rajkumarrawal (Rajkumar rawal)

reacted to their post with 👍 7 days ago

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184

I submitted a "Continual GUI Agents" Paper by Ziwei Liu, Borul Kang, Hangjie Yuan, Zixiang Zhao, Wei li, Yifan Zhu, Tao Feng ,
From

Tsinghua ,

ZhejiangUniversity ,

ethz ,

BUPT2023213296 . to Daily Papers on

huggingface .

Continual GUI Agents framework addresses performance degradation in dynamic digital environments through reinforcement fine tuning with novel anchoring rewards that stabilize learning across shifting UI domains and resolutions.

Continual GUI Agents (2601.20732)

posted an update 7 days ago

Post

184

I submitted a "Continual GUI Agents" Paper by Ziwei Liu, Borul Kang, Hangjie Yuan, Zixiang Zhao, Wei li, Yifan Zhu, Tao Feng ,
From

Tsinghua ,

ZhejiangUniversity ,

ethz ,

BUPT2023213296 . to Daily Papers on

huggingface .

Continual GUI Agents framework addresses performance degradation in dynamic digital environments through reinforcement fine tuning with novel anchoring rewards that stabilize learning across shifting UI domains and resolutions.

Continual GUI Agents (2601.20732)

reacted to their post with 👍 10 days ago

Post

3661

I submitted a "FlashLabs Chroma 1.0: A Real-Time End-to-End Spoken Dialogue Model with Personalized Voice Cloning" Paper by Tanyu Chen, Tairan Chen, Kai shen , Zhenghua Bao, Zhihui Zhang, Man Yuan, Yi Shi From

FlashLabs to Daily Papers on

huggingface .

Chroma 1.0 enables real time spoken dialogue with personalized voice cloning through discrete speech representations and interleaved text audio token scheduling.

Chroma 1.0 , the world’s first open source, real time speech to speech model with voice cloning.

FlashLabs Chroma 1.0: A Real-Time End-to-End Spoken Dialogue Model with Personalized Voice Cloning (2601.11141)

posted an update 10 days ago

Post

3661

I submitted a "FlashLabs Chroma 1.0: A Real-Time End-to-End Spoken Dialogue Model with Personalized Voice Cloning" Paper by Tanyu Chen, Tairan Chen, Kai shen , Zhenghua Bao, Zhihui Zhang, Man Yuan, Yi Shi From

FlashLabs to Daily Papers on

huggingface .

Chroma 1.0 enables real time spoken dialogue with personalized voice cloning through discrete speech representations and interleaved text audio token scheduling.

Chroma 1.0 , the world’s first open source, real time speech to speech model with voice cloning.

FlashLabs Chroma 1.0: A Real-Time End-to-End Spoken Dialogue Model with Personalized Voice Cloning (2601.11141)

reacted to their post with 👍 22 days ago

Post

854

I submitted a "AgencyBench: Benchmarking the Frontiers of Autonomous Agents in 1M-Token Real-World Contexts" Paper by @weizhihao1KeyuLi Junhao shi @dqwangDequan Wang @YangXiao-nlpYang Xiao Mohan Jiang @Sunshine279Jie Sun Yunze Wu Shijie Xia Xiaojie Cai Tianze Xu Weiye Si Wenjie Li Pengfei Liu From

SJTU Shanghai Jiao Tong University

PolyUHK The Hong Kong Polytechnic University GAIRSII-GAIR to Daily Papers on huggingfaceHugging Face.

A potentially another direction for Benchmarking the Frontiers of Autonomous Agents in 2026

Some of the observations founded are :-

-- Long-horizon tasks remain challenging :
Even frontier models struggle with sustained reasoning over real world tasks that require 1M tokens and 90 tool calls, indicating limits in long context autonomy.

-- Proprietary models outperform open source models:
Closed source models achieve a higher average score (48.4%) than open source counterparts (32.1%), revealing a persistent performance gap on complex agentic tasks.

