Pifarré - Education Reimagined: The Impact of Advanced …, 2024"],"snippet":"… or unsupervised methods (no prior training) that are trained on a large corpus, eg, Wikipedia and common crawl dataset. Deep learning models such as Word2Vec (Mikolov et al., 2013) or GloVe (Pennington et al., 2014) use knowledge from large datasets …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=Htw4EQAAQBAJ&oi=fnd&pg=PA62&dq=commoncrawl&ots=kSR8j_0el9&sig=LKvzymX23LEr9pUF2qm1-7AUE0c"]}
{"year":"2024","title":"The Large Language Model GreekDeBERTa","authors":["AK Koukouvinis, DA Pantazi"],"snippet":"ABSTRACT Language Models for Natural Language Processing (NLP) have constituted a significant area of research and development for over two decades, with a notable trend towards increasing model complexity and size. The general …","url":["https://pergamos.lib.uoa.gr/uoa/dl/object/3417651/file.pdf"]}
{"year":"2024","title":"The life cycle of large language models in education: A framework for understanding sources of bias","authors":["J Lee, Y Hicke, R Yu, C Brooks, RF Kizilcec - British Journal of Educational …, 2024"],"snippet":"Large language models (LLMs) are increasingly adopted in educational contexts to provide personalized support to students and teachers. The unprecedented capacity of LLM‐based applications to understand and generate natural language can …","url":["https://bera-journals.onlinelibrary.wiley.com/doi/abs/10.1111/bjet.13505"]}
{"year":"2024","title":"The losT daTa: how aI sysTems censor lGBTQ+ conTenT In The name of safeTy","authors":["E Ungless"],"snippet":"… The Google team made the C4 dataset using a snapshot of the Internet in April 2019, as collected by the non-profit Common Crawl, which uses bots to make a free and publicly available copy of a subset of the Internet. But raw Common Crawl data …","url":["https://www.nature.com/articles/s43588-024-00695-4"]}
{"year":"2024","title":"The Mirage of Artificial Intelligence Terms of Use Restrictions","authors":["P Henderson, MA Lemley - arXiv preprint arXiv:2412.07066, 2024"],"snippet":"… For example, many model creators start with Common Crawl and then filter the data for quality.The selection of “everything available for scraping on the internet” is not sufficiently creative to qualify for copyright protection. If there is enough creativity …","url":["https://arxiv.org/pdf/2412.07066"]}
{"year":"2024","title":"The Mitigation of Excessive Retrieval Augmentation and Knowledge Conflicts in Large Language Models","authors":["M Galway, M DiRenzo, D Esposito, R Marchand… - 2024"],"snippet":"There have been significant advances with large language models in generating coherent and contextually relevant responses, but their limitations in accessing and integrating real-time or specialized information have driven the development of …","url":["https://www.researchsquare.com/article/rs-5263949/latest.pdf"]}
{"year":"2024","title":"The model student: GPT-4 performance on graduate biomedical science exams","authors":["D Stribling, Y Xia, MK Amer, KS Graim, CJ Mulligan… - Scientific Reports, 2024"],"snippet":"… As these study materials may have been incorporated into the GPT-4 training data such as the Common Crawl 43 , standardized examinations may not be an accurate assessment of domain-specific model knowledgebase and capability …","url":["https://www.nature.com/articles/s41598-024-55568-7"]}
{"year":"2024","title":"The OECD-UNSD Multinational Enterprise Information Platform","authors":["G Pilgrim, S Ang - 2024"],"snippet":"… (3) Common Crawl is an open source initiative to provide a monthly snapshot of the internet through web scraping. As part of the project, they provide a quarterly network graph of hyperlinks between domains, which can be used to determine …","url":["https://www.oecd-ilibrary.org/economics/the-oecd-unsd-multinational-enterprise-information-platform_b7d90a06-en"]}
{"year":"2024","title":"The Open Web Index","authors":["G Hendriksen, M Dinzinger, SM Farzana, NA Fathima…"],"snippet":"… To operationalize our crawling pipeline, we introduce a re-crawl mechanism specifically for Common Crawl dumps. Unlike Common Crawl, we crawl on a daily basis and save the results as WARC (Web ARChive) files.This approach allows us …","url":["https://djoerdhiemstra.com/wp-content/uploads/ecir2024ir4good.pdf"]}
{"year":"2024","title":"The Open Web Index: Crawling and Indexing the Web for Public Use","authors":["G Hendriksen, M Dinzinger, SM Farzana, NA Fathima… - European Conference on …, 2024"],"snippet":"… To operationalize our crawling pipeline, we introduce a re-crawl mechanism specifically for Common Crawl dumps. Unlike Common Crawl, we crawl on a daily basis and save the results as WARC (Web ARChive) files. Footnote 11 This …","url":["https://link.springer.com/chapter/10.1007/978-3-031-56069-9_10"]}
{"year":"2024","title":"The performance of the LSTM-based code generated by Large Language Models (LLMs) in forecasting time series data","authors":["S Gopali, S Siami-Namini, F Abri, AS Namin - Natural Language Processing Journal, 2024"],"snippet":"Generative AI, and in particular Large Language Models (LLMs), have gained substantial momentum due to their wide applications in various disciplines. While the use of these game changing technologies in generating textual information has …","url":["https://www.sciencedirect.com/science/article/pii/S2949719124000682"]}
{"year":"2024","title":"The poison of dimensionality","authors":["LN Hoang - arXiv preprint arXiv:2409.17328, 2024"],"snippet":"This paper advances the understanding of how the size of a machine learning model affects its vulnerability to poisoning, despite state-of-the-art defenses. Given isotropic random honest feature vectors and the geometric median (or clipped mean) …","url":["https://arxiv.org/pdf/2409.17328"]}
{"year":"2024","title":"The Power of Absence: Thinking with Archival Theory in Algorithmic Design","authors":["J Sherman, R Morrison, L Klein, DK Rosner - arXiv preprint arXiv:2405.05420, 2024"],"snippet":"… , for example–but also of datasets like the Colossal Clean Common Crawl corpus, or C4, which explicitly documents its decision to include … [33] have shown how the quality filters imposed on the original Common Crawl dataset exhibit a preference …","url":["https://arxiv.org/pdf/2405.05420"]}
{"year":"2024","title":"The Practical Epistemologies of Design and Artificial Intelligence","authors":["W Billingsley - Science & Education, 2024"],"snippet":"This article explores the epistemological trade-offs that practical and technology design fields make by exploring past philosophical discussions of design, practitioner research, and pragmatism. It argues that as technologists apply Artificial …","url":["https://link.springer.com/article/10.1007/s11191-024-00517-z"]}
{"year":"2024","title":"The principal components of meaning, revisited","authors":["C Westbury, M Yang, K Anderson - Psychonomic Bulletin & Review, 2024"],"snippet":"… the Common Crawl corpus (https://commoncrawl.org/), a web-derived corpus. As its name suggests, the model has vectors of length 300. … ://nlp.stanford.edu/projects/glove/), a matrix with vectors of length 300 that was trained on 840 billion tokens from …","url":["https://link.springer.com/article/10.3758/s13423-024-02551-y"]}
{"year":"2024","title":"The Progenitors of the Information Age and the Birth of AI: Introducing the “Political Economy of the Fourth Industrial Revolution”","authors":["V Menaldo"],"snippet":"America’s economy is increasingly fueled by digital devices, machines, and appliances that communicate with each other over the internet, ever-improving algorithms for driverless cars and virtual reality, and generative Artificial Intelligence (AI) …","url":["https://faculty.washington.edu/vmenaldo/Books/Political%20Economy%20of%204th%20Industrial%20Revolution.pdf"]}
{"year":"2024","title":"The research landscape on generative artificial intelligence: a bibliometric analysis of transformer-based models","authors":["G Marchena Sekli - Kybernetes, 2024"],"snippet":"Purpose The aim of this study is to offer valuable insights to businesses and facilitate better understanding on transformer-based models (TBMs), which are among the widely employed generative artificial intelligence (GAI) models, garnering …","url":["https://www.emerald.com/insight/content/doi/10.1108/K-03-2024-0554/full/html"]}
{"year":"2024","title":"The Responsible Foundation Model Development Cheatsheet: A Review of Tools & Resources","authors":["S Longpre, S Biderman, A Albalak, H Schoelkopf… - arXiv preprint arXiv …, 2024"],"snippet":"… These corpora often merge and deduplicate multiple years of common crawl scrapes, or supplement additional sources including biomedical text (PubMed), legal text (Freelaw, … 2023) provides a 3 trillion token, 2023 processed split of …","url":["https://arxiv.org/pdf/2406.16746"]}
{"year":"2024","title":"The Revealed Preferences of Pre-authorized Licenses and Their Ethical Implications for Generative Models","authors":["VM Suriyakumar, P Menell, D Hadfield-Menell…"],"snippet":"This work examines the revealed preferences of creators as reflected in open and quasi-open licensing regimes based on the most commonly used licenses by copyright holders of images in the Creative Commons and copyright holders of code …","url":["https://blog.genlaw.org/pdfs/genlaw_icml2024/75.pdf"]}
{"year":"2024","title":"The Right Prompts for the Job: Repair Code-Review Defects with Large Language Model","authors":["Z Zhao, Z Xu, J Zhu, P Di, Y Yao, X Ma - arXiv preprint arXiv:2312.17485, 2023"],"snippet":"Automatic program repair (APR) techniques have the potential to reduce manual efforts in uncovering and repairing program defects during the code review (CR) process. However, the limited accuracy and considerable time costs associated with …","url":["https://arxiv.org/pdf/2312.17485"]}
{"year":"2024","title":"The Right to Scrap Data on the Internet: From the US Case hiQLabs, Inc. v. LinkedIn Corp. to the ChatGPT Scraping Cases: Differences Between US and EU Law [pre …","authors":["JTS y López - Global Privacy Law Review, 2024"],"snippet":"… a doctor when she was undergoing treatment for a rare genetic condition ended up in the Common Crawl’s archive and LAION’s dataset, and therefore in the GhatGPT datasets (because the Common Crawl is one of the ChatGPT training …","url":["https://kluwerlawonline.com/journalarticle/Global+Privacy+Law+Review/5.1/GPLR2024001"]}
{"year":"2024","title":"The Rise of Generative Artificial Intelligence: Impact on Societies, Economies and Enterprises","authors":["N Kshetri - 2024"],"snippet":"This timely book explores how generative artificial intelligence (GAI) is developing and diffusing, highlighting the diverse impacts this technology is likely to have on economies and societies. It also examines the effects on and the responses of …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=kYs3EQAAQBAJ&oi=fnd&pg=PR1&dq=commoncrawl&ots=mh6g6xHEyE&sig=t0v1cmrPk9WuKIrRpFmkOu7EK7w"]}
{"year":"2024","title":"The Role and Prospects of Using ChatGPT Artificial Intelligence-Based Chatbots in Healthcare Improvement","authors":["NA Mumtaz - ISWOPHA, 2024","NA Mumtaz - … OF INTERNATIONAL SEMINAR AND WORKSHOP ON …"],"snippet":"In the age of digital transformation, healthcare is undergoing a revolution through information technology and artificial intelligence (AI). This article explores the role of AI-based chatbots, like ChatGPT, in healthcare enhancement. Utilizing a literature …","url":["https://healthscience.dinus.ac.id/category/index.php/iswopha/article/download/147/20","https://swopha.dinus.ac.id/wp-content/uploads/sites/6/2024/06/Prosiding-ISBN-FIX2_1.pdf#page=130"]}
{"year":"2024","title":"The role of large language models in agriculture: harvesting the future with LLM intelligence","authors":["TA Shaikh, T Rasool, K Veningston, SM Yaseen - Progress in Artificial Intelligence, 2024"],"snippet":"Significant accomplishments in many agricultural applications during the past decade attest to the fast progress and use of deep learning and machine learning methods in agricultural systems. However, these conventional models have a few …","url":["https://link.springer.com/article/10.1007/s13748-024-00359-4"]}
{"year":"2024","title":"The Science of Data Filtering: Data Curation cannot be Compute Agnostic","authors":["S Goyal, P Maini, ZC Lipton, A Raghunathan, JZ Kolter - ICLR 2024 Workshop on …"],"snippet":"… In fact, we show that even a model trained on *unfiltered common crawl* obtains higher accuracy than that trained on the LAION dataset post 40 or more repetitions. While past research in neural scaling laws has considered web data to be …","url":["https://openreview.net/forum?id=9wzo4EjEGM"]}
{"year":"2024","title":"The science of implicit race bias: Evidence from the Implicit Association Test","authors":["KN Morehouse, MR Banaji - Daedalus, 2024"],"snippet":"Beginning in the mid-1980s, scientific psychology underwent a revolution–the implicit revolution–that led to the development of methods to capture implicit bias: attitudes, stereotypes, and identities that operate without full conscious awareness …","url":["https://www.amacad.org/sites/default/files/publication/downloads/Daedalus_Wi24_05_Morehouse_Banaji.pdf"]}
{"year":"2024","title":"The Self in Action: Narrating Agentic Moments","authors":["S Zilberstein, E Ayala-Hurtado, M Sanchez, D Robey - RSF: The Russell Sage …, 2024"],"snippet":"This article develops a cultural and contextual approach to studying agency that attends to variation in how people narrate their experiences. Drawing on the large-scale, nationally representative American Voices Project data, the article uses …","url":["https://www.rsfjournal.org/content/rsfjss/10/5/118.full.pdf"]}
{"year":"2024","title":"The Shape of Word Embeddings: Recognizing Language Phylogenies through Topological Data Analysis","authors":["O Draganov, S Skiena - arXiv preprint arXiv:2404.00500, 2024"],"snippet":"Word embeddings represent language vocabularies as clouds of $d$-dimensional points. We investigate how information is conveyed by the general shape of these clouds, outside of representing the semantic meaning of each token. Specifically, we …","url":["https://arxiv.org/html/2404.00500v1"]}
{"year":"2024","title":"The Silicone Ceiling: Auditing GPT's Race and Gender Biases in Hiring","authors":["L Armstrong, A Liu, S MacNeil, D Metaxa - arXiv preprint arXiv:2405.04412, 2024"],"snippet":"Large language models (LLMs) are increasingly being introduced in workplace settings, with the goals of improving efficiency and fairness. However, concerns have arisen regarding these models' potential to reflect or exacerbate social biases …","url":["https://arxiv.org/pdf/2405.04412"]}
{"year":"2024","title":"The SlayQA benchmark of social reasoning: testing gender-inclusive generalization with neopronouns","authors":["B Bunzeck, S Zarrieß - Proceedings of the 2nd GenBench Workshop on …, 2024"],"snippet":"… C4 is based on CommonCrawl web dumps that were then cleaned, filtered and deduplicated to certain degrees. RedPajamaData-1T and Dolma also contain considerable portions of CommonCrawl enriched with data from diverse sources …","url":["https://aclanthology.org/2024.genbench-1.3.pdf"]}
{"year":"2024","title":"The Social Impact of Generative LLM-Based AI","authors":["Y Xie, S Avila - arXiv preprint arXiv:2410.21281, 2024"],"snippet":"Liking it or not, ready or not, we are likely to enter a new phase of human history in which Artificial Intelligence (AI) will dominate economic production and social life -- the AI Revolution. Before the actual arrival of the AI Revolution, it is time for us to …","url":["https://arxiv.org/pdf/2410.21281"]}
{"year":"2024","title":"The Sociolinguistic Foundations of Language Modeling","authors":["J Grieve, S Bartl, M Fuoli, J Grafmiller, W Huang… - arXiv preprint arXiv …, 2024"],"snippet":"In this paper, we introduce a sociolinguistic perspective on language modeling. We claim that large language models are inherently models of varieties of language, and we consider how this insight can inform the development and deployment of …","url":["https://arxiv.org/pdf/2407.09241"]}
{"year":"2024","title":"The Tokenization Problem: Understanding Generative AI's Computational Language Bias","authors":["M Asprovska, N Hunter - Ubiquity Proceedings, 2024"],"snippet":"… This paper used the Common Crawl corpus as a stand-in due to its wide linguistic representation, but the actual distribution within the pre-training dataset may differ. The discrepancies between these datasets might significantly influence tokenization …","url":["https://ubiquityproceedings.com/articles/123/files/66cd63cd02dcc.pdf"]}
{"year":"2024","title":"The Trade-off between Performance, Efficiency, and Fairness in Adapter Modules for Text Classification","authors":["MD Bui, K von der Wense - arXiv preprint arXiv:2405.02010, 2024"],"snippet":"… 2019) is derived from 393,423 online biographies in English from the Common Crawl corpus, each including the subject’s occupation and gender. The dataset contains 28 occupations, assuming a binary gender classification. Gender identification …","url":["https://arxiv.org/pdf/2405.02010"]}
{"year":"2024","title":"The use of machine learning and deep learning models in detecting depression on social media: A systematic literature review","authors":["WA Gadzama, D Gabi, MS Argungu, HU Suru - Personalized Medicine in Psychiatry, 2024"],"snippet":"Depression is regarded as one of the world's primary concerns. Recent researchers use artificial intelligence techniques like machine learning and deep learning to identify depressive symptoms automatically. This literature review focuses on using …","url":["https://www.sciencedirect.com/science/article/pii/S2468171724000115"]}
