Update README.md

README.md

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 This repository contains the dataset for **Finch**, an enterprise-grade benchmark for evaluating an agent’s ability to work like a skilled finance & accounting expert (work IQ) on real-world professionel workflows.
 
-* **Paper**: https://arxiv.org/abs/2512.13168
-* **Project Page**: https://huggingface.co/datasets/FinWorkBench/Finch  
-* **Code**: _to be added_
+* **Paper**: https://arxiv.org/abs/2512.13168 
 
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@@ -51,18 +49,43 @@ The workflows are derived from **real-world enterprise workspaces** (primarily E
 
 We adopt a three-step workflow labeling process:
 
-1. **Inducing workflow types and instances** from real collaborative context in **enterprise email threads** (Enron Corpus: 500,000 emails from 150 executives and employees).  
-2. **Deriving concrete workflow instances** by analyzing changes across **spreadsheet versions** (15,000 versioned spreadsheets from Enron and EUSES) and designing workflows based on high-quality artifacts from investment and securities companies, World Bank, Canadian/British government agencies, WideSearch, Dabstep, and more.  
+1. **Inducing workflow types and instances** from real collaborative context in **enterprise email threads** ([Enron Corpus](https://en.wikipedia.org/wiki/Enron_Corpus): 500,000 emails from 150 executives and employees).  
+2. **Deriving concrete workflow instances** by analyzing changes across **spreadsheet versions** (15,000 versioned spreadsheets from Enron and [EUSES](https://dl.acm.org/doi/10.1145/1082983.1083242)) and designing workflows based on high-quality artifacts from investment and securities companies, World Bank, Canadian/British government agencies, WideSearch, Dabstep, and more.  
 3. **Conductin meticulous expert annotation** of task instructions, input files, and reference outputs, involving hundreds of hours of expert work.
 
-This process yields **172 enterprise-grade workflows—primarily multi-task composite**, involving 1,710 spreadsheets and 27 million cells, capturing the intrinsic **compositional, messy, multimodal, and collaborative nature** of real-world finance & accounting work. In this release, we provide full annotations for the first 72 workflows, with the remaining 100 to be released in a subsequent update.
+![Results](figs/annotation.png)
 
-Experiment results show that even frontier agents (GPT 5.1 Pro and Claude Sonnet 4.5 Pro) solve fewer than 40% of the workflows, revealing a substantial performance gap for real-world enterprise scenarios.
+This process yields **172 enterprise-grade workflows—primarily multi-task composite**, involving 1,710 spreadsheets and 27 million cells, capturing the intrinsic **messy, long-horizon, knowledge-intensive, and collaborative nature** of real-world finance & accounting work. In this release, we provide full annotations for the first 72 workflows, with the remaining 100 to be released in a subsequent update.
+
+![Results](figs/distribution_chart.png)
+
+We conduct both human and automated evaluations of frontier AI systems including GPT5.1, Claude Sonnet 4.5, Gemini 3 Pro, Grok 4, and Qwen 3 Max, and GPT 5.1 Pro spends 48 hours in total yet passes only 38.4% of workflows, while Claude Sonnet 4.5 passes just 25.0%, revealing a substantial performance gap for real-world enterprise scenarios.
 
 ![Results](figs/exp_results.jpeg)
 
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+## Examples
+
+Example 1: Review the Inv & WC Value Adj summary tab and add the missing cross‑sheet data references to the other worksheets so the roll‑up pulls the correct figures. Return the updated file with those links in place.
+
+![Results](figs/example_2.jpeg)
+
+Example 2: Add a new worksheet named "Scenario3" to the same workbook, mirroring the structure, row/column layout, monthly detail table, and chart area of "Scenario1". For Scenario3, update the hedging assumptions to a balanced allocation: 10-Yr 25%, 5-Yr 20%, 1-Yr 15%, May-Sep 20%, Q3 15%. Keep the note "Maximum Monthly Average Short Position to Cover (July Peak) = 30,508 MW" unchanged; only the new sheet should be added, and formulas may be used within it.
+
+![Results](figs/example_2.jpeg)
+
+Example 3: Transcribe the content from the image into the Excel file.
+
+![Results](figs/example_3.jpeg)
+
+Example 4: Per the red parameters and the Method 1/Method 2 guidance noted in H8 and H9, complete the formulas in columns T and U (starting from1), Note that the starting point for the formulas in columns T and U is 1, representing the initial signal to hold Index 1. In the formulas for columns T and U, 1 represents the signal to hold Index 1, -1 represents the signal to hold Index 2, and 0 represents the signal to make no change. Then complete column I. The method selection in B6 should drive the model so that all cells and charts refresh consistently when switching between methods.
+
+![Results](figs/example_4.jpeg)
+
+---
+
+
 ## 📁 Dataset Structure
 
 The instruction-tuning corpus is released in **JSONL** format.