-- Feedback driven self correction varies widely:
Models like GPT 5.2 and Claude show strong gains from iterative feedback, while others (e.g. DeepSeek V3.2) exhibit minimal or no improvement after feedback.

-- Efficiency trade offs are significant:
High performing models often consume far more tokens and time, some models (e.g. Grok 4.1 Fast) are more token efficient despite lower absolute scores.

-- Agentic scaffolds strongly influence performance:
Models tend to perform best within their native or optimized ecosystems, highlighting that agent performance depends on tight coupling between the model and its scaffold not the model alone.

..... many more...

AgencyBench: Benchmarking the Frontiers of Autonomous Agents in 1M-Token Real-World Contexts (2601.11044)

1 reply

·

replied to their post 22 days ago

https://huggingface.co/papers/2601.11044

posted an update 22 days ago

Post

854

I submitted a "AgencyBench: Benchmarking the Frontiers of Autonomous Agents in 1M-Token Real-World Contexts" Paper by @weizhihao1KeyuLi Junhao shi @dqwangDequan Wang @YangXiao-nlpYang Xiao Mohan Jiang @Sunshine279Jie Sun Yunze Wu Shijie Xia Xiaojie Cai Tianze Xu Weiye Si Wenjie Li Pengfei Liu From

SJTU Shanghai Jiao Tong University

PolyUHK The Hong Kong Polytechnic University GAIRSII-GAIR to Daily Papers on huggingfaceHugging Face.

A potentially another direction for Benchmarking the Frontiers of Autonomous Agents in 2026

Some of the observations founded are :-

-- Long-horizon tasks remain challenging :
Even frontier models struggle with sustained reasoning over real world tasks that require 1M tokens and 90 tool calls, indicating limits in long context autonomy.

-- Proprietary models outperform open source models:
Closed source models achieve a higher average score (48.4%) than open source counterparts (32.1%), revealing a persistent performance gap on complex agentic tasks.

-- Feedback driven self correction varies widely:
Models like GPT 5.2 and Claude show strong gains from iterative feedback, while others (e.g. DeepSeek V3.2) exhibit minimal or no improvement after feedback.

-- Efficiency trade offs are significant:
High performing models often consume far more tokens and time, some models (e.g. Grok 4.1 Fast) are more token efficient despite lower absolute scores.

-- Agentic scaffolds strongly influence performance:
Models tend to perform best within their native or optimized ecosystems, highlighting that agent performance depends on tight coupling between the model and its scaffold not the model alone.

..... many more...

AgencyBench: Benchmarking the Frontiers of Autonomous Agents in 1M-Token Real-World Contexts (2601.11044)

1 reply

·

reacted to their post with 👍 25 days ago

Post

666

"Recursive Language Models" Paper become "3rd Paper of the day" on Hugging Face

Recursive Language Models (2512.24601)

posted an update 27 days ago

Post

666

"Recursive Language Models" Paper become "3rd Paper of the day" on Hugging Face

Recursive Language Models (2512.24601)

reacted to YatharthS's post with 👍 about 2 months ago

Post

3692

🤯 🤯 Released a high quality finetuned LLM based TTS model that can generate realistic and clear 48khz audio at over 100x realtime speed! 🤯 🤯

Github link: https://github.com/ysharma3501/MiraTTS

Model link: https://github.com/ysharma3501/MiraTTS

Blog explaining llm tts models: https://huggingface.co/blog/YatharthS/llm-tts-models

4 replies

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reacted to danielhanchen's post with 👍 about 2 months ago

Post

5537

NVIDIA releases Nemotron 3 Nano, a new 30B hybrid reasoning model! 🔥

Has 1M context window & best in class performance for SWE-Bench, reasoning & chat. Run the MoE model locally with 24GB RAM.

GGUF: unsloth/Nemotron-3-Nano-30B-A3B-GGUF
💚 Step-by-step Guide: https://docs.unsloth.ai/models/nemotron-3

1 reply

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reacted to danielhanchen's post with 👍 about 2 months ago

Post

2484

Google releases FunctionGemma, a new 270M parameter model that runs on just 0.5 GB RAM.✨

Built for tool-calling, run locally on your phone at 50+ tokens/s, or fine-tune with Unsloth & deploy to your phone.