{"year":"2024","title":"The Web Data Commons Schema. org Table Corpora","authors":["R Peeters, A Brinkmann, C Bizer - Companion Proceedings of the ACM on Web …, 2024"],"snippet":"… This paper presented the WDC Schema.org Table Corpora that we extracted from the Common Crawl. To the best of our knowledge, the corpora are the largest public table corpora that contain tables from many different sources which all share a …","url":["https://dl.acm.org/doi/pdf/10.1145/3589335.3651441"]}
{"year":"2024","title":"The Web Is Missing an Essential Part of Infrastructure: An Open Web Index A proposal for building an index of the Web that separates the infrastructure part of the …","authors":["D Lewandowski"],"snippet":"The web as it currently exists would not be possible without search engines. They are an integral part of the Web and can also be seen as a part of the Web’s infrastructure. Google alone now serves over two trillion search queries per year. 11 …","url":["https://cacm.acm.org/opinion/the-web-is-missing-an-essential-part-of-infrastructure/"]}
{"year":"2024","title":"The wompom","authors":["RH Baayen - Corpus Linguistics and Linguistic Theory, 2024"],"snippet":"In this essay, I reflect on the past, present, and future of corpus linguistics. My own research has focused primarily on morphology, the mental lexicon, and lexical processing. A consequence of this narrow, myopic focus on just a tiny part of the rich …","url":["https://www.degruyter.com/document/doi/10.1515/cllt-2024-0053/html"]}
{"year":"2024","title":"The work of art in the age of artificial intelligibility","authors":["J McLoughlin - AI & SOCIETY, 2024"],"snippet":"The emergence of complex deep-learning models capable of producing novel images on a practically innumerable number of subjects and in an equally wide variety of artistic styles is beginning to highlight serious inadequacies in the ethical …","url":["https://link.springer.com/article/10.1007/s00146-023-01845-4"]}
{"year":"2024","title":"The Zamba2 Suite: Technical Report","authors":["P Glorioso, Q Anthony, Y Tokpanov, A Golubeva… - arXiv preprint arXiv …, 2024"],"snippet":"In this technical report, we present the Zamba2 series -- a suite of 1.2B, 2.7B, and 7.4B parameter hybrid Mamba2-transformer models that achieve state of the art performance against the leading open-weights models of their class, while …","url":["https://arxiv.org/pdf/2411.15242"]}
{"year":"2024","title":"Themes and sentiments in conversations about food waste on Twitter: Proposal of a framework using neural topic modeling","authors":["MW Barbosa, A Gomes - Food Quality and Preference, 2024"],"snippet":"… In this database, Twitter data was extracted from CommonCrawl. This method resulted in a collection spanning 80,000 distinct users. Historical snapshots from CommonCrawl, which spanned two years, were also considered to augment the …","url":["https://www.sciencedirect.com/science/article/pii/S0950329324002131"]}
{"year":"2024","title":"Theoretical and Methodological Framework for Studying Texts Produced by Large Language Models","authors":["J Milička - arXiv preprint arXiv:2408.16740, 2024"],"snippet":"This paper addresses the conceptual, methodological and technical challenges in studying large language models (LLMs) and the texts they produce from a quantitative linguistics perspective. It builds on a theoretical framework that …","url":["https://arxiv.org/pdf/2408.16740"]}
{"year":"2024","title":"Think Carefully and Check Again! Meta-Generation Unlocking LLMs for Low-Resource Cross-Lingual Summarization","authors":["Z Li, Y Wang, B Hooi, Y Cai, N Cheung, N Peng… - arXiv preprint arXiv …, 2024"],"snippet":"… We consider the data ratio from the CommonCrawl corpus1 and its intersection with two datasets, aligning with the languages used in the previous … 1http://commoncrawl.org 2https://github.com/csebuetnlp/xl-sum/tree/ master/multilingual_rouge_scoring 3https://github.com/Tiiiger/…","url":["https://arxiv.org/pdf/2410.20021"]}
{"year":"2024","title":"Think&Cite: Improving Attributed Text Generation with Self-Guided Tree Search and Progress Reward Modeling","authors":["J Li, HT Ng - arXiv preprint arXiv:2412.14860, 2024"],"snippet":"Despite their outstanding capabilities, large language models (LLMs) are prone to hallucination and producing factually incorrect information. This challenge has spurred efforts in attributed text generation, which prompts LLMs to generate content …","url":["https://arxiv.org/pdf/2412.14860"]}
{"year":"2024","title":"Threat Modelling and Risk Analysis for Large Language Model (LLM)-Powered Applications","authors":["SB Tete - arXiv preprint arXiv:2406.11007, 2024"],"snippet":"The advent of Large Language Models (LLMs) has revolutionized various applications by providing advanced natural language processing capabilities. However, this innovation introduces new cybersecurity challenges. This paper …","url":["https://arxiv.org/pdf/2406.11007"]}
{"year":"2024","title":"THROUGH THE LENS OF WEB ARCHIVES","authors":["MS Weber - The Routledge Companion to Transnational Web …, 2024"],"snippet":"Information ecosystems are a central component of modern society, and increasingly a critical component of our social fabric. In the past 50 years, however, these networks of media and other information sources have become incredibly …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=RLYyEQAAQBAJ&oi=fnd&pg=PA199&dq=commoncrawl&ots=ebVn40Yl74&sig=TAL16juUi0AEYMHtO-_GWIjoSHg"]}
{"year":"2024","title":"TiC-LM: A Multi-Year Benchmark for Continual Pretraining of Language Models","authors":["J Li, M Armandpour, SI Mirzadeh, S Mehta, V Shankar… - NeurIPS 2024 Workshop on …"],"snippet":"… Figure 1: (Left) Total number of tokens per month in our TiC-CommonCrawl. We draw training sets from a tenth of the data in each month … timesteps, we consider training on a generic web-crawl (ie, Common Crawl) 46 spanning 114 different …","url":["https://openreview.net/pdf?id=PpSDVE5rAy"]}
{"year":"2024","title":"Time for a Pause: Without Effective Public Oversight, AI in Schools Will Do More Harm Than Good.","authors":["B Williamson, A Molnar, F Boninger - 2024"],"snippet":"Public education is a public and private good essential to democratic civic life. The public must, therefore, be able to provide meaningful direction over schools through transparent democratic governance structures. And yet artificial intelligence (AI) 1 …","url":["https://nepc.colorado.edu/sites/default/files/publications/PB%20Williamson_0.pdf"]}
{"year":"2024","title":"Time Machine GPT","authors":["F Drinkall, E Rahimikia, JB Pierrehumbert, S Zohren - arXiv preprint arXiv:2404.18543, 2024"],"snippet":"… To scale to even larger models, processing the annual Common Crawl datasets is a necessary step, though the dataset has proved problematic due to its scale and lack of … Aside from this, cleaning Common Crawl would also demand significant …","url":["https://arxiv.org/pdf/2404.18543"]}
{"year":"2024","title":"Timely Quality Problem Resolution in Peer-Production Systems: The Impact of Bots, Policy Citations, and Contributor Experience","authors":["V Mindel, A Aaltonen, A Rai, L Mathiassen, W Jabr - Information Systems Research, 2024"],"snippet":"Although online peer-production systems have proven to be effective in producing high-quality content, their open call for participation makes them susceptible to ongoing quality problems. A key concern is that the problems should be addressed …","url":["https://pubsonline.informs.org/doi/abs/10.1287/isre.2020.0485"]}
{"year":"2024","title":"TinyLLM: A Framework for Training and Deploying Language Models at the Edge Computers","authors":["SV Kandala, P Medaranga, A Varshney - arXiv preprint arXiv:2412.15304, 2024"],"snippet":"… Specifically, we utilized the Fineweb dataset [39], selecting 9 billion tokens from a collection of over 15 trillion tokens compiled from CommonCrawl dumps since 2013. Additionally, we incorporated the SHL dataset [18], which contains annotated data …","url":["https://arxiv.org/pdf/2412.15304"]}
{"year":"2024","title":"To Code, or Not To Code? Exploring Impact of Code in Pre-training","authors":["V Aryabumi, Y Su, R Ma, A Morisot, I Zhang, A Locatelli… - arXiv preprint arXiv …, 2024"],"snippet":"Including code in the pre-training data mixture, even for models not specifically designed for code, has become a common practice in LLMs pre-training. While there has been anecdotal consensus among practitioners that code data plays a vital role …","url":["https://arxiv.org/pdf/2408.10914"]}
{"year":"2024","title":"To store or not: Online cost optimization for running big data jobs on the cloud","authors":["X Fu, L Pan, S Liu - Future Generation Computer Systems, 2024"],"snippet":"As businesses increasingly rely on cloud-based big data analytics services to drive insights, reducing the cost of storing and analyzing large volumes of data in the cloud has become a major concern. During the execution of big data analysis jobs …","url":["https://www.sciencedirect.com/science/article/pii/S0167739X24000803"]}
{"year":"2024","title":"TO WHOM DOES THE WORLD BELONG?","authors":["A Hartley - Boston Review, 2024"],"snippet":"… Indeed, crawls contain enormous amounts of copyrighted information; the Common Crawl alone, a standard repository maintained by a nonprofit and used to train many LLMs, contains most of b-ok.org, a huge repository of pirated ebooks that …","url":["https://search.ebscohost.com/login.aspx?direct=true&profile=ehost&scope=site&authtype=crawler&jrnl=07342306&asa=N&AN=181264664&h=DA2%2B6xk1XV1I104kxogXez9%2F0P4%2BjGjmnqy8yaM1BrTWD8n1PSPnVXq4CouwDEGbBVt9bGdKLXdBVGIzcuj9SQ%3D%3D&crl=c"]}
{"year":"2024","title":"TOFU: A Task of Fictitious Unlearning for LLMs","authors":["P Maini, Z Feng, A Schwarzschild, ZC Lipton, JZ Kolter - arXiv preprint arXiv …, 2024"],"snippet":"… LLMs trained on Common Crawl data1 may be able to correctly answer factual questions about this person and they may wish to have their data removed from an LLM. In fact, regulations around the Right to be Forgotten that focus on this situation …","url":["https://arxiv.org/pdf/2401.06121"]}
{"year":"2024","title":"Tokenization and Morphology in Multilingual Language Models: A~ Comparative Analysis of mT5 and ByT5","authors":["TA Dang, L Raviv, L Galke - arXiv preprint arXiv:2410.11627, 2024"],"snippet":"Morphology is a crucial factor for multilingual language modeling as it poses direct challenges for tokenization. Here, we seek to understand how tokenization influences the morphological knowledge encoded in multilingual language models …","url":["https://arxiv.org/pdf/2410.11627"]}
{"year":"2024","title":"TOMGPT: Reliable Text-Only Training Approach for Cost-Effective Multi-modal Large Language Model","authors":["Y Chen, Q Wang, S Wu, Y Gao, T Xu, Y Hu - ACM Transactions on Knowledge …, 2024"],"snippet":"… For instance, c4 [37] dataset, a colossal and cleaned version of the web crawl corpus from Common Crawl, serves as a suitable option. Since the CLIP text encoder has limitations in processing long text, we subdivided the text in the c4 …","url":["https://dl.acm.org/doi/pdf/10.1145/3654674"]}
{"year":"2024","title":"Tonirodriguez at CheckThat! 2024: Is it Possible to Use Zero-Shot Cross-Lingual Methods for Subjectivity Detection in Low-Resources Languages?","authors":["A Rodríguez, E Golobardes, J Suau - 2024"],"snippet":"… on 2.5TB of filtered CommonCrawl data containing 100 languages. Following the work of XLM and RoBERTa, the XLM-RoBERTa or XLM-R model takes multilingual pretraining one step further by massively upscaling the training data [19]. Using the …","url":["https://ceur-ws.org/Vol-3740/paper-54.pdf"]}
{"year":"2024","title":"Tooling for big data extraction","authors":["R Beilich - HPI Future SOC Lab–Proceedings 2020, 2024"],"snippet":"… , provided by Common Crawl, what may causes libraries to crumble and others to rise. … The Common Crawl Foundation created “an open repository of web crawl data that can be … [5] For the Common Crawl dataset this results in three types of …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=T7chEQAAQBAJ&oi=fnd&pg=PA131&dq=commoncrawl&ots=FOSGIq3qSE&sig=sEPIohlICTxBrVyEWDUlz6BPyts"]}
{"year":"2024","title":"Topic Modeling for Auditing Purposes in the Banking Sector","authors":["A Giaconia, V Chiariello, S Giannuzzi, M Passarotti - 2024"],"snippet":"This study explores the application of topic modeling techniques for auditing purposes in the banking sector, focusing on the analysis of reviews of anti-money laundering alerts. We compare three topic modeling algorithms: Latent Dirichlet …","url":["https://clic2024.ilc.cnr.it/wp-content/uploads/2024/12/112_main_short.pdf"]}
{"year":"2024","title":"Topic Modelling Swahili Using LDA and Contextualized Embeddings","authors":["DW Kahenya, W Mwangi, R Rimiru - 2024 Intelligent Methods, Systems, and …, 2024"],"snippet":"… The XLMRoBERTa model, developed by [19] in their study on Unsupervised Cross-lingual Representation Learning at Scale, was trained on 2.5TB of filtered CommonCrawl data containing 100 languages. Flair framework [20] was used to …","url":["https://ieeexplore.ieee.org/abstract/document/10652736/"]}
{"year":"2024","title":"Topology Only Pre-Training: Towards Generalised Multi-Domain Graph Models","authors":["AO Davies, R Green, NS Ajmeri, TMS Filho"],"snippet":"The principal benefit of unsupervised representation learning is that a pre-trained model can be fine-tuned where data or labels are scarce. Existing approaches for graph representation learning are domain specific, maintaining consistent node and …","url":["https://www.researchgate.net/profile/Alex-Davies-32/publication/375756323_Topology_Only_Pre-Training_Towards_Generalised_Multi-Domain_Graph_Models/links/674dac2a359dcb4d9d4b733f/Topology-Only-Pre-Training-Towards-Generalised-Multi-Domain-Graph-Models.pdf"]}
{"year":"2024","title":"TorchTitan: One-stop PyTorch native solution for production ready LLM pre-training","authors":["W Liang, T Liu, L Wright, W Constable, A Gu… - arXiv preprint arXiv …, 2024"],"snippet":"The development of large language models (LLMs) has been instrumental in advancing state-of-the-art natural language processing applications. Training LLMs with billions of parameters and trillions of tokens require sophisticated distributed …","url":["https://arxiv.org/pdf/2410.06511"]}
{"year":"2024","title":"Toward a Holistic Evaluation of Robustness in CLIP Models","authors":["W Tu, W Deng, T Gedeon - arXiv preprint arXiv:2410.01534, 2024"],"snippet":"Contrastive Language-Image Pre-training (CLIP) models have shown significant potential, particularly in zero-shot classification across diverse distribution shifts. Building on existing evaluations of overall classification robustness, this work aims …","url":["https://arxiv.org/pdf/2410.01534"]}
{"year":"2024","title":"Toward Better Education Quality through Students' Sentiment Analysis Using AutoML","authors":["C Simionescu, D Marcu, MS Măciucă - … . Broad Research in Artificial Intelligence and …, 2024"],"snippet":"Sentiment analysis from students' interactions with learning environments is a topic of interest for researchers in the field of education because it can make important contributions to improving the quality of instructional processes through …","url":["https://edusoft.ro/brain/index.php/brain/article/download/1548/1812"]}
{"year":"2024","title":"Toward Inference-optimal Mixture-of-Expert Large Language Models","authors":["L Yun, Y Zhuang, Y Fu, EP Xing, H Zhang - arXiv preprint arXiv:2404.02852, 2024"],"snippet":"Mixture-of-Expert (MoE) based large language models (LLMs), such as the recent Mixtral and DeepSeek-MoE, have shown great promise in scaling model size without suffering from the quadratic growth of training cost of dense transformers …","url":["https://arxiv.org/html/2404.02852v1"]}
{"year":"2024","title":"Toward Open-Source AI Systems as Digital Public Goods: Definitions, Hopes and Challenges","authors":["L Gimpel - New Frontiers in Science in the Era of AI"],"snippet":"… Training data might be proprietary, free but not open as in Google Trends, have unclear provenance or feature copyright-protected data (including the massive “open” datasets scrapped from the web used to train generative AI models such as …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=tfEoEQAAQBAJ&oi=fnd&pg=PA129&dq=commoncrawl&ots=yF0ByLlGn1&sig=RvpxDq0tehsxE65QYFknuJstBdc"]}
{"year":"2024","title":"Toward Robust Arabic AI-Generated Text Detection: Tackling Diacritics Challenges","authors":["H Alshammari, K Elleithy - Information, 2024"],"snippet":"Current AI detection systems often struggle to distinguish between Arabic human-written text (HWT) and AI-generated text (AIGT) due to the small marks present above and below the Arabic text called diacritics. This study introduces robust Arabic text …","url":["https://www.mdpi.com/2078-2489/15/7/419"]}
{"year":"2024","title":"Toward Robust, Reliable, and Generalizable Models for Tabular Data","authors":["J Gardner - 2024"],"snippet":"Tabular data–spreadsheet-type data with rows and columns–is widely used across many domains and real-world applications, from finance to healthcare to natural and social sciences. However, tabular data modeling has received far less attention, and …","url":["https://search.proquest.com/openview/9cc4f4c12499fa9cb718e61e19fe1d7f/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
{"year":"2024","title":"Toward Understanding Training Data Attacks In Artificial Intelligence And Machine Learning Models","authors":["AW Pilbeam, JS White"],"snippet":"… With all of these changes, the most accessible source of training data continues to be open source data, such as the Common Crawl datasets(Tom B. Brown, 2020) and others that have been made publicly available. Only extremely large technology …","url":["https://www.researchgate.net/profile/Joshua-White-26/publication/381313907_Toward_Understanding_Training_Data_Attacks_In_Artificial_Intelligence_And_Machine_Learning_Models/links/66687663de777205a325424e/Toward-Understanding-Training-Data-Attacks-In-Artificial-Intelligence-And-Machine-Learning-Models.pdf"]}
{"year":"2024","title":"Towards a Framework for Openness in Foundation Models: Proceedings from the Columbia Convening on Openness in Artificial Intelligence","authors":["A Basdevant, C François, V Storchan, K Bankston… - arXiv preprint arXiv …, 2024"],"snippet":"Over the past year, there has been a robust debate about the benefits and risks of open sourcing foundation models. However, this discussion has often taken place at a high level of generality or with a narrow focus on specific technical attributes. In …","url":["https://arxiv.org/pdf/2405.15802"]}
{"year":"2024","title":"Towards a Scalable Geoparsing Approach for the Web","authors":["SM Farzana, T Hecking - 2024"],"snippet":"The ongoing surge in web data generation and storage, coupled with embedded geographic information, holds immense potential for enhancing search applications across diverse domains. However, extracting geographic information for further …","url":["https://ceur-ws.org/Vol-3683/paper4.pdf"]}
{"year":"2024","title":"Towards a small language model powered chain‐of‐reasoning for open‐domain question answering","authors":["J Roh, M Kim, K Bae - ETRI Journal, 2024"],"snippet":"… Unlike the ONUS approach [10], which extracts simple sub-question examples from a Common Crawl, our method emphasizes the autonomous generation of a dataset without human intervention facilitated by the use of LLMs. Consequently, we …","url":["https://onlinelibrary.wiley.com/doi/abs/10.4218/etrij.2023-0355"]}
{"year":"2024","title":"Towards a sociology of recurrent events. Constellations of cultural change around Eurovision in 18 countries (1981–2021)","authors":["L Carbone, J Mijs, T van Dooremalen, S Daenekindt - Poetics, 2024"],"snippet":"… First, we used CMD with a corpus that was pre-trained on Common Crawl data using fastText English embeddings. Common Crawl is a vast and heterogeneous source of information that crawls web archives and freely provides their data to the …","url":["https://www.sciencedirect.com/science/article/pii/S0304422X24000287"]}
{"year":"2024","title":"Towards a Unified Terminology: A study on Siemens Energy Technical Information Systems","authors":["S Adhami - 2024"],"snippet":"… The dataset includes the Common Crawl archive, an extensive collection of web-extracted text [5], as well as the WebText dataset, books … GPT-3’s training includes a staggering 400 billion tokens from Common Crawl, 19 billion from WebText, 12 …","url":["https://www.diva-portal.org/smash/get/diva2:1886644/FULLTEXT01.pdf"]}
{"year":"2024","title":"Towards adaptive support for self‐regulated learning of causal relations: Evaluating four Dutch word vector models","authors":["HJ Pijeira‐Díaz, S Braumann, J van de Pol, T van Gog… - British Journal of …, 2024"],"snippet":"Advances in computational language models increasingly enable adaptive support for self‐regulated learning (SRL) in digital learning environments (DLEs; eg, via automated feedback). However, the accuracy of those models is a common concern …","url":["https://bera-journals.onlinelibrary.wiley.com/doi/pdf/10.1111/bjet.13431"]}
{"year":"2024","title":"Towards Automated Solution Recipe Generation for Industrial Asset Management with LLM","authors":["N Zhou, D Patel, S Lin, F O'Donncha - arXiv preprint arXiv:2407.18992, 2024"],"snippet":"This study introduces a novel approach to Industrial Asset Management (IAM) by incorporating Conditional-Based Management (CBM) principles with the latest advancements in Large Language Models (LLMs). Our research introduces an …","url":["https://arxiv.org/pdf/2407.18992"]}
{"year":"2024","title":"Towards automatic question generation using pre-trained model in academic field for Bahasa Indonesia","authors":["D Suhartono, MRN Majiid, R Fredyan - Education and Information Technologies, 2024"],"snippet":"… This model is a potent tool for transforming our text data into numerical representations because it was previously trained on the sizable Common Crawl Dataset in Indonesian. These embeddings are essential for later modeling and …","url":["https://link.springer.com/article/10.1007/s10639-024-12717-9"]}
{"year":"2024","title":"Towards Better Language Models: Algorithms, Architectures, and Applications","authors":["Q Wu - 2024"],"snippet":"This thesis explores the advancement of language models by focusing on three important perspectives: Algorithms, Architectures, and Applications. We aim to improve the performance, efficiency, and practical usage of these language models …","url":["https://search.proquest.com/openview/9a13c09922415abc0335be4afbb39cf9/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
{"year":"2024","title":"Towards Better Statistical Understanding of Watermarking LLMs","authors":["Z Cai, S Liu, H Wang, H Zhong, X Li - arXiv preprint arXiv:2403.13027, 2024"],"snippet":"In this paper, we study the problem of watermarking large language models (LLMs). We consider the trade-off between model distortion and detection ability and formulate it as a constrained optimization problem based on the green-red algorithm …","url":["https://arxiv.org/html/2403.13027v1"]}
{"year":"2024","title":"Towards Building Multilingual Language Model for Medicine","authors":["P Qiu, C Wu, X Zhang, W Lin, H Wang, Y Zhang… - arXiv preprint arXiv …, 2024"],"snippet":"In this paper, we aim to develop an open-source, multilingual language model for medicine, that the benefits a wider, linguistically diverse audience from different regions. In general, we present the contribution from the following aspects: first, for …","url":["https://arxiv.org/pdf/2402.13963"]}
{"year":"2024","title":"Towards Chapterisation of Podcasts Detection of Host and Structuring Questions in Radio Transcripts","authors":["M Piguet - 2024"],"snippet":"This Master thesis investigates the application of Bidirectional Encoder Representations from Transformers (BERT) on podcast to identify the host and detect structuring questions within each episode. This research is conducted on an …","url":["https://infoscience.epfl.ch/record/310625/files/Towards_Chapterisation_of_Podcasts___Master_Thesis___28_03_2024.pdf"]}
{"year":"2024","title":"Towards Cross-Lingual LLM Evaluation for European Languages","authors":["K Thellmann, B Stadler, M Fromm, JS Buschhoff… - arXiv preprint arXiv …, 2024"],"snippet":"… Section 4.2 shows the connection between the proportion of languages in the CommonCrawl dataset and the performance of the current best open weights models. Lastly, Section 4.3 highlights how the performance of the models depend on the …","url":["https://arxiv.org/pdf/2410.08928"]}
{"year":"2024","title":"Towards Data Governance of Frontier AI Models","authors":["J Hausenloy, D McClements, M Thakur"],"snippet":"Data is essential to train and fine-tune today’s frontier artificial intelligence (AI) models and to develop future ones. To date, academic, legal, and regulatory work has primarily addressed how data can directly harm consumers and creators, such …","url":["https://jasonhausenloy.com/data.pdf"]}
{"year":"2024","title":"Towards Data-efficient Machine Learning Systems","authors":["N Sachdeva - 2024"],"snippet":"The amount of data available to train modern machine learning systems has been increasing rapidly, so much so that we're using, eg, entirety of the publicly available text data to train state-of-the-art (SoTA) large language models (LLMs), interaction …","url":["https://escholarship.org/content/qt8nb955b8/qt8nb955b8.pdf"]}
{"year":"2024","title":"Towards detection and explanation of factual inconsistencies","authors":["T Raha - 2024"],"snippet":"Factual inconsistencies in text, which include a range of errors from minor inaccuracies to substantial distortions, present a significant challenge in the realm of information dissemination. These inconsistencies, whether unintentional or the …","url":["https://cdn.iiit.ac.in/cdn/web2py.iiit.ac.in/research_centres/publications/download/mastersthesis.pdf.8ef5c54c01b01a0e.746865736973202835292e706466.pdf"]}
{"year":"2024","title":"Towards Disfluency Annotated Corpora for Indian Languages","authors":["C Kochar, V Mujadia, P Mishra, DM Sharma"],"snippet":"In the natural course of spoken language, individuals often engage in thinking and self-correction during speech production. These instances of interruption or correction are commonly referred to as disfluencies. When preparing data for …","url":["http://sanskrit.jnu.ac.in/conf/wildre7/pdf/2024.wildre-1.1.pdf"]}
{"year":"2024","title":"Towards Effective Time-Aware Language Representation: Exploring Enhanced Temporal Understanding in Language Models","authors":["J Wang, A Jatowt, Y Cai - arXiv preprint arXiv:2406.01863, 2024"],"snippet":"In the evolving field of Natural Language Processing, understanding the temporal context of text is increasingly crucial. This study investigates methods to incorporate temporal information during pre-training, aiming to achieve effective time-aware …","url":["https://arxiv.org/pdf/2406.01863"]}
{"year":"2024","title":"Towards Enhanced Information Access in Finance: A Dataset for Table Structure Understanding in Annual Securities Reports","authors":["K Kadowaki, Y Kimura, H Ototake - … for Financial Engineering and Economics (CIFEr), 2024"],"snippet":"… The WDC Web Table Corpus 2015 [8] structured 230 million tables in web pages from CommonCrawl by classifying them into categories such as relational, entity, matrix, and other, as well as identifying the presence and location of headers and …","url":["https://ieeexplore.ieee.org/abstract/document/10772986/"]}
{"year":"2024","title":"Towards Estimating Personal Values in Song Lyrics","authors":["AM Demetriou, J Kim, S Manolios, C Liem - arXiv preprint arXiv:2408.12694, 2024"],"snippet":"Most music widely consumed in Western Countries contains song lyrics, with US samples reporting almost all of their song libraries contain lyrics. In parallel, social science theory suggests that personal values - the abstract goals that guide our …","url":["https://arxiv.org/pdf/2408.12694"]}
{"year":"2024","title":"Towards Federated Large Language Models: Motivations, Methods, and Future Directions","authors":["Y Cheng, W Zhang, Z Zhang, C Zhang, S Wang, S Mao - … Communications Surveys & …, 2024"],"snippet":"Large Language Models (LLMs), such as LLaMA and GPT-4, have transformed the paradigm of natural language comprehension and generation. Despite their impressive performance, these models still face certain challenges, including the …","url":["https://ieeexplore.ieee.org/abstract/document/10759678/"]}
{"year":"2024","title":"Towards Green AI. A methodological survey of the scientific literature","authors":["E Barbierato, A Gatti - IEEE Access, 2024"],"snippet":"The pervasive deployment of Deep Learning models has recently prompted apprehensions regarding their ecological footprint, owing to the exorbitant levels of energy consumption necessitated by the training and inference processes. The term …","url":["https://ieeexplore.ieee.org/iel7/6287639/6514899/10418137.pdf"]}
{"year":"2024","title":"Towards interactive information seeking: conversational question answering","authors":["Y Li - 2024"],"snippet":"… To further advance the field, additional conversational search benchmarks have been introduced, such as ORQuAC [93], which extends CAsT and QuAC with more conversations constructed from Natural Questions and additional passages from …","url":["https://theses.lib.polyu.edu.hk/bitstream/200/12892/3/7339.pdf"]}
{"year":"2024","title":"Towards Large Language Models for Everyone: Instruction Following, Knowledge Retrieval and Multilingualism","authors":["XV Lin - 2024"],"snippet":"Large language models (LLMs) have significantly advanced the field of Natural Language Processing and demonstrated the potential to fuel a variety of AI applications. Nonetheless, building them in a way that maximally benefits the very …","url":["https://search.proquest.com/openview/85e6510c39ed33a126be9d258775afa5/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
{"year":"2024","title":"Towards Machine Translation Based on Monolingual Texts","authors":["I Kvapilíková - 2024"],"snippet":"… The CommonCrawl1 project carries out periodic web crawls and publishes the crawled data in an open … the CommonCrawl corpus. For example, the open source OSCAR2 project compiled a large multilingual corpus by language …","url":["https://dspace.cuni.cz/bitstream/handle/20.500.11956/188428/140116518.pdf?sequence=1"]}
{"year":"2024","title":"Towards More Factual Large Language Models: Parametric and Non-parametric Approaches","authors":["Z Jiang - 2024"],"snippet":"Large language models (LLMs) are increasingly important in assisting people to access information, ranging from simple factoid questions such as “where is the world’s largest ice sheet located” to complex questions that require accessing real-time …","url":["https://kilthub.cmu.edu/ndownloader/files/47721265"]}
{"year":"2024","title":"Towards Privacy Preserving LLMs Training","authors":["B Buesser - Large Language Models in Cybersecurity: Threats …, 2024"],"snippet":"Privacy-preserving training of machine learning models aims to avoid or minimize (mitigate) the exact or similar reproduction (leakage) of information contained in the training data. This chapter introduces pre-processing methods (filtering and de-duplication) …","url":["https://link.springer.com/content/pdf/10.1007/978-3-031-54827-7_19.pdf"]}
{"year":"2024","title":"Towards quantifying politicization in foreign aid project reports","authors":["S Wang, G Eggers, ART Georgiadis, TA Đo, L Gontard… - Proceedings of the Second …, 2024"],"snippet":"We aim to develop a metric of politicization by investigating whether this concept can be operationalized computationally using document embeddings. We are interested in measuring the extent to which foreign aid is politicized. Textual reports of foreign …","url":["https://aclanthology.org/2024.politicalnlp-1.9.pdf"]}
{"year":"2024","title":"Towards Region-aware Bias Evaluation Metrics","authors":["A Borah, A Garimella, R Mihalcea - arXiv preprint arXiv:2406.16152, 2024"],"snippet":"… To measure biases in different data domains and regions, we extract region-aware topics using the GeoWAC dataset which spans Common Crawl separated by regions, and create a WEAT-style evaluation setup using these topics. Data. We consider two …","url":["https://arxiv.org/pdf/2406.16152"]}
{"year":"2024","title":"Towards reliability and interactive debugging for large language models","authors":["B Paranjape - 2024"],"snippet":"Large language models (LLMs) have permeated our everyday lives and are used in critical decision-making scenarios that can affect millions of people. Despite their impressive progress, model deficiencies may result in exacerbating harmful biases …","url":["https://digital.lib.washington.edu/researchworks/bitstream/handle/1773/51339/Paranjape_washington_0250E_26573.pdf?sequence=1"]}
{"year":"2024","title":"Towards Robust Evaluation: A Comprehensive Taxonomy of Datasets and Metrics for Open Domain Question Answering in the Era of Large Language Models","authors":["A Srivastava, A Memon - arXiv preprint arXiv:2406.13232, 2024"],"snippet":"Open Domain Question Answering (ODQA) within natural language processing involves building systems that answer factual questions using large-scale knowledge corpora. Recent advances stem from the confluence of several factors …","url":["https://arxiv.org/pdf/2406.13232"]}
{"year":"2024","title":"Towards Safe Multilingual Frontier AI","authors":["A Kanepajs, V Ivanov, R Moulange - arXiv preprint arXiv:2409.13708, 2024"],"snippet":"… Table 2: Logistic regression results: relationship between dependent variable and log(CommonCrawl corpus share). 2400 observations across 24 languages (100 per language) for each regression, with Holm–Bonferroni adjusted p-values. Adjusted …","url":["https://arxiv.org/pdf/2409.13708"]}
{"year":"2024","title":"Towards Systematic Monolingual NLP Surveys: GenA of Greek NLP","authors":["J Bakagianni, K Pouli, M Gavriilidou, J Pavlopoulos - arXiv preprint arXiv:2407.09861, 2024"],"snippet":"Natural Language Processing (NLP) research has traditionally been predominantly focused on English, driven by the availability of resources, the size of the research community, and market demands. Recently, there has been a noticeable shift …","url":["https://arxiv.org/pdf/2407.09861"]}
{"year":"2024","title":"Towards the automatic creation of NER systems for new domains","authors":["E Matos, M Rodrigues, A Teixeira - Proceedings of the 16th International Conference …, 2024"],"snippet":"… ner-roberta (ROBERTA): xlm-roberta-base-trimmed-pt-600002 model based in xlm-roberta-base, pretrained on 2.5TB of filtered CommonCrawl data containing 100 languages. It was introduced in the paper Unsupervised Crosslingual …","url":["https://aclanthology.org/2024.propor-1.22.pdf"]}