GGUF: unsloth/functiongemma-270m-it-GGUF
Docs + Notebook: https://docs.unsloth.ai/models/functiongemma

2 replies

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reacted to their post with 👍 about 2 months ago

Post

1919

" An open standardized protocol enabling communication for autonomous robots to exchange data, coordinate tasks, and collaborate in real-time environments in the age of AI ". r2r-protocol (Robot2Robot Protocol) is now officially open source! 🔓

"pip install r2r-protocol"

Whether you're a developer, researcher, or tech enthusiast, we invite you to explore, use, and contribute to the project.

🔗 Check it out here: [ https://github.com/Tech-Parivartan/r2r-protocol?tab=readme-ov-file ]

Let’s build the future together! 💡

AiParivartanResearchLab

techparivartan

Documentation of the r2r-protocal : [ https://techparivartanai.notion.site/Robot-to-Robot-r2r-Protocol-1f008f0fb18780439d70e8b9bbbdb869 ]

The R2R Protocol enables seamless robot-to-robot interaction across industrial automation, swarm robotics, logistics, and multi-agent systems. It defines structured message formats, negotiation logic, discovery mechanisms, and extensible APIs.

#r2r_protocol #robot2robot_protocol #ai #aiparivartanresearchlab #techparivartan

https://huggingface.co/blog/rajkumarrawal/rawalraj

posted an update about 2 months ago

Post

1919

" An open standardized protocol enabling communication for autonomous robots to exchange data, coordinate tasks, and collaborate in real-time environments in the age of AI ". r2r-protocol (Robot2Robot Protocol) is now officially open source! 🔓

"pip install r2r-protocol"

Whether you're a developer, researcher, or tech enthusiast, we invite you to explore, use, and contribute to the project.

🔗 Check it out here: [ https://github.com/Tech-Parivartan/r2r-protocol?tab=readme-ov-file ]

Let’s build the future together! 💡

AiParivartanResearchLab

techparivartan

Documentation of the r2r-protocal : [ https://techparivartanai.notion.site/Robot-to-Robot-r2r-Protocol-1f008f0fb18780439d70e8b9bbbdb869 ]

The R2R Protocol enables seamless robot-to-robot interaction across industrial automation, swarm robotics, logistics, and multi-agent systems. It defines structured message formats, negotiation logic, discovery mechanisms, and extensible APIs.

#r2r_protocol #robot2robot_protocol #ai #aiparivartanresearchlab #techparivartan

https://huggingface.co/blog/rajkumarrawal/rawalraj

replied to their post 2 months ago

https://github.com/rawalraj022/aiprl-llm-intelligence-report/blob/main/2025_AD_Top_LLM_Benchmark_Evaluations/9)September(2025)/Core_Knowledge_%26_Reasoning_Benchmarks/Core_Knowledge_%26_Reasoning_Benchmarks.pdf

replied to their post 2 months ago

Research Highlights :
Comparative insights, evaluation methodologies, and industry trends for AI decision makers.

Disclaimer:
This comprehensive Core Knowledge & Reasoning analysis represents the current state of large language model capabilities as of September 2025. All performance metrics are based on standardized evaluations and may vary based on specific implementation details, hardware configurations, and testing methodologies. Users are advised to consult original research papers and official documentation for detailed technical insights and application guidelines. Individual model performance may differ in real-world scenarios and should be validated accordingly. If there are any discrepancies or updates beyond this report, please refer to the respective model providers for the most current information.

reacted to their post with 👍 2 months ago

Post

2839

September(2025) LLM Core Knowledge & Reasoning Benchmarks Report By

AiParivartanResearchLab (AIPRL-LIR)

Monthly LLM's Intelligence Reports for AI Decision Makers :
Our "aiprl-llm-intelligence-report" repo to establishes (AIPRL-LIR) framework for Large Language Model overall evaluation and analysis through systematic monthly intelligence reports. Unlike typical AI research papers or commercial reports. It provides structured insights into AI model performance, benchmarking methodologies, Multi-hosting provider analysis, industry trends ...