{"year":"2024","title":"Towards the Machine Translation of Scientific Neologisms","authors":["P Lerner, F Yvon - 2024"],"snippet":"… OSCAR-fr 22.01 is a French cleaned subset of Common Crawl, which was also partly used to train BLOOM. It consists of 42 billion words (382 GB). Figure 4 shows that 15.8% of FranceTerme target (French) terms do not appear even a single time in …","url":["https://hal.science/hal-04835653/document"]}
{"year":"2024","title":"Towards Understanding Systems Trade-offs in Retrieval-Augmented Generation Model Inference","authors":["M Shen, M Umar, K Maeng, GE Suh, U Gupta - arXiv preprint arXiv:2412.11854, 2024"],"snippet":"… We construct our retrieval indices using a 100M document chunk subset of Common Crawl [18]. Each document chunk is made up of 100 tokens, encoded into a vector. We explore three different dense retriever indices: an accuracyoriented one …","url":["https://arxiv.org/pdf/2412.11854"]}
{"year":"2024","title":"Towards Video Understanding through Language in Real-life Settings","authors":["S Castro - 2024"],"snippet":"Videos have become an integral part of our daily lives, with a rapidly growing number on YouTube, Netflix, and TikTok serving as testimony to their widespread popularity. Behind the simplicity of their interfaces and user experiences, the …","url":["https://deepblue.lib.umich.edu/bitstream/handle/2027.42/194696/sacastro_1.pdf?sequence=1"]}
{"year":"2024","title":"Towards Website X-Ray for Europe's Municipalities: Unveiling Digital Transformation with Multimodal Embeddings","authors":["J Gerber, B Kreiner, J Saxer, A Weiler - International Conference on Information …, 2025"],"snippet":"Local governments are going digital! To track their progress, researchers want to analyze their websites. This study explores finding these websites and understanding their content. Three methods for website discovery were compared …","url":["https://link.springer.com/chapter/10.1007/978-3-031-78090-5_11"]}
{"year":"2024","title":"Toxic Memes Recognition Through with Multimodal Bidirectional Cross-Attention","authors":["A Hashim, N Coleman, J Roy - 2024"],"snippet":"… Common Crawl (CC) Common Crawl is a large-scale web corpus that provides diverse and extensive data, capturing a wide range of topics and domains. Models pre-trained on Common Crawl benefit from exposure to varied language usages …","url":["https://www.preprints.org/frontend/manuscript/bb8946b334869dadbb95184922f16766/download_pub"]}
{"year":"2024","title":"Toxicity Detection for Free","authors":["Z Hu, J Piet, G Zhao, J Jiao, D Wagner - arXiv preprint arXiv:2405.18822, 2024"],"snippet":"… An analysis of undesirable content in the common crawl corpus. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 2 …","url":["https://arxiv.org/pdf/2405.18822"]}
{"year":"2024","title":"Toxicity Mitigation with Retrieval-Augmented Language Models applied to English and Portuguese Text Generation","authors":["LA Pozzobon - 2024"],"snippet":"Grandes modelos de linguagem alcançaram capacidades impressionantes de geração e compreensão textual através de treino autosupervisionado ao longo dos anos. Enquanto aprendem a prever a próxima palavra, esses modelos mapeiam o …","url":["https://repositorio.unicamp.br/Busca/Download?codigoArquivo=574041&tipoMidia=0"]}
{"year":"2024","title":"Toxicity of the Commons: Curating Open-Source Pre-Training Data","authors":["C Arnett, E Jones, IP Yamshchikov, PC Langlais - arXiv preprint arXiv:2410.22587, 2024"],"snippet":"Open-source large language models are becoming increasingly available and popular among researchers and practitioners. While significant progress has been made on open-weight models, open training data is a practice yet to be adopted by …","url":["https://arxiv.org/pdf/2410.22587"]}
{"year":"2024","title":"Training and evaluation of vector models for Galician","authors":["M Garcia - Language Resources and Evaluation, 2024"],"snippet":"This paper presents a large and systematic assessment of distributional models for Galician. To this end, we have first trained and evaluated static word embeddings (eg, word2vec, GloVe), and then compared their performance with that of current …","url":["https://link.springer.com/article/10.1007/s10579-024-09740-0"]}
{"year":"2024","title":"Training BERT Models to Carry over a Coding System Developed on One Corpus to Another","authors":["D Galambos, P Zsamboki - Proceedings of the 2024 Joint International Conference …, 2024"],"snippet":"This paper describes how we train BERT models to carry over a coding system developed on the paragraphs of a Hungarian literary journal to another. The aim of the coding system is to track trends in the perception of literary translation around …","url":["https://aclanthology.org/2024.lrec-main.1452.pdf"]}
{"year":"2024","title":"Training Bilingual LMs with Data Constraints in the Targeted Language","authors":["S Seto, M ter Hoeve, H Bai, N Schluter, D Grangier - arXiv preprint arXiv:2411.12986, 2024"],"snippet":"… on combinations of German (target) and English (auxiliary) with varying existing English datasets based on the common crawl: mC4 (Xue… different snapshots of the common crawl. They are all aimed at general language model pretraining …","url":["https://arxiv.org/pdf/2411.12986"]}
{"year":"2024","title":"Training Data for Large Language Model","authors":["Y Ju, H Ma - arXiv preprint arXiv:2411.07715, 2024"],"snippet":"… 通过提供这些数据,Common Crawl支持了各种研究和开发活 动,包括但不限于搜索 引擎优化,语言模型训练,社会数据研究等.由于其数据量… ,Common Crawl成为了许多 数据驱动项目的重要基础,在GPT-3的训练中,Common Crawl贡献 了其中约60%数据的 …","url":["https://arxiv.org/pdf/2411.07715?"]}
{"year":"2024","title":"Training Data for the Price of a Sandwich1","authors":["S Baack, M Insights - 2024"],"snippet":"… , this report sheds light on the implications of Common Crawl’s popularity by exploring the values that guide Common Crawl itself in-depth. … ) whether Common Crawl’s data had been used and b) what specific version of Common Crawl was …","url":["https://foundation.mozilla.org/documents/350/2024CommonCrawlMozillaFoundation.pdf"]}
{"year":"2024","title":"Training Task Experts through Retrieval Based Distillation","authors":["J Ge, X Jia, V Viswanathan, H Luo, G Neubig - arXiv preprint arXiv:2407.05463, 2024"],"snippet":"One of the most reliable ways to create deployable models for specialized tasks is to obtain an adequate amount of high-quality task-specific data. However, for specialized tasks, often such datasets do not exist. Existing methods address this by …","url":["https://arxiv.org/pdf/2407.05463"]}
{"year":"2024","title":"Transfer Learning in the Era of Large Language Models","authors":["Z Phang - 2024"],"snippet":"Natural language processing has made great strides in recent years, largely driven by developments in large-scale neural networks trained on large quantities of textual data. This thesis is a collection of work studying transfer learning—the transfer of …","url":["https://search.proquest.com/openview/b77dad94943b6995357404681c126f1f/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
{"year":"2024","title":"Transformer verbatim in-context retrieval across time and scale","authors":["K Armeni, M Pranjić, S Pollak - Proceedings of the 28th Conference on …, 2024"],"snippet":"To predict upcoming text, language models must in some cases retrieve in-context information verbatim. In this report, we investigated how the ability of language models to retrieve arbitrary in-context nouns developed during training (across time) …","url":["https://aclanthology.org/2024.conll-1.6.pdf"]}
{"year":"2024","title":"Transformer-Based Named Entity Recognition Model-Tamil Language Check for updates","authors":["K Dhayalan, N Sultanova, J Mustafina, P Daud - Data Science and Emerging Technologies …"],"snippet":"This work presents different transformer-based approaches to the named entity recognition problem in the Tamil language. The WikiANN-ta dataset is used for training, validating and testing the model. Person, organization and location tags are …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=SeoEEQAAQBAJ&oi=fnd&pg=PA251&dq=commoncrawl&ots=LpNtMEhFcV&sig=rvIZ8MAeX1vawwV5W0MYS8VUePk"]}
{"year":"2024","title":"Transformer-Driven Models for Language, Vision, and Multimodality","authors":["M Luo, T Gokhale, N Varshney, Y Yang, C Baral - Advances in Multimodal Information …, 2024"],"snippet":"In this chapter, we will learn about the modeling and learning techniques that drive multimodal applications. We will focus specifically on the recent advances in transformer-based modeling for natural language understanding, and image …","url":["https://link.springer.com/chapter/10.1007/978-3-031-57816-8_2"]}
{"year":"2024","title":"Transformers and large language models in healthcare: A review","authors":["S Nerella, S Bandyopadhyay, J Zhang, M Contreras… - Artificial Intelligence in …, 2024"],"snippet":"With Artificial Intelligence (AI) increasingly permeating various aspects of society, including healthcare, the adoption of the Transformers neural network architecture is rapidly changing many applications. Transformer is a type of deep learning …","url":["https://www.sciencedirect.com/science/article/pii/S0933365724001428"]}
{"year":"2024","title":"Transformers and tradition: using Generative AI and Deep Learning for financial markets prediction","authors":["TJ Wade - 2024"],"snippet":"Artificial intelligence has revolutionized numerous industries, and financial markets are no exception. With the ability to process vast amounts of data quickly and accurately, AI algorithms have been increasingly used in finance to predict stock …","url":["http://etheses.lse.ac.uk/4657/1/Wade_200622083.pdf"]}
{"year":"2024","title":"Transformers at HSD-2Lang 2024: Hate Speech Detection in Arabic and Turkish Tweets Using BERT Based Architectures","authors":["K Singhal, J Bedi - Proceedings of the 7th Workshop on Challenges and …, 2024"],"snippet":"Over the past years, researchers across the globe have made significant efforts to develop systems capable of identifying the presence of hate speech in different languages. This paper describes the team Transformers’ submission to the subtasks …","url":["https://aclanthology.org/2024.case-1.26.pdf"]}
{"year":"2024","title":"Transformers for Detection of Distressed Cardiac Patients with an ICD Based on Danish Text Messages","authors":["JDW Andersen, ML Jensen, UK Wiil, S Skovbakke… - 2023 IEEE International …, 2023"],"snippet":"Cardiac patients with implantable cardioverter defibrillator devices frequently exhibit signs of anxiety and depression (termed \"Distressed\"). Early detection of these patients is vital for evaluation, intervention, and prevention against relapse …","url":["https://ieeexplore.ieee.org/abstract/document/10385964/"]}
{"year":"2024","title":"Transformers on Dynamical Systems-An Exploration of In-context Learning","authors":["S Sanghavi - 2023"],"snippet":"Large Language Models (LLMs) have shown to be highly effective at performing in-context learning, where, given a prompt, the model can learn from the prompt and complete the sequence without needing to perform additional gradient steps or fine-tuning. In …","url":["https://www2.eecs.berkeley.edu/Pubs/TechRpts/2023/EECS-2023-287.pdf"]}
{"year":"2024","title":"Transformers@ DravidianLangTech-EACL2024: Sentiment Analysis of Code-Mixed Tamil Using RoBERTa","authors":["K Singhal, J Bedi - Proceedings of the Fourth Workshop on Speech, Vision …, 2024"],"snippet":"In recent years, there has been a persistent focus on developing systems that can automatically identify the hate speech content circulating on diverse social media platforms. This paper describes the team Transformers’ submission to the Caste/Immigration …","url":["https://aclanthology.org/2024.dravidianlangtech-1.25.pdf"]}
{"year":"2024","title":"Transformers@ LT-EDI-EACL2024: Caste and Migration Hate Speech Detection in Tamil Using Ensembling on Transformers","authors":["K Singhal, J Bedi - Proceedings of the Fourth Workshop on Language …, 2024"],"snippet":"In recent years, there has been a persistent focus on developing systems that can automatically identify the hate speech content circulating on diverse social media platforms. This paper describes the team “Transformers” submission to the Caste …","url":["https://aclanthology.org/2024.ltedi-1.32.pdf"]}
{"year":"2024","title":"Transforming Conversational AI","authors":["M McTear, M Ashurkina"],"snippet":"We were motivated to write this book by the launch in November 2022 of ChatGPT and by the ensuing excitement and disruption across the world of Conversational AI. The book is written for a broad audience who are already working, starting to work …","url":["https://link.springer.com/content/pdf/10.1007/979-8-8688-0110-5.pdf"]}
{"year":"2024","title":"Transforming Dutch: Debiasing Dutch Corefence Resolution Systems for Non-binary Pronouns","authors":["G Boven - 2024"],"snippet":"Gender-neutral pronouns are increasingly being introduced across Western languages, and are continuously more frequently being adopted by non-binary individuals. Recent evaluations have however demonstrated that English language …","url":["https://studenttheses.uu.nl/bitstream/handle/20.500.12932/45908/Transforming_Dutch_ThesisAI_GoyavanBoven_Final.pdf?sequence=1&isAllowed=y"]}
{"year":"2024","title":"TransGPT: Multi-modal Generative Pre-trained Transformer for Transportation","authors":["P Wang, X Wei, F Hu, W Han - arXiv preprint arXiv:2402.07233, 2024"],"snippet":"Natural language processing (NLP) is a key component of intelligent transportation systems (ITS), but it faces many challenges in the transportation domain, such as domain-specific knowledge and data, and multi-modal inputs and outputs. This …","url":["https://arxiv.org/pdf/2402.07233"]}
{"year":"2024","title":"Translate-Distill: Learning Cross-Language Dense Retrieval by Translation and Distillation","authors":["E Yang, D Lawrie, J Mayfield, DW Oard, S Miller - arXiv preprint arXiv:2401.04810, 2024"],"snippet":"Prior work on English monolingual retrieval has shown that a cross-encoder trained using a large number of relevance judgments for query-document pairs can be used as a teacher to train more efficient, but similarly effective, dual-encoder student …","url":["https://arxiv.org/pdf/2401.04810"]}
{"year":"2024","title":"Translating and predicting document structure for medical domain scientific abstracts","authors":["SA Rauf, F Yvon - Computer Speech & Language, 2024"],"snippet":"Abstract Machine Translation (MT) technologies have improved in many ways and generate usable outputs for a growing number of domains and language pairs. Yet, most sentence based MT systems struggle with contextual dependencies …","url":["https://www.sciencedirect.com/science/article/pii/S0885230824000068"]}
{"year":"2024","title":"Translating QA is Enough: A Key to Unlocking In-context Cross-lingual Performance","authors":["S Kim, D Ki, Y Kim, J Lee - ICML 2024 Workshop on In-Context Learning"],"snippet":"Multilingual large language models (MLLMs) have demonstrated significant cross-lingual capabilities through in-context learning. Existing approaches typically construct monolingual few-shot examples, either in the source or target language. However …","url":["https://openreview.net/pdf?id=CzcCUzJQER"]}
{"year":"2024","title":"Translating scientific abstracts in the bio-medical domain with structure-aware models","authors":["SA Rauf, F Yvon - Computer Speech and Language, 2024"],"snippet":"Machine Translation (MT) technologies have improved in many ways and generate usable outputs for a growing number of domains and language pairs. Yet, most sentence based MT systems struggle with contextual dependencies, processing …","url":["https://hal.science/hal-04476788/document"]}
{"year":"2024","title":"Translation from Historical to Contemporary Japanese Using Japanese T5","authors":["H Usui, K Komiya - Proceedings of the Joint 3rd International Conference …, 2023"],"snippet":"This paper presents machine translation from historical Japanese to contemporary Japanese using a Text-to-Text Transfer Transformer (T5). The result of the previous study that used neural machine translation (NMT), Long Short Term Memory (LSTM) …","url":["https://aclanthology.org/2023.nlp4dh-1.4.pdf"]}
{"year":"2024","title":"TransLSTM: A hybrid LSTM-Transformer model for fine-grained suggestion mining","authors":["S Riaz, A Saghir, MJ Khan, H Khan, HS Khan, MJ Khan - Natural Language …, 2024"],"snippet":"… Each model, excluding BERT, which employs BERT-BASE-Uncased, undergoes testing using simple text vectorization, GloVe, and Common Crawl. Notably, the GloVe word embedding surpasses common text vectorization and Common Crawl in …","url":["https://www.sciencedirect.com/science/article/pii/S2949719124000372"]}
{"year":"2024","title":"TraQuLA: Transparent Question Answering Over RDF Through Linguistic Analysis","authors":["E Zimina, K Järvelin, J Peltonen, A Ranta… - International Conference on …, 2024"],"snippet":"Answering complex questions over knowledge graphs has gained popularity recently. Systems based on large language models seem to achieve top performance. However, these models may generate content that looks reasonable …","url":["https://link.springer.com/chapter/10.1007/978-3-031-62362-2_2"]}
{"year":"2024","title":"Treading water: new data on the impact of AI ethics information sessions in classics and ancient language pedagogy","authors":["EAS Ross, J Baines - Journal of Classics Teaching, 2024"],"snippet":"Over 2023, many universities and policy organisations in the higher education (HE) sector are working to create guiding principles and guidelines for the use of generative artificial intelligence (AI) in HE Teaching and Learning (T&L). Despite …","url":["https://www.cambridge.org/core/services/aop-cambridge-core/content/view/7EC62BAA5E593C81DB991897729D16DF/S2058631024000412a.pdf/treading_water_new_data_on_the_impact_of_ai_ethics_information_sessions_in_classics_and_ancient_language_pedagogy.pdf"]}
{"year":"2024","title":"TriLM vs FloatLM: Ternary LLMs are more Performant than Quantized FP16 LLMs","authors":["A Kaushal, T Vaidhya, T Pandey, A Bhagat, I Rish - … 2024 Workshop on Foundation Models in …"],"snippet":"Ternary LLMs offer significantly better performance for their size (measured in bits) than the models trained and deployed in FP16/BF16. Given the widespread usage of quantization before deployment and advancements in Post Training Quantization …","url":["https://openreview.net/pdf?id=gvaDL9omKU"]}
{"year":"2024","title":"Trustworthy and Responsible AI for Human-Centric Autonomous Decision-Making Systems","authors":["F Dehghani, M Dibaji, F Anzum, L Dey, A Basdemir… - arXiv preprint arXiv …, 2024"],"snippet":"Artificial Intelligence (AI) has paved the way for revolutionary decision-making processes, which if harnessed appropriately, can contribute to advancements in various sectors, from healthcare to economics. However, its black box nature …","url":["https://arxiv.org/pdf/2408.15550"]}
{"year":"2024","title":"Tucano: Advancing Neural Text Generation for Portuguese","authors":["NK Corrêa, A Sen, S Falk, S Fatimah - arXiv preprint arXiv:2411.07854, 2024"],"snippet":"Significant advances have been made in natural language processing in recent years. However, our current deep learning approach to language modeling requires substantial resources in terms of data and computation. One of the side effects of this …","url":["https://arxiv.org/pdf/2411.07854?"]}
{"year":"2024","title":"Turing Representational Similarity Analysis (RSA): A Flexible Method for Measuring Alignment Between Human and Artificial Intelligence","authors":["M Ogg, R Bose, J Scharf, C Ratto, M Wolmetz - arXiv preprint arXiv:2412.00577, 2024"],"snippet":"As we consider entrusting Large Language Models (LLMs) with key societal and decision-making roles, measuring their alignment with human cognition becomes critical. This requires methods that can assess how these systems represent …","url":["https://arxiv.org/pdf/2412.00577"]}
{"year":"2024","title":"Turning Point","authors":["J Müller"],"snippet":"Does this headline serve to characterize the enormously rapid and profound changes that information technology (IT) is currently causing in all areas of our lives? Is the comparison to an eighth day of creation exaggerated? After reading the …","url":["https://link.springer.com/content/pdf/10.1007/978-3-658-46079-2.pdf"]}
{"year":"2024","title":"Typhoon 2: A Family of Open Text and Multimodal Thai Large Language Models","authors":["K Pipatanakul, P Manakul, N Nitarach… - arXiv preprint arXiv …, 2024"],"snippet":"… In our study, we begin with a total of 40 packs of Thai CommonCrawl data with a cut-off date of September 2023 and perform HTML extraction from scratch using Trafilatura2. This process results in a significantly larger dataset, comprising …","url":["https://arxiv.org/pdf/2412.13702"]}
{"year":"2024","title":"Uhura: A Benchmark for Evaluating Scientific Question Answering and Truthfulness in Low-Resource African Languages","authors":["E Bayes, IA Azime, JO Alabi, J Kgomo, T Eloundou… - arXiv preprint arXiv …, 2024"],"snippet":"Evaluations of Large Language Models (LLMs) on knowledge-intensive tasks and factual accuracy often focus on high-resource languages primarily because datasets for low-resource languages (LRLs) are scarce. In this paper, we present Uhura -- a …","url":["https://arxiv.org/pdf/2412.00948"]}
{"year":"2024","title":"Ultra-Sparse Memory Network","authors":["Z Huang, Q Min, H Huang, D Zhu, Y Zeng, R Guo… - arXiv preprint arXiv …, 2024"],"snippet":"It is widely acknowledged that the performance of Transformer models is exponentially related to their number of parameters and computational complexity. While approaches like Mixture of Experts (MoE) decouple parameter count from …","url":["https://arxiv.org/pdf/2411.12364"]}
{"year":"2024","title":"Unboxing Occupational Bias: Grounded Debiasing LLMs with US Labor Data","authors":["A Gorti, M Gaur, A Chadha - arXiv preprint arXiv:2408.11247, 2024"],"snippet":"Large Language Models (LLMs) are prone to inheriting and amplifying societal biases embedded within their training data, potentially reinforcing harmful stereotypes related to gender, occupation, and other sensitive categories. This issue …","url":["https://arxiv.org/pdf/2408.11247"]}
{"year":"2024","title":"Uncovering Inverse Generativity: An Exploratory Prompt Analysis in LLM Platforms","authors":["J Zebhauser, M Shahid, H Rothe - 2024"],"snippet":"Extended generativity theory states that while generativity lead to more users, more users also affect product boundaries of a platform. We seek to uncover the complex relationship by turning to large language model (LLM) platforms, such as ChatGPT …","url":["https://aisel.aisnet.org/icis2024/diginnoventren/diginnoventren/17/"]}
{"year":"2024","title":"Understanding College Students' Satisfaction With ChatGPT: An Exploratory And Predictive Machine Learning Approach Using Feature Engineering","authors":["K Pabreja, N Pabreja - MIER Journal of Educational Studies Trends and …, 2024"],"snippet":"Artificial Intelligence (AI) technologies are continually improving and becoming more pervasive in many facets of our lives. ChatGPT is one such cutting-edge artificial intelligence application, and it has received a lot of worldwide media attention …","url":["https://mierjs.in/index.php/mjestp/article/download/2568/1593"]}
{"year":"2024","title":"Understanding Emergent Abilities of Language Models from the Loss Perspective","authors":["Z Du, A Zeng, Y Dong, J Tang - arXiv preprint arXiv:2403.15796, 2024"],"snippet":"Recent studies have put into question the belief that emergent abilities in language models are exclusive to large models. This skepticism arises from two observations: 1) smaller models can also exhibit high performance on emergent abilities and 2) …","url":["https://arxiv.org/pdf/2403.15796"]}
{"year":"2024","title":"Understanding Large Language Models","authors":["T Amaratunga"],"snippet":"Today, finding someone who hasn’t heard of ChatGPT, the AI chatbot that took the world by storm, is hard. ChatGPT—and its competitors such as Google Bard, Microsoft Bing Chat, etc.—are part of a broader area in AI known as large language …","url":["https://link.springer.com/content/pdf/10.1007/979-8-8688-0017-7.pdf"]}
{"year":"2024","title":"Understanding latent affective bias in large pre-trained neural language models","authors":["A Kadan, P Deepak, S Bhadra, MP Gangan, VL Lajish - Natural Language …, 2024"],"snippet":"Groundbreaking inventions and highly significant performance improvements in deep learning based Natural Language Processing are witnessed through the development of transformer based large Pre-trained Language Models (PLMs). The …","url":["https://www.sciencedirect.com/science/article/pii/S2949719124000104"]}
{"year":"2024","title":"Understanding LLM's: Comprehensive Overview","authors":["Y Liua, H Hea, T Hana, X Zhanga, M Liua, J Tiana…"],"snippet":"The introduction of ChatGPT has led to a significant increase in the utilization of Large Language Models (LLMs) for addressing downstream tasks. There’s an increasing focus on cost-efficient training and deployment within this context. Low-cost …","url":["https://thetaedger.com/index.php/2024/09/06/understanding-llms-comprehensive-overview/"]}
{"year":"2024","title":"Understanding LLMs: A Comprehensive Overview from Training to Inference","authors":["Y Liu, H He, T Han, X Zhang, M Liu, J Tian, Y Zhang… - arXiv preprint arXiv …, 2024"],"snippet":"… from the CommonCrawl. However, due to the presence of a substantial amount of low-quality data in web archives, preprocessing is essential when working with CommonCrawl data. Currently, four commonly used filtered datasets based on …","url":["https://arxiv.org/pdf/2401.02038"]}
{"year":"2024","title":"Understanding New Machine Learning Architectures: Practical Generative Artificial Intelligence for Anesthesiologists","authors":["CW Connor - Anesthesiology, 2024"],"snippet":"Recent advances in neural networks have given rise to generative artificial intelligence, systems able to produce fluent responses to natural questions or attractive and even photorealistic images from text prompts. These systems were …","url":["https://pubs.asahq.org/anesthesiology/article/140/3/599/139780"]}
{"year":"2024","title":"Understanding Privacy Risks of Embeddings Induced by Large Language Models","authors":["Z Zhu, N Shao, D Lian, C Wu, Z Liu, Y Yang, E Chen - arXiv preprint arXiv …, 2024"],"snippet":"… CC-News (CommonCrawl News dataset) is a dataset containing news articles from international news websites. It contains 708241 English-language news articles published between January 2017 and December 2019. Pile-PubMed is a …","url":["https://arxiv.org/pdf/2404.16587"]}
{"year":"2024","title":"Understanding the Effects of Human-written Paraphrases in LLM-generated Text Detection","authors":["HT Lau, A Zubiaga - arXiv preprint arXiv:2411.03806, 2024"],"snippet":"Natural Language Generation has been rapidly developing with the advent of large language models (LLMs). While their usage has sparked significant attention from the general public, it is important for readers to be aware when a piece of text is LLM-generated …","url":["https://arxiv.org/pdf/2411.03806"]}
{"year":"2024","title":"Understanding the Interplay of Scale, Data, and Bias in Language Models: A Case Study with BERT","authors":["M Ali, S Panda, Q Shen, M Wick, A Kobren - arXiv preprint arXiv:2407.21058, 2024"],"snippet":"… We experiment with English Wikipedia and the CC-100 English subset of Common Crawl. For each model size and type of training data, we compute biases in the representations upstream and performance disparities downstream …","url":["https://arxiv.org/pdf/2407.21058"]}
{"year":"2024","title":"UnifiedCrawl: Aggregated Common Crawl for Affordable Adaptation of LLMs on Low-Resource Languages","authors":["B Melesse Tessema, A Kedia, TS Chung - arXiv e-prints, 2024","BM Tessema, A Kedia, TS Chung - arXiv preprint arXiv:2411.14343, 2024"],"snippet":"… In this study, we extract all the available textual data from every archive within the common crawl for a specific low resource language. Our choice of the common crawl dataset is driven by our objective to maximize the acquisition of the available …","url":["https://arxiv.org/pdf/2411.14343","https://ui.adsabs.harvard.edu/abs/2024arXiv241114343M/abstract"]}
{"year":"2024","title":"UNIVERSAL IMITATION GAMES","authors":["S Mahadevan - 2024"],"snippet":"In 1950, Alan Turing proposed a framework called an imitation game in which the participants are to be classified Human or Machine solely from natural language interactions. Using mathematics largely developed since Turing–category theory–we …","url":["https://people.cs.umass.edu/~mahadeva/papers/Universal_Imitation_Games_Final_Arxiv.pdf"]}
{"year":"2024","title":"University Students' Attitudes and Perceptions on Learning English with ChatGPT","authors":["M Atakuziev, AM Gultom - Formosa Journal of Sustainable Research, 2024"],"snippet":"This study examines 43 master's students' perceptions of ChatGPT in English language learning at Universitas Negeri Yogyakarta. Using a descriptive quantitative methodology, data was gathered via questionnaires and interviews …","url":["https://journal.formosapublisher.org/index.php/fjsr/article/download/10163/10765"]}
{"year":"2024","title":"Unlock the Power of Frozen LLMs in Knowledge Graph Completion","authors":["B Xue, Y Xu, Y Song, Y Pang, Y Ren, J Ding, L Fu… - arXiv preprint arXiv …, 2024"],"snippet":"Classical knowledge graph completion (KGC) methods rely solely on structural information, struggling with the inherent sparsity of knowledge graphs (KGs). Large Language Models (LLMs) learn extensive knowledge from large corpora with …","url":["https://arxiv.org/pdf/2408.06787"]}
{"year":"2024","title":"Unlocking the conversion of Web Screenshots into HTML Code with the WebSight Dataset","authors":["H Laurençon, L Tronchon, V Sanh - arXiv preprint arXiv:2403.09029, 2024"],"snippet":"… available online (and often captured in web crawls like Common Crawl) presents a tempting resource for generating pairs of screenshots and corresponding HTML codes by simply rendering the HTML and capturing the output. However, this …","url":["https://arxiv.org/pdf/2403.09029"]}
{"year":"2024","title":"Unlocking the Marketing and Sales Potential: Bridging Generative AI with Domain-Specific Data using Retrieval Augmented Generation Architecture","authors":["V Lac, D Leschik - Generative Künstliche Intelligenz in Marketing und …, 2024"],"snippet":"The landscape of artificial intelligence (AI) has undergone a paradigm shift due to the transformative impact of Large Language Models (LLMs), facilitated by their capacity to generate text closely simulating human language. Amidst the notable …","url":["https://link.springer.com/chapter/10.1007/978-3-658-45132-5_15"]}
{"year":"2024","title":"Unlocking the Potential of Generative Artificial Intelligence: A Case Study in Software Development","authors":["M Wu-Gehbauer, C Rosenkranz - 2024"],"snippet":"To unlock the potential of GenAI, software developers are facing a key tension. On the one hand, GenAI, as a general-purpose technology, offers vast possibilities for software development. On the other hand, developing software in enterprises …","url":["https://aisel.aisnet.org/icis2024/aiinbus/aiinbus/25/"]}
{"year":"2024","title":"UNLOCKING THE POWER OF LANGUAGE: IMPROVING MULTILINGUAL CAPABILITIES IN GENERATIVE AI FOR GLOBAL ACCESSIBILITY","authors":["LK Maddali"],"snippet":"Generative AI has emerged as a transformative technology with the potential to revolutionize global communication and accessibility. However, the current state of language support in generative AI applications presents both opportunities and …","url":["https://www.academia.edu/download/115776661/IJARET_15_03_019.pdf"]}
{"year":"2024","title":"Unmasking Memorization: Assessing Dutch Language Memorization in mT5 Models","authors":["K Berendsen - 2024"],"snippet":"This study investigates the memorization of Dutch language content in mT5 models, a multilingual variant of the T5 Transformer-based models. A fill-mask evaluation technique is used to assess memorization and how it varies across different model …","url":["https://studenttheses.uu.nl/bitstream/handle/20.500.12932/47129/ADS_Thesis_Kas_Berendsen.pdf?sequence=1"]}
{"year":"2024","title":"Unraveling the Mystery of Scaling Laws: Part I","authors":["H Su, Z Tian, X Shen, X Cai - arXiv preprint arXiv:2403.06563, 2024"],"snippet":"Scaling law principles indicate a power-law correlation between loss and variables such as model size, dataset size, and computational resources utilized during training. These principles play a vital role in optimizing various aspects of model pre-training …","url":["https://arxiv.org/html/2403.06563v1"]}
{"year":"2024","title":"Unseen but influential associates: Properties of words' associates influence lexical and semantic processing","authors":["EJ Muraki, PM Pexman - Psychonomic Bulletin & Review, 2024"],"snippet":"In many models of lexical and semantic processing, it is assumed that single word processing is a function of the characteristics of the words presented and the distributional properties of the words’ networks. Recent research suggests that …","url":["https://link.springer.com/article/10.3758/s13423-024-02485-5"]}
{"year":"2024","title":"Unsupervised approach for misinformation detection in Russia-Ukraine war news","authors":["N Khairova, A Galassi, FL Scudo, B Ivasiuk, I Redozub - 2024"],"snippet":"The Russian-Ukrainian war has attracted considerable global attention; however, fake news often obstructs the formation of public opinion and disseminates false information. To address this issue, we have curated the RUWA dataset, comprising …","url":["https://ceur-ws.org/Vol-3722/paper3.pdf"]}
{"year":"2024","title":"Unsupervised LLM Adaptation for Question Answering","authors":["K Saito, K Sohn, CY Lee, Y Ushiku - arXiv preprint arXiv:2402.12170, 2024"],"snippet":"… Commoncrawl 2. The topics cover politics, sports, business, etc. To reduce the number of tokens, we ask ChatGPT to generate summaries. … We employ NewsFetch7 to crawl the news from Commoncrawl. The published date of the article …","url":["https://arxiv.org/pdf/2402.12170"]}
{"year":"2024","title":"Unsupervised Outlier Detection for Language-Independent Text Quality Filtering","authors":["J Daðason, H Loftsson - Proceedings of the 3rd Annual Meeting of the Special …, 2024"],"snippet":"… Common Crawl (CC) is an organization that maintains a massive repository of data crawled … corpora, all of which are derived from Common Crawl. It consists of 6.3 trillion tokens in 167 … crawled sources, such as Common Crawl. The total size …","url":["https://aclanthology.org/2024.sigul-1.46.pdf"]}