( all in one monthly report ) Leading Models & Companies, 23 Benchmarks in 6 Categories, Global Hosting Providers, & Research Highlights

Here’s what you’ll find inside this month’s intelligence report:-

Leading Models & Companies :

openai ,

Anthropic ,

meta-llama ,

deepmind

google ,

mistralai ,

Cohere ,

Qwen ,

deepseek-ai ,

MicrosoftResearch ,

amazonwebservices ,

nvidia ,

grokgpt-org and more.

23 Benchmarks in 6 Categories :
With a special focus on Core Knowledge & Reasoning performance across diverse tasks.

Repository link is in comments below :

https://huggingface.co/blog/rajkumarrawal/september-2025-aiprl-lir-core-knowledge-reasoning#6935ab96da60512619b7cf1f

4 replies

·

posted an update 2 months ago

Post

2839

September(2025) LLM Core Knowledge & Reasoning Benchmarks Report By

AiParivartanResearchLab (AIPRL-LIR)

Monthly LLM's Intelligence Reports for AI Decision Makers :
Our "aiprl-llm-intelligence-report" repo to establishes (AIPRL-LIR) framework for Large Language Model overall evaluation and analysis through systematic monthly intelligence reports. Unlike typical AI research papers or commercial reports. It provides structured insights into AI model performance, benchmarking methodologies, Multi-hosting provider analysis, industry trends ...

( all in one monthly report ) Leading Models & Companies, 23 Benchmarks in 6 Categories, Global Hosting Providers, & Research Highlights

Here’s what you’ll find inside this month’s intelligence report:-

Leading Models & Companies :

openai ,

Anthropic ,

meta-llama ,

deepmind

google ,

mistralai ,

Cohere ,

Qwen ,

deepseek-ai ,

MicrosoftResearch ,

amazonwebservices ,

nvidia ,

grokgpt-org and more.

23 Benchmarks in 6 Categories :
With a special focus on Core Knowledge & Reasoning performance across diverse tasks.

Repository link is in comments below :

https://huggingface.co/blog/rajkumarrawal/september-2025-aiprl-lir-core-knowledge-reasoning#6935ab96da60512619b7cf1f

4 replies

·

reacted to their post with 👍 2 months ago

Post

1144

September(2025) LLM Commonsense & Social Benchmarks Report By

AiParivartanResearchLab (AIPRL-LIR)

Monthly LLM's Intelligence Reports for AI Decision Makers :
Our "aiprl-llm-intelligence-report" repo to establishes (AIPRL-LIR) framework for Large Language Model overall evaluation and analysis through systematic monthly intelligence reports. Unlike typical AI research papers or commercial reports. It provides structured insights into AI model performance, benchmarking methodologies, Multi-hosting provider analysis, industry trends ...

( all in one monthly report ) Leading Models & Companies, 23 Benchmarks in 6 Categories, Global Hosting Providers, & Research Highlights

Here’s what you’ll find inside this month’s intelligence report:-

Leading Models & Companies :

openai ,

Anthropic ,

meta-llama ,

google

deepmind ,

mistralai ,

Cohere ,

Qwen ,

deepseek-ai ,

MicrosoftResearch ,

amazonwebservices ,

nvidia ,

grokgpt-org and more.

23 Benchmarks in 6 Categories :
With a special focus on Commonsense & Social performance across diverse tasks.

Repository link is in comments below :

https://huggingface.co/blog/rajkumarrawal/september-2025-aiprl-lir-commonsense-social

2 replies

·

replied to their post 2 months ago

https://github.com/rawalraj022/aiprl-llm-intelligence-report/blob/main/2025_AD_Top_LLM_Benchmark_Evaluations/9)September(2025)/Commonsense_%26_Social_Benchmarks/Commonsense_%26_Social_Benchmarks.pdf

Rajkumar rawal

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Rajkumar rawal

AI & ML interests

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