{"year":"2024","title":"Unsupervised Video Moment Retrieval with Knowledge-based Pseudo Supervision Construction","authors":["G Wang, X Wu, X Tu, Z Liu, J Yan - ACM Transactions on Information Systems"],"snippet":"Video moment retrieval locates a specified moment by a sentence query. Recent approaches have made remarkable advancements with large-scale video-sentence annotations. These annotations require extensive human labor and expertise …","url":["https://dl.acm.org/doi/abs/10.1145/3701229"]}
{"year":"2024","title":"Untangling the Unrestricted Web: Automatic Identification of Multilingual Registers","authors":["E Henriksson, A Myntti, A Eskelinen… - arXiv preprint arXiv …, 2024"],"snippet":"This article explores deep learning models for the automatic identification of registers - text varieties such as news reports and discussion forums - in web-based datasets across 16 languages. Web register (or genre) identification would provide a …","url":["https://arxiv.org/pdf/2406.19892"]}
{"year":"2024","title":"Untie the Knots: An Efficient Data Augmentation Strategy for Long-Context Pre-Training in Language Models","authors":["J Tian, D Zheng, Y Cheng, R Wang, C Zhang, D Zhang - arXiv preprint arXiv …, 2024"],"snippet":"… (2024), who emphasize the influence of data quality and diversity in training models, our curated dataset incorporates sources such as Common Crawl, books, Wikipedia, code, and academic papers. Additionally, our dataset is multilingual, with …","url":["https://arxiv.org/pdf/2409.04774"]}
{"year":"2024","title":"Unveiling Al's Evolution and Algorithms","authors":["JK Jayabarathan - Responsible Implementations of Generative AI for …, 2024"],"snippet":"… LLMs are trained on massive datasets such as Common Crawl and the Pile. The terabytes of data comprising these datasets were extracted from billions of publicly accessible websites. On the other hand, Small language models are trained on …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=dDUjEQAAQBAJ&oi=fnd&pg=PA1&dq=commoncrawl&ots=FpM1dToh3h&sig=7RG9Xvu0hnTXgmQz49EK0q4MawI"]}
{"year":"2024","title":"Unveiling Gender Bias in Large Language Models: Using Teacher's Evaluation in Higher Education As an Example","authors":["Y Huang - arXiv preprint arXiv:2409.09652, 2024"],"snippet":"This paper investigates gender bias in Large Language Model (LLM)-generated teacher evaluations in higher education setting, focusing on evaluations produced by GPT-4 across six academic subjects. By applying a comprehensive analytical …","url":["https://arxiv.org/pdf/2409.09652"]}
{"year":"2024","title":"UNVEILING THE COGNITIVE CAPACITY OF CHATGPT: ASSESSING ITS HUMAN-LIKE REASONING ABILITIES","authors":["J Oyeniyi"],"snippet":"… OpenAI utilizes a dataset termed Common Crawl, which is a collection of publicly available websites. This dataset includes billions of web pages and is one of the largest text datasets available. Meanwhile, this dataset is just a starting line. …","url":["https://www.researchgate.net/profile/Johnson-Oyeniyi/publication/379810137_UNVEILING_THE_COGNITIVE_CAPACITY_OF_CHATGPT_ASSESSING_ITS_HUMAN-LIKE_REASONING_ABILITIES/links/661ce53439e7641c0bc8fbf8/Unveiling-the-Cognitive-Capacity-of-ChatGPT-Assessing-its-Human-Like-Reasoning-Abilities.pdf"]}
{"year":"2024","title":"USA: Copyright Management Information and Training Material for Generative AI","authors":["M Lejeune - Computer Law Review International, 2024"],"snippet":"… Plaintiffs allege that “thousands” of their copyrighted works of journalism were caught in this “scrape,” stripped of their author, title, and copyright information, and input into at least three of OpenAI’s training sets (WebText, WebText2, and Common …","url":["https://www.degruyter.com/document/doi/10.9785/cri-2024-250606/html"]}
{"year":"2024","title":"USDC: A Dataset of $\\underline {U} $ ser $\\underline {S} $ tance and $\\underline {D} $ ogmatism in Long $\\underline {C} $ onversations","authors":["M Marreddy, SR Oota, VC Chinni, M Gupta, L Flek - arXiv preprint arXiv:2406.16833, 2024"],"snippet":"Identifying user's opinions and stances in long conversation threads on various topics can be extremely critical for enhanced personalization, market research, political campaigns, customer service, conflict resolution, targeted advertising, and …","url":["https://arxiv.org/pdf/2406.16833"]}
{"year":"2024","title":"Use of Large Language Models to Aid Analysis of Textual Data","authors":["LR Bentley, X Xia, JM Sitt, SC Fankhauser…"],"snippet":"… The use of the data generated by the Common Crawl discussed earlier in this paper mitigates this limitation, drawing from the vast and growing body of content generated through the internet. The quality of the input data also plays a vital role in …","url":["https://www.researchgate.net/profile/Robert-Tai/publication/372535382_Use_of_Large_Language_Models_to_Aid_Analysis_of_Textual_Data/links/667ee9f40a25e27fbc1488b2/Use-of-Large-Language-Models-to-Aid-Analysis-of-Textual-Data.pdf"]}
{"year":"2024","title":"User Story Classification with Machine Learning and LLMs","authors":["P Chuor, A Ittoo, S Heng - … Conference on Knowledge Science, Engineering and …, 2024"],"snippet":"We address the problem of classifying Capability, Task, Hard-goal, and Soft-goal in user stories. Such a classification is essential for generating Rationale Tree. Several articles have attempted to classify different aspects of user stories in the past …","url":["https://link.springer.com/chapter/10.1007/978-981-97-5492-2_13"]}
{"year":"2024","title":"Using Generative AI in Research","authors":["K Frail, J Kung - 2024"],"snippet":"The slides accompany a workshop that is intended for graduate students to learn more about generative AI in the context of the research lifecycle. This work is licensed under a Creative Commons license so that others may share and adapt the …","url":["https://era.library.ualberta.ca/items/e5c442f4-2b3f-4667-9085-81e638fd4053/download/fefc29f1-0e16-40f6-a5df-3383be16357d"]}
{"year":"2024","title":"Using Images to Find Context-Independent Word Representations in Vector Space","authors":["H Kumar - arXiv preprint arXiv:2412.03592, 2024"],"snippet":"… • We use the CommonCrawl dump image links and DuckDuckGo’s image search API to search for openly available images for terms in the final vocabulary. The image set for each term consists of the images of the given term and images for the …","url":["https://arxiv.org/pdf/2412.03592"]}
{"year":"2024","title":"Using Large Language Models to Probe Cognitive Constructs, Augment Data, and Design Instructional Materials","authors":["F Kieser, P Wulff - … in Educational Sciences: Approaches, Applications and …, 2024"],"snippet":"… It was shown that transformer-based large language models (LLMs could be pretrained on large language data sets such as the Common Crawl of the Internet, the Books Corpus, or Wikipedia, and then further fine-tuned in specific tasks [9, 10] …","url":["https://link.springer.com/chapter/10.1007/978-981-99-9379-6_14"]}
{"year":"2024","title":"Using Large Language Models to Understand Leadership Perception and Expectation","authors":["Y Zhang, X Wang, Z Zhang, X Wang, X Ma, Y Wu… - 2024 IEEE International …, 2024"],"snippet":"Using multimodal approaches for measuring propositions in natural language (the Fill-Mask Association Test, FMAT) and ChatGPT 4.0, based on the Five-Factor Model of personality traits, we examined how leaders are perceived and expected in …","url":["https://www.computer.org/csdl/proceedings-article/icmew/2024/10645444/1ZNTgrD9Tk4"]}
{"year":"2024","title":"Using Large Language Models to Understand Telecom Standards","authors":["A Karapantelakis, M Shakur, A Nikou, F Moradi… - arXiv preprint arXiv …, 2024"],"snippet":"… They have billions of parameters and are trained on corpora such as Common Crawl [5]. For foundation models to adapt to application domains, such as telecommunications, prompt engineering and fine-tuning approaches are used …","url":["https://arxiv.org/pdf/2404.02929"]}
{"year":"2024","title":"Using LLMs for the Extraction and Normalization of Product Attribute Values","authors":["A Brinkmann, N Baumann, C Bizer - … Conference on Advances in Databases and …, 2024"],"snippet":"Product offers on e-commerce websites often consist of a product title and a textual product description. In order to enable features such as faceted product search or to generate product comparison tables, it is necessary to extract structured attribute-value …","url":["https://link.springer.com/chapter/10.1007/978-3-031-70626-4_15"]}
{"year":"2024","title":"Using LLMs for the Extraction","authors":["ABDN Baumann, C Bizerb - Advances in Databases and Information Systems: 28th …"],"snippet":"Product offers on e-commerce websites often consist of a product title and a textual product description. In order to enable features such as faceted product search or to generate product comparison tables, it is necessary to extract structured attribute-value …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=VmAeEQAAQBAJ&oi=fnd&pg=PA216&dq=commoncrawl&ots=6n9NAnl_T7&sig=WCgZpfxsqIMNO9eWqzLCarti3fU"]}
{"year":"2024","title":"Using rhetorical strategies to design prompts: a human-in-the-loop approach to make AI useful","authors":["N Ranade, M Saravia, A Johri - AI & SOCIETY, 2024"],"snippet":"… It consumed the text content of the popular CommonCrawl dataset of web pages from 2016 to 2019. Although OpenAI curated it to eliminate redundancy and improve quality, it is nominally 45-terabytes worth of compressed text data. …","url":["https://link.springer.com/article/10.1007/s00146-024-01905-3"]}
{"year":"2024","title":"Utilizing Large Language Models for Non-trained Binary Sentiment Classification","authors":["H Ahn, T Hwang, S Jung, OAIC PLM"],"snippet":"Prompt Return a VALID JSON object with key “sentiment”. Return sentiment must be “positive” or “negative”. Do not say anything other than JSON object result. There is no “neutral”,“mixed” answer. Answer must start with ‘1’. Classify the sentiment of the …","url":["https://koreascience.kr/article/CFKO202306643315751.pdf"]}
{"year":"2024","title":"Utilizing Large Language Models in Ophthalmology: The Current Landscape and Challenges","authors":["P Chotcomwongse, P Ruamviboonsuk, A Grzybowski - Ophthalmology and Therapy, 2024"],"snippet":"A large language model (LLM) is an artificial intelligence (AI) model that uses natural language processing (NLP) to understand, interpret, and generate human-like language responses from unstructured text input. Its real-time response capabilities …","url":["https://link.springer.com/article/10.1007/s40123-024-01018-6"]}
{"year":"2024","title":"Uzbek news corpus for named entity recognition","authors":["A Yusufu, K Aziz, A Yusufu, A Ainiwaer, F Li, D Ji - Language Resources and …, 2024"],"snippet":"We have presented a corpus of Uzbek news articles containing manually annotated named entities. The corpus comprises 500 articles (222,536 tokens) and three entity classes (person, location, organization) sourced from Qalampir, an online news …","url":["https://link.springer.com/article/10.1007/s10579-024-09786-0"]}
{"year":"2024","title":"UzRoberta: A pre-trained language model for Uzbek","authors":["R Davronov, F Adilova - AIP Conference Proceedings, 2024"],"snippet":"… Common Crawl datasets, was generated distributed word representations for 157 different languages [8]. Author’s Uzbek Wikipedia model has 110K words, compared to -830K words in the Common Crawl … It is pre-trained on 2.5TB of filtered …","url":["https://pubs.aip.org/aip/acp/article/3004/1/050001/3270462"]}
{"year":"2024","title":"UZROBERTA: AN UZBEK LANGUAGE PRE-TRAINED MODEL","authors":["F Adilova, R Davronov, R Safarov - Universum: технические науки, 2023"],"snippet":"… Distributed word representations for 157 distinct languages were created using the Wikipedia and Common Crawl databases [8]. The author's Uzbek Wikipedia model has 110K words, but the Common Crawl model only has 830K words. They …","url":["https://cyberleninka.ru/article/n/uzroberta-an-uzbek-language-pre-trained-model"]}
{"year":"2024","title":"V-GlórIA-Customizing Large Vision and Language Models to European Portuguese","authors":["A Simplício, D Semedo, J Magalhães - Proceedings of the 1st Workshop on …, 2024"],"snippet":"Generative Vision and Language models have obtained remarkable results recently, thanks to the use of robust pre-trained Visual encoders and Large Language Models (LLMs), together with efficient model adaptation training strategies, requiring …","url":["https://aclanthology.org/2024.customnlp4u-1.24.pdf"]}
{"year":"2024","title":"Validating and Exploring Large Geographic Corpora","authors":["J Dunn - arXiv preprint arXiv:2403.08198, 2024"],"snippet":"… Beginning with a 427 billion word corpus derived from the Common Crawl, three methods are used to improve the quality of sub-corpora representing specific language-country pairs … This paper starts with an existing web corpus derived …","url":["https://arxiv.org/pdf/2403.08198"]}
{"year":"2024","title":"Validating pretrained language models for content quality classification with semantic-preserving metamorphic relations","authors":["PYP Chan, J Keung - Natural Language Processing Journal, 2024"],"snippet":"Context: Utilizing pretrained language models (PLMs) has become common practice in maintaining the content quality of question-answering (Q&A) websites. However, evaluating the effectiveness of PLMs poses a challenge as they tend to provide local …","url":["https://www.sciencedirect.com/science/article/pii/S2949719124000621"]}
{"year":"2024","title":"Value Residual Learning For Alleviating Attention Concentration In Transformers","authors":["Z Zhou, T Wu, Z Jiang, Z Lan - arXiv preprint arXiv:2410.17897, 2024"],"snippet":"Transformers can capture long-range dependencies using self-attention, allowing tokens to attend to all others directly. However, stacking multiple attention layers leads to attention concentration. One natural way to address this issue is to use cross-layer …","url":["https://arxiv.org/pdf/2410.17897"]}
{"year":"2024","title":"VERB: Visualizing and Interpreting Bias Mitigation Techniques Geometrically for Word Representations","authors":["YAN ZHENG, CCM YEH, J WANG, WEI ZHANG - 2024"],"snippet":"Complicated and massive datasets are becoming more and more commonly represented as vectorized embeddings. They are part of a de facto model for words in word vector embeddings such as Word2Vec [51] and GloVe [54], and are …","url":["https://scholar.archive.org/work/2ppdkjgmevgzhe4lcnrni2nqaa/access/wayback/https://dl.acm.org/doi/pdf/10.1145/3604433"]}
{"year":"2024","title":"Verifying Claims About Metaphors with Large-Scale Automatic Metaphor Identification","authors":["K Aono, R Sasano, K Takeda - arXiv preprint arXiv:2404.01029, 2024"],"snippet":"… Third, in this study, the examples were collected from CommonCrawl, which is a corpus of texts on the Web, and thus contains mostly written language. It is unknown whether similar results can be obtained when analyzing examples collected from a …","url":["https://arxiv.org/pdf/2404.01029"]}
{"year":"2024","title":"VERISCORE: Evaluating the factuality of verifiable claims in long-form text generation","authors":["Y Song, Y Kim, M Iyyer - arXiv preprint arXiv:2406.19276, 2024"],"snippet":"Existing metrics for evaluating the factuality of long-form text, such as FACTSCORE (Min et al., 2023) and SAFE (Wei et al., 2024), decompose an input text into \"atomic claims\" and verify each against a knowledge base like Wikipedia. These metrics are not …","url":["https://arxiv.org/pdf/2406.19276"]}
{"year":"2024","title":"VetMedGPT: Generative Pre-trained Transformer for Veteri-nary Medicine Healthcare","authors":["P Lin, SR Hussain, T Kadari, V Biyyala, S Bennur…"],"snippet":"… This open dataset is sourced from 84 CommonCrawl snapshots and refined through the CCNet pipeline, presenting a vast pool of over 100 billion text documents. Notably, it includes a corpus of 30 billion documents that are enhanced with quality …","url":["https://www.researchgate.net/profile/Sayed-Hussain-20/publication/385722362_VetMedGPT_Generative_Pre-trained_Transformer_for_Veteri-_nary_Medicine_Healthcare/links/6732d84da78ba469f05ea7d3/VetMedGPT-Generative-Pre-trained-Transformer-for-Veteri-nary-Medicine-Healthcare.pdf"]}
{"year":"2024","title":"Viewpoints Detection in Political Speeches","authors":["TM Doan - 2024"],"snippet":"Politics has significant impacts on our daily lives. It influences laws, policies, and resources allocation. The Internet and social media confront readers with an overwhelming amount of political texts. Readers struggle to analyze the information …","url":["https://ntnuopen.ntnu.no/ntnu-xmlui/bitstream/handle/11250/3152093/Tu%20My%20Doan.pdf?sequence=1"]}
{"year":"2024","title":"ViFactCheck: A New Benchmark Dataset and Methods for Multi-domain News Fact-Checking in Vietnamese","authors":["TT Hoa, TQ Duy, KQ Tran, K Van Nguyen - arXiv preprint arXiv:2412.15308, 2024"],"snippet":"The rapid spread of information in the digital age highlights the critical need for effective fact-checking tools, particularly for languages with limited resources, such as Vietnamese. In response to this challenge, we introduce ViFactCheck, the first …","url":["https://arxiv.org/pdf/2412.15308"]}
{"year":"2024","title":"ViHateT5: Enhancing Hate Speech Detection in Vietnamese With A Unified Text-to-Text Transformer Model","authors":["LT Nguyen - arXiv preprint arXiv:2405.14141, 2024"],"snippet":"… Leveraging a Transformer architecture and trained on a massive dataset of 2.5TB filtered CommonCrawl text across 100 languages, it employs a masked language modeling (MLM) objective to learn crosslingual representations. This approach …","url":["https://arxiv.org/pdf/2405.14141"]}
{"year":"2024","title":"ViLLM-Eval: A Comprehensive Evaluation Suite for Vietnamese Large Language Models","authors":["TH Nguyen, AC Le, VC Nguyen - arXiv preprint arXiv:2404.11086, 2024"],"snippet":"The rapid advancement of large language models (LLMs) necessitates the development of new benchmarks to accurately assess their capabilities. To address this need for Vietnamese, this work aims to introduce ViLLM-Eval, the …","url":["https://arxiv.org/pdf/2404.11086"]}
{"year":"2024","title":"Virtual reality in automotive digital twins: a large language model-assisted content analysis of an expert evaluation","authors":["KSD Ka, IV Bosman, D Smit - Proceedings of the 27th International Academic …, 2024"],"snippet":"Digital twins are gaining significant traction within the automotive engineering industry. Within this environment of data interchange that may reach very high levels of complexity, virtual reality can ease understanding and provide intuitive interaction …","url":["https://dl.acm.org/doi/pdf/10.1145/3681716.3681733"]}
{"year":"2024","title":"VISION2UI: A Real-World Dataset with Layout for Code Generation from UI Designs","authors":["Y Gui, Z Li, Y Wan, Y Shi, H Zhang, Y Su, S Dong… - arXiv preprint arXiv …, 2024"],"snippet":"… we opt to create our dataset on top of the Common Crawl3 dataset. The Common Crawl dataset is a vast collection of Web page data from … This partial dataset from the original Common Crawl dataset includes 3.35 billion pages, amounting to a total …","url":["https://arxiv.org/pdf/2404.06369"]}
{"year":"2024","title":"Visual Artists, Technological Shock, and Generative AI","authors":["CA Jones, H Gupta, M Ritchie - 2024"],"snippet":"The impact of generative AI (GenAI) programs on visual art is comparable to earlier historical moments of technological shock, when literary and visual artists grappled with unprecedented reproductive tools such as the printing press, photography, and …","url":["https://mit-genai.pubpub.org/pub/l62ipwcb"]}
{"year":"2024","title":"Visual Instruction Tuning towards General-Purpose Multimodal Model: A Survey","authors":["J Huang, J Zhang, K Jiang, H Qiu, S Lu - arXiv preprint arXiv:2312.16602, 2023"],"snippet":"Traditional computer vision generally solves each single task independently by a dedicated model with the task instruction implicitly designed in the model architecture, arising two limitations: (1) it leads to task-specific models, which require …","url":["https://arxiv.org/pdf/2312.16602"]}
{"year":"2024","title":"VLUE: A New Benchmark and Multi-task Knowledge Transfer Learning for Vietnamese Natural Language Understanding","authors":["PNT Do, SQ Tran, PG Hoang, K Van Nguyen… - arXiv preprint arXiv …, 2024"],"snippet":"… 250002 multilingual CommonCrawl XLM-Robertalarge … This model was trained on a Transformers-based masked language task using two terabytes of CommonCrawl data across more than a hundred languages. The model has two …","url":["https://arxiv.org/html/2403.15882v1"]}
{"year":"2024","title":"Vocabulary Expansion of Chat Models with Unlabeled Target Language Data","authors":["A Yamaguchi, T Morishita, A Villavicencio, N Aletras - arXiv preprint arXiv:2412.11704, 2024"],"snippet":"Chat models (ie language models trained to follow instructions through conversation with humans) outperform base models (ie trained solely on unlabeled data) in both conversation and general task-solving abilities. These models are generally English-centric …","url":["https://arxiv.org/pdf/2412.11704"]}
{"year":"2024","title":"Volume 2024 Fall Issue 2","authors":["U Benoliel, C Engel, RH McAdams, AHC Hung"],"snippet":"Disclosure laws are a fundamental regulatory mechanism in the United States, mandating firms to provide comprehensive and intricate data that is of significant value to the public. Unfortunately, this data is often complex and voluminous, making …","url":["https://heinonline.org/hol-cgi-bin/get_pdf.cgi?handle=hein.journals/jltp2024&section=9"]}
{"year":"2024","title":"W-RAG: Weakly Supervised Dense Retrieval in RAG for Open-domain Question Answering","authors":["J Nian, Z Peng, Q Wang, Y Fang - arXiv preprint arXiv:2408.08444, 2024"],"snippet":"… The corpus may comprise chuncked Wikipedia articles or from online sources such as Reddit and Common Crawl, while the question-answer pairs could be sourced from OpenQA platforms such as Quora and StackOverflow. The simple first-stage …","url":["https://arxiv.org/pdf/2408.08444"]}
{"year":"2024","title":"WaCadie: Towards an Acadian French Corpus","authors":["J Robichaud, P Cook - Proceedings of the 2024 Joint International Conference …, 2024"],"snippet":"… We treat each post as one document, similar to one website’s HTML from the Common Crawl corpus. We refer to this corpus as r/acadie. … We used CommonCrawl’s extensive database and scraped New Brunswick (.nb.ca) websites …","url":["https://aclanthology.org/2024.lrec-main.1514.pdf"]}
{"year":"2024","title":"WanJuan-CC: A Safe and High-Quality Open-sourced English Webtext Dataset","authors":["J Qiu, H Lv, Z Jin, R Wang, W Ning, J Yu, CB Zhang… - arXiv preprint arXiv …, 2024"],"snippet":"… Moreover, Common Crawl contains a large amount of unsafe content, such as toxic and pornographic … Common Crawl data, which includes data extraction, heuristic rule filtering, fuzzy deduplication, content safety filtering, and data quality …","url":["https://arxiv.org/pdf/2402.19282"]}
{"year":"2024","title":"WaterPark: A Robustness Assessment of Language Model Watermarking","authors":["J Liang, Z Wang, L Hong, S Ji, T Wang - arXiv preprint arXiv:2411.13425, 2024"],"snippet":"… Specifically, WATERPARK integrates a variety of LLMs including OPT-1.3B [74], Llama2-7B [58], Mistral-7B [22], and Gemma-2B/7B [15]; it also includes a variety of datasets including: C4 is a cleaned version of Common Crawl’s web crawl corpus …","url":["https://arxiv.org/pdf/2411.13425"]}
{"year":"2024","title":"WCC-EC 2.0: Enhancing Neural Machine Translation with a 1.6 M+ Web-Crawled English-Chinese Parallel Corpus","authors":["J Zhang, K Su, Y Tian, T Matsumoto - Electronics, 2024"],"snippet":"This research introduces WCC-EC 2.0 (Web-Crawled Corpus—English and Chinese), a comprehensive parallel corpus designed for enhancing Neural Machine Translation (NMT), featuring over 1.6 million English-Chinese sentence pairs …","url":["https://www.mdpi.com/2079-9292/13/7/1381/pdf"]}
{"year":"2024","title":"We have no idea what we are walking into: AI and ethical considerations","authors":["KB Forrest - Annals of the New York Academy of Sciences, 2024"],"snippet":"… called “Common Crawl” provide data, “C4” is a curated (de-duplicated and some nonsensical junk eliminated) set of the Common Crawl data, then there is a data set well named “The Pile”, and others that are compilations of books, music …","url":["https://nyaspubs.onlinelibrary.wiley.com/doi/abs/10.1111/nyas.15133"]}
{"year":"2024","title":"Weakly supervised learning for an effective focused web crawler","authors":["PRJ Dhanith, K Saeed, G Rohith, SP Raja - Engineering Applications of Artificial …, 2024"],"snippet":"Focused crawler traverses the Web to only collect pages that are relevant to a particular topic, and is increasingly considered as a way to get around the scalability issues with current general-purpose search engines. But the data diversity in the …","url":["https://www.sciencedirect.com/science/article/pii/S0952197624001027"]}
{"year":"2024","title":"WEATHER-5K: A Large-scale Global Station Weather Dataset Towards Comprehensive Time-series Forecasting Benchmark","authors":["T Han, S Guo, Z Chen, W Xu, L Bai - arXiv preprint arXiv:2406.14399, 2024"],"snippet":"Global Station Weather Forecasting (GSWF) is crucial for various sectors, including aviation, agriculture, energy, and disaster preparedness. Recent advancements in deep learning have significantly improved the accuracy of weather predictions by …","url":["https://arxiv.org/pdf/2406.14399"]}
{"year":"2024","title":"Web Archives Metadata Generation with GPT-4o: Challenges and Insights","authors":["A Nair, ZR Goh, T Liu, AYP Huang - Information Technology and Libraries, 2025","AY Huang, A Nair, ZR Goh, T Liu - arXiv preprint arXiv:2411.05409, 2024"],"snippet":"Current metadata creation for web archives is time consuming and costly due to reliance on human effort. This paper explores the use of gpt-4o for metadata generation within the Web Archive Singapore, focusing on scalability, efficiency, and …","url":["https://arxiv.org/pdf/2411.05409","https://ital.corejournals.org/index.php/ital/article/download/17305/11938"]}
{"year":"2024","title":"Web Crawl Refusals: Insights From Common Crawl","authors":["M Ansar - 2024"],"snippet":"… Abstract: This study investigates server-side blocks encountered by Common Crawl, a major … that approximately 1.68% of websites in a Common Crawl snapshot exhibit some form of explicit … of these blocks and the effectiveness of …","url":["http://essay.utwente.nl/98890/"]}
{"year":"2024","title":"Web Data Commons-RDFa, Microdata, Embedded JSON-LD, and Microformats Data Sets-October 2023","authors":["A Brinkmann, C Bizer - 2024"],"snippet":"The Web Data Commons RDFa, Microdata and Microformats data sets has been extracted from the September/October 2023 release of the Common Crawl. In summary, we found structured data within 1.7 billion HTML pages out of the 3.4 …","url":["https://madata.bib.uni-mannheim.de/429/"]}
{"year":"2024","title":"Web Data Commons-Schema. org Table Corpus 2023","authors":["R Peeters, A Brinkmann, C Bizer - 2024"],"snippet":"The WDC schema.org Table Corpus consists of ~5 million relational tables which were generated by extracting schema.org data from the Common Crawl and grouping the data into seperate tables for each class/host combination, eg all …","url":["https://madata.bib.uni-mannheim.de/430/"]}
{"year":"2024","title":"Web scraping and Generative Models training in the Directive 790/19","authors":["C Gallese - i-lex, 2023"],"snippet":"… The companies that created GM never disclosed the exact corpus of training data they employed to train their models; however, it has become clear sources that many copyrighted materials were employed as part of larger datasets such as the …","url":["https://i-lex.unibo.it/article/download/18871/17439"]}
{"year":"2024","title":"Web scraping: Jurisprudence and legal doctrines","authors":["AG Fontana - The Journal of World Intellectual Property"],"snippet":"… In the case of ChatGPT, for example, during the pretraining phase large quantities of textual data are used, extracted from archives like Common Crawl, Wikipedia or Google Books but also from platforms like Reddit. Without web scraping no AI or …","url":["https://onlinelibrary.wiley.com/doi/abs/10.1111/jwip.12331"]}
{"year":"2024","title":"WebCiteS: Attributed Query-Focused Summarization on Chinese Web Search Results with Citations","authors":["H Deng, C Wang, X Li, D Yuan, J Zhan, T Zhou, J Ma… - arXiv preprint arXiv …, 2024"],"snippet":"Enhancing the attribution in large language models (LLMs) is a crucial task. One feasible approach is to enable LLMs to cite external sources that support their generations. However, existing datasets and evaluation methods in this domain still …","url":["https://arxiv.org/pdf/2403.01774"]}
{"year":"2024","title":"WebGraph: The Next Generation (Is in Rust)","authors":["T Fontana, S Vigna, S Zacchiroli - ACM Web Conference 2024, 2024"],"snippet":"We report the results of a yearlong effort to port the WebGraph framework from Java to Rust. For two decades WebGraph has been instrumental in the analysis and distribution of large graphs for the research community of TheWebConf, but the …","url":["https://hal.science/hal-04494627/document"]}
{"year":"2024","title":"What are Large Language Models Made of?","authors":["C Stinson - Leading the Way: Envisioning the Future of Higher …, 2024"],"snippet":"… CommonCrawl is the lowest quality but largest of these datasets, consisting of text scraped from all over the web. Their data from the years 2016 to 2019 were used to train GPT-3. OpenAI’s quality control measure for filtering CommonCrawl was to …","url":["https://ecampusontario.pressbooks.pub/futureofhighereducation/chapter/what-are-large-language-models-made-of/"]}
{"year":"2024","title":"What can be learned about color from","authors":["Q Liu, J van Paridon, G Lupyan"],"snippet":"… Word embedding models trained on COCA-fiction performed better than models trained on much larger corpora: COCA-fiction (at 120 million tokens) outperformed OpenSubtitles (750 million tokens) and Common Crawl ( 600 billion tokens) though …","url":["https://files.de-1.osf.io/v1/resources/vyxpq/providers/osfstorage/601db57b4497cf000a9bfca1?action=download&direct&version=3"]}
{"year":"2024","title":"What do BERT word embeddings learn about the French language?","authors":["E Goliakova, D Langlois - Sixth International Conference, 2024"],"snippet":"Pre-trained word embeddings (for example, BERT-like) have been successfully used in a variety of downstream tasks. However, do all embeddings, obtained from the models of the same architecture, encode information in the same way? Does the …","url":["https://dcl.bas.bg/clib/wp-content/uploads/2024/09/CLIB2024_PROCEEDINGS_v1.0.pdf#page=21"]}
{"year":"2024","title":"What Does “Palliative” Mean? Sentiment, Knowledge, and Public Perception Concerning Palliative Care on the Internet since the COVID-19 Pandemic","authors":["J Peters, M Heckel, E Breindl, C Ostgathe - Palliative Medicine Reports, 2024"],"snippet":"… data from the CommonCrawl corpus, 25 consisting of English-language websites with the ccTLD-domains .com, .org and .uk. Twenty-three, 219 texts with relevant thematic focus remained in the corpus. (3) We created a large X corpus because the …","url":["https://www.liebertpub.com/doi/pdf/10.1089/pmr.2024.0057"]}
{"year":"2024","title":"What is the authentic internet register before & after the Russian invasion in Ukraine? Polish and Czech YouTube comments from 2021–2023","authors":["A Tikhonov - Lodz Papers in Pragmatics, 2024"],"snippet":"Over one million tokens of comments were collected for the study using data mining methods. The videos under which the comments were dug out were not chosen arbitrarily but according to the current official national YouTube trends in Poland and …","url":["https://www.degruyter.com/document/doi/10.1515/lpp-2024-0026/html"]}
{"year":"2024","title":"What's in a Name? Experimental Evidence of Gender Bias in Recommendation Letters Generated by ChatGPT","authors":["DM Kaplan, R Palitsky, SJ Arconada Alvarez… - Journal of Medical Internet …, 2024"],"snippet":"… In the case of GPT-3.5 (the current version at the time of this study), the model contains 175 billion parameters and was trained with commonly available text training sets that represent a broad swath of data on the internet (Common Crawl) …","url":["https://www.jmir.org/2024/1/e51837/"]}
{"year":"2024","title":"What's New in My Data? Novelty Exploration via Contrastive Generation","authors":["M Isonuma, I Titov - arXiv preprint arXiv:2410.14765, 2024"],"snippet":"Fine-tuning is widely used to adapt language models for specific goals, often leveraging real-world data such as patient records, customer-service interactions, or web content in languages not covered in pre-training. These datasets are typically …","url":["https://arxiv.org/pdf/2410.14765"]}
{"year":"2024","title":"When Context Leads but Parametric Memory Follows in Large Language Models","authors":["Y Tao, A Hiatt, E Haake, AJ Jetter, A Agrawal - arXiv preprint arXiv:2409.08435, 2024"],"snippet":"Large language models (LLMs) have demonstrated remarkable progress in leveraging diverse knowledge sources. This study investigates how nine widely used LLMs allocate knowledge between local context and global parameters when …","url":["https://arxiv.org/pdf/2409.08435"]}
{"year":"2024","title":"When Every Token Counts: Optimal Segmentation for Low-Resource Language Models","authors":["G Suri, V Dewangan, R Sonavane - arXiv preprint arXiv:2412.06926, 2024","V Dewangan, G Suri, R Sonavane - Proceedings of the First Workshop on …, 2025"],"snippet":"… The CC100 dataset consists of monolingual data of 116 languages extracted from the January-December 2018 Commoncrawl snapshots. We benchmark on the English language using the Wikipedia corpus readily accessible on Kaggle Datasets2 …","url":["https://aclanthology.org/2025.loreslm-1.24.pdf","https://arxiv.org/pdf/2412.06926"]}
{"year":"2024","title":"When Precision Meets Position: BFloat16 Breaks Down RoPE in Long-Context Training","authors":["H Wang, Q Liu, C Du, T Zhu, C Du, K Kawaguchi… - arXiv preprint arXiv …, 2024"],"snippet":"… This suggests that CommonCrawl sequences in our dataset are not only more numerous but also longer, contributing significantly to the … Overall, our up-sampled data mixture places greater emphasis on longer sequences from CommonCrawl …","url":["https://arxiv.org/pdf/2411.13476"]}
{"year":"2024","title":"When Young Scholars Cooperate with LLMs in Academic Tasks: The Influence of Individual Differences and Task Complexities","authors":["J Wang, C Huang, S Yan, W Xie, D He - International Journal of Human–Computer …, 2024"],"snippet":"As a novel AI-powered conversational system, large language models (LLMs) have the potential to be used in various applications. Recent advances in LLMs like ChatGPT have made LLM-based academic tools possible. However, most of the …","url":["https://www.tandfonline.com/doi/abs/10.1080/10447318.2024.2352919"]}
{"year":"2024","title":"Where does In-context Learning\\\\Happen in Large Language Models?","authors":["S Sia, D Mueller, K Duh - The Thirty-eighth Annual Conference on Neural …"],"snippet":"Self-supervised large language models have demonstrated the ability to perform various tasks via in-context learning, but little is known about where the model locates the task with respect to prompt instructions and demonstration examples. In …","url":["https://openreview.net/pdf?id=LLuSjg59an"]}
{"year":"2024","title":"Where does In-context Translation Happen in Large Language Models","authors":["S Sia, D Mueller, K Duh - arXiv preprint arXiv:2403.04510, 2024"],"snippet":"Self-supervised large language models have demonstrated the ability to perform Machine Translation (MT) via in-context learning, but little is known about where the model performs the task with respect to prompt instructions and demonstration …","url":["https://arxiv.org/html/2403.04510v1"]}
{"year":"2024","title":"Which Programming Language and What Features at Pre-training Stage Affect Downstream Logical Inference Performance?","authors":["F Uchiyama, T Kojima, A Gambardella, Q Cao… - arXiv preprint arXiv …, 2024"],"snippet":"Recent large language models (LLMs) have demonstrated remarkable generalization abilities in mathematics and logical reasoning tasks. Prior research indicates that LLMs pre-trained with programming language data exhibit high …","url":["https://arxiv.org/pdf/2410.06735"]}
{"year":"2024","title":"Which Word Embeddings for Modeling Web Search Queries? Application to the Study of Search Strategies","authors":["C Ibarboure, L Tanguy, F Amadieu - 2023"],"snippet":"In order to represent the global strategies deployed by a user during an information retrieval session on the Web, we compare different pretrained vector models capable of representing the queries submitted to a search engine. More precisely …","url":["https://www.scitepress.org/Papers/2023/121776/121776.pdf"]}
{"year":"2024","title":"Who Gets Paid (for) What? The Cultural Political Economy of News Content in Generative AI","authors":["S Nam - Emerging Media, 2024"],"snippet":"One of the key controversies that generative artificial intelligence (AI) has recently stirred was whether compensation is due for the copyrighted materials used to train AI models. This article explores the logic, trajectories, and dynamics of content …","url":["https://journals.sagepub.com/doi/pdf/10.1177/27523543241287835"]}
{"year":"2024","title":"Who's Afraid of ChatGPT?: Large Language Models and Conspiracies","authors":["J Laudun - Contemporary Legend, 2024"],"snippet":"… GPT-3 added Common Crawl to the training datasets, 570GB of text obtained after filtering from 45TB of plaintext. The filtering was done by comparing new documents to documents in WebText, with the latter acting as a proxy for high-quality …","url":["https://scholarworks.iu.edu/journals/index.php/cl/article/download/38419/40746"]}
{"year":"2024","title":"Why 'open'AI systems are actually closed, and why this matters","authors":["DG Widder, M Whittaker, SM West - Nature, 2024"],"snippet":"This paper examines ‘open’ artificial intelligence (AI). Claims about ‘open’ AI often lack precision, frequently eliding scrutiny of substantial industry concentration in large-scale AI development and deployment, and often incorrectly applying …","url":["https://www.nature.com/articles/s41586-024-08141-1"]}
{"year":"2024","title":"WikiDBs: A Large-Scale Corpus Of Relational Databases From Wikidata","authors":["L Vogel, JM Bodensohn, C Binnig - The Thirty-eight Conference on Neural Information …"],"snippet":"Deep learning on tabular data, and particularly tabular representation learning, has recently gained growing interest. However, representation learning for relational databases with multiple tables is still an underexplored area, which may be …","url":["https://openreview.net/pdf?id=abXaOcvujs"]}
{"year":"2024","title":"Willkommens-Merkel, Chaos-Johnson, and Tore-Klose: Modeling the Evaluative Meaning of German Personal Name Compounds","authors":["AETDA Blessing, M Belosevic"],"snippet":"We present a comprehensive computational study of the under-investigated phenomenon of personal name compounds (PNCs) in German such as Willkommens-Merkel (‘Welcome-Merkel’). Prevalent in news, social media, and …","url":["https://openreview.net/pdf?id=GHLROxS7Fh"]}
{"year":"2024","title":"WITH LLaMA-3?","authors":["WIFWER BILLIONS"],"snippet":"… Although Datacomp is derived from Common Crawl and represents a snapshot of data in the public internet, it inevitably includes noisy and potentially unsafe content. The dataset’s curation involves rigorous filtering, including NSFW filters on images …","url":["https://openreview.net/pdf?id=WpObsQTpfp"]}
{"year":"2024","title":"Worldwide Federated Training of Language Models","authors":["A Iacob, L Sani, B Marino, P Aleksandrov, ND Lane - arXiv preprint arXiv:2405.14446, 2024"],"snippet":"… To simulate geographically distributed systems, we use a subset of Multilingual Colossal Common Crawl (mC4)[81], covering high and low-… For IID experiments, we use the standard Cleaned Colossal Common Crawl (C4) English dataset …","url":["https://arxiv.org/pdf/2405.14446"]}
{"year":"2024","title":"WRITTEN IN PERSIAN USING A TRANSFORMER-BASED MODEL","authors":["T Firoozi, MJ Gierl - The Routledge International Handbook of Automated …, 2024"],"snippet":"… This model is created using contents from Common Crawl and Wikipedia. It is trained using CBOW with position weights, in dimension 300, with character n-grams of length 5, and a window of size 5 and 10. The model gives 300-dimensional vector …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=3-UFEQAAQBAJ&oi=fnd&pg=PA55&dq=commoncrawl&ots=pOzjIBhsMA&sig=n-gWEJHSQ9_8r8O4JLKLSCq2r2M"]}
{"year":"2024","title":"X-Phishing-Writer: A Framework for Cross-Lingual Phishing Email Generation","authors":["SW Guo, YC Fan - ACM Transactions on Asian and Low-Resource …, 2024"],"snippet":"… The mBART model employs various language corpora from the Common Crawl dataset and undergoes multilingual pretraining based on the BART architecture. The training data is a concatenation of data from � diferent languages, denoted as � = �1,�2...�� …","url":["https://dl.acm.org/doi/pdf/10.1145/3670402"]}
{"year":"2024","title":"XLM for Autonomous Driving Systems: A Comprehensive Review","authors":["S Fourati, W Jaafar, N Baccar, S Alfattani - arXiv preprint arXiv:2409.10484, 2024"],"snippet":"Large Language Models (LLMs) have showcased remarkable proficiency in various information-processing tasks. These tasks span from extracting data and summarizing literature to generating content, predictive modeling, decision-making …","url":["https://arxiv.org/pdf/2409.10484"]}
{"year":"2024","title":"XLMR4MD: New Vietnamese dataset and framework for detecting the consistency of description and permission in Android applications using large language models","authors":["QN Nguyen, NT Cam, K Van Nguyen - Computers & Security, 2024"],"snippet":"… The most significant update that XLMRoBERTa provides compared to the original is that the amount of training data has increased significantly, the cleaned CommonCrawl data it was trained on takes up a considerable memory block of up to …","url":["https://www.sciencedirect.com/science/article/pii/S0167404824001159"]}
{"year":"2024","title":"XLORE 3: A Large-scale Multilingual Knowledge Graph from Heterogeneous Wiki Knowledge Resources","authors":["K Zeng, H Jin, X Lv, F Zhu, L Hou, Y Zhang, F Pang… - ACM Transactions on …, 2024"],"snippet":"In recent years, Knowledge Graph (KG) has attracted significant attention from academia and industry, resulting in the development of numerous technologies for KG construction, completion, and application. XLORE is one of the largest …","url":["https://dl.acm.org/doi/pdf/10.1145/3660521"]}
{"year":"2024","title":"Y-MAP-Net: Real-time depth, normals, segmentation, multi-label captioning and 2D human pose in RGB images","authors":["A Qammaz, N Vasilikopoulos, I Oikonomidis… - arXiv preprint arXiv …, 2024"],"snippet":"We present Y-MAP-Net, a Y-shaped neural network architecture designed for real-time multi-task learning on RGB images. Y-MAP-Net, simultaneously predicts depth, surface normals, human pose, semantic segmentation and generates multi-label …","url":["https://arxiv.org/pdf/2411.10334"]}
{"year":"2024","title":"Yankari: A Monolingual Yoruba Dataset","authors":["M Akpobi - arXiv preprint arXiv:2412.03334, 2024"],"snippet":"This paper presents Yankari, a large-scale monolingual dataset for the Yoruba language, aimed at addressing the critical gap in Natural Language Processing (NLP) resources for this important West African language. Despite being spoken by over …","url":["https://arxiv.org/pdf/2412.03334"]}
{"year":"2024","title":"Yes, This Is A Puff Piece? A Comparative Analysis of the Vendor Defences of Puffery, Statements of Future Intent and Disclaimers–Part 2—How far does the …","authors":["J Beardwood - Computer Law Review International, 2024"],"snippet":"… Plaintiffs allege that “thousands” of their copyrighted works of journalism were caught in this “scrape,” stripped of their author, title, and copyright information, and input into at least three of OpenAI’s training sets (WebText, WebText2, and Common …","url":["https://www.degruyter.com/document/doi/10.9785/cri-2024-250605/html"]}
{"year":"2024","title":"Yi-Lightning Technical Report","authors":["A Wake, A Wang, B Chen, CX Lv, C Li, C Huang, C Cai… - arXiv preprint arXiv …, 2024"],"snippet":"This technical report presents Yi-Lightning, our latest flagship large language model (LLM). It achieves exceptional performance, ranking 6th overall on Chatbot Arena, with particularly strong results (2nd to 4th place) in specialized categories including …","url":["https://arxiv.org/pdf/2412.01253"]}
{"year":"2024","title":"Yi: Open Foundation Models by 01. AI","authors":["A Young, B Chen, C Li, C Huang, G Zhang, G Zhang… - arXiv preprint arXiv …, 2024"],"snippet":"… We start with web documents from Common Crawl, use the CCNet pipeline [79] for language identification and perplexity scoring. Then … Notably, the Chinese content extracted from Common Crawl present unique challenges, particularly with a …","url":["https://arxiv.org/pdf/2403.04652"]}
{"year":"2024","title":"Yuan 2.0-M32: Mixture of Experts with Attention Router","authors":["S Wu, J Luo, X Chen, L Li, X Zhao, T Yu, C Wang… - arXiv preprint arXiv …, 2024"],"snippet":"Yuan 2.0-M32, with a similar base architecture as Yuan-2.0 2B, uses a mixture-of-experts architecture with 32 experts of which 2 experts are active. A new router network, Attention Router, is proposed and adopted for a more efficient selection of experts …","url":["https://arxiv.org/pdf/2405.17976"]}
{"year":"2024","title":"YuLan: An Open-source Large Language Model","authors":["Y Zhu, K Zhou, K Mao, W Chen, Y Sun, Z Chen, Q Cao… - arXiv preprint arXiv …, 2024"],"snippet":"… In addition to these sources, we process raw data from Common Crawl (CC) dumps, particularly focusing on events that occurred between January 2021 and February 2023. To manage the practical challenges of HTML content extraction and …","url":["https://arxiv.org/pdf/2406.19853"]}
{"year":"2024","title":"Zero and Few Short Learning Using Large Language Models for De-Identification of Medical Records","authors":["YS Yashwanth, R Shettar - IEEE Access, 2024"],"snippet":"… Among the word embeddings, CommonCrawl, a general English word embedding, demonstrated superior performance compared to the other four. The highest F-measure for CommonCrawl was 96.46, with corresponding precision and recall scores of …","url":["https://ieeexplore.ieee.org/iel8/6287639/6514899/10630540.pdf"]}
{"year":"2024","title":"Zero-Shot Distillation for Image Encoders: How to Make Effective Use of Synthetic Data","authors":["N Popp, JH Metzen, M Hein - arXiv preprint arXiv:2404.16637, 2024"],"snippet":"… The first one involves relying on large-scale data such as common crawl datasets [7,38]. While this approach is feasible for large foundation models, it poses challenges for smaller models as these lack the same level of generalization capabilities due to …","url":["https://arxiv.org/pdf/2404.16637"]}
{"year":"2024","title":"Zero-shot learning for multilingual discourse relation classification","authors":["E Metheniti, P Muller, C Braud, M Hernández-Casas - 5th Workshop on …, 2024"],"snippet":"Classifying discourse relations is a hard task: discourse-annotated data is scarce, especially for languages other than English, and there exist different theoretical frameworks that affect textual spans to be linked and the label set used. Thus, work …","url":["https://hal.science/hal-04483805/document"]}
{"year":"2024","title":"Zero-Shot Prompting and Few-Shot Fine-Tuning: Revisiting Document Image Classification Using Large Language Models","authors":["A Scius-Bertrand, M Jungo, L Vögtlin, JM Spat… - International Conference on …, 2025"],"snippet":"… LLMs typically rely on unsupervised pre-training of decoder-only transformer architectures on a large body of texts from the internet, such as the Common Crawl dataset [17], followed by reinforcement learning from human feedback, to achieve …","url":["https://link.springer.com/chapter/10.1007/978-3-031-78495-8_10"]}
{"year":"2024","title":"Zero-shot Sentiment Analysis in Low-Resource Languages Using a Multilingual Sentiment Lexicon","authors":["F Koto, T Beck, Z Talat, I Gurevych, T Baldwin - arXiv preprint arXiv:2402.02113, 2024"],"snippet":"Improving multilingual language models capabilities in low-resource languages is generally difficult due to the scarcity of large-scale data in those languages. In this paper, we relax the reliance on texts in low-resource languages by using …","url":["https://arxiv.org/pdf/2402.02113"]}
{"year":"2024","title":"Zero-Shot vs. Few-Shot Multi-Speaker TTS Using Pre-trained Czech SpeechT5 Model","authors":["J Lehečka, Z Hanzlíček, J Matoušek, D Tihelka - arXiv preprint arXiv:2407.17167, 2024"],"snippet":"… Text Data As a source of unlabeled text data, we used the Common Crawl project4 which is a huge public web archive consisting of petabytes of crawled web pages. We used the language information provided in the index files to select Czech …","url":["https://arxiv.org/pdf/2407.17167"]}
{"year":"2024","title":"Zeroth-Order Adaptive Neuron Alignment Based Pruning without Re-Training","authors":["E Cunegatti, LL Custode, G Iacca - arXiv preprint arXiv:2411.07066, 2024"],"snippet":"Network pruning is a set of computational techniques that aim to reduce a given model's computational cost by removing a subset of its parameters while having minimal impact on performance. Throughout the last decade, the most widely used …","url":["https://arxiv.org/pdf/2411.07066?"]}
{"year":"2024","title":"ZIP-FIT: Embedding-Free Data Selection via Compression-Based Alignment","authors":["E Obbad, I Mlauzi, B Miranda, R Schaeffer, K Obbad… - arXiv preprint arXiv …, 2024"],"snippet":"Data selection is crucial for optimizing language model (LM) performance on specific tasks, yet most existing methods fail to effectively consider the target task distribution. Current approaches either ignore task-specific requirements entirely or …","url":["https://arxiv.org/pdf/2410.18194"]}
{"year":"2024","title":"Zipfian Whitening","authors":["S Yokoi, H Bao, H Kurita, H Shimodaira - arXiv preprint arXiv:2411.00680, 2024"],"snippet":"The word embedding space in neural models is skewed, and correcting this can improve task performance. We point out that most approaches for modeling, correcting, and measuring the symmetry of an embedding space implicitly assume …","url":["https://arxiv.org/pdf/2411.00680"]}
{"year":"2024","title":"ZS4C: Zero-Shot Synthesis of Compilable Code for Incomplete Code Snippets using ChatGPT","authors":["A Kabir, S Wang, Y Tian, M Asaduzzaman, W Zhang - arXiv preprint arXiv …, 2024"],"snippet":"Technical question and answering (Q&A) sites such as Stack Overflow have become an important source for software developers to seek knowledge. However, code snippets on Q&A sites are usually uncompilable and semantically incomplete for …","url":["https://arxiv.org/pdf/2401.14279"]}
{"year":"2024","title":"Zyda-2: a 5 Trillion Token High-Quality Dataset","authors":["Y Tokpanov, P Glorioso, Q Anthony, B Millidge - arXiv preprint arXiv:2411.06068, 2024"],"snippet":"… Given that all open datasets ultimately originated from similar Common Crawl scrapes, we expect them to contain significant fractions of duplicated documents. Deduplication has been found to generally improve language modeling performance (Lee et al.…","url":["https://arxiv.org/pdf/2411.06068"]}
{"year":"2024","title":"Zyda: A 1.3 T Dataset for Open Language Modeling","authors":["Y Tokpanov, B Millidge, P Glorioso, J Pilault, A Ibrahim… - arXiv preprint arXiv …, 2024"],"snippet":"… Additionally, unlike these works which directly filter from Common Crawl, we aim to instead collect and collate existing open-source datasets under one banner, and to uniformly filter and deduplicate them against one another so as to create a dataset …","url":["https://arxiv.org/pdf/2406.01981"]}