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README.md

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 <img src="imgs/github.svg" width="15px" style="display:inline;"> <a href="https://github.com/TIGER-AI-Lab/OpenResearcher" target="_blank">Github</a> | 🤗 <a href="https://huggingface.co/collections/TIGER-Lab/openresearcher" target="_blank">HuggingFace</a> ｜ <img src="imgs/notion.svg" width="15px" style="display:inline;"> <a href="https://boiled-honeycup-4c7.notion.site/OpenResearcher-A-Fully-Open-Pipeline-for-Long-Horizon-Deep-Research-Trajectory-Synthesis-2f7e290627b5800cb3a0cd7e8d6ec0ea?source=copy_link" target="_blank">Blog</a> ｜ <img src="imgs/slack.png" width="14px" style="display:inline;"> <a href="https://join.slack.com/t/openresearcher/shared_invite/zt-3p0r32cky-PqtZkVjjWIAI14~XwcRMfQ" target="_blank">Slack</a> | <img src="imgs/wechat.svg" width="14px" style="display:inline;"> <a href="imgs/wechat_group.png" target="_blank">WeChat</a> 
 
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+## Overview 
+**OpenResearcher** is a fully open agentic large language model (30B-A3B) designed for **long-horizon deep research** scenarios. It achieves an impressive **54.8%** accuracy on [BrowseComp-Plus](https://huggingface.co/spaces/Tevatron/BrowseComp-Plus), surpassing performance of `GPT-4.1`, `Claude-Opus-4`, `Gemini-2.5-Pro`, `DeepSeek-R1` and `Tongyi-DeepResearch`. It also demonstrates **leading performance** across a range of deep research benchmarks, including BrowseComp, GAIA, WebWalkerQA, and xbench-DeepSearch. We **fully open-source** the training and evaluation recipe—including data, model, training methodology, and evaluation framework for everyone to progress deep research.
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+## OpenResearcher Corpus 
+This dataset contains a carefully curated ~11B-tokens corpus, which serves as an offline search engine for our data generation process, eliminating the need for external Search APIs.
+
+## Format
+Each row in the dataset contains the following fields:
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+qid (int64): A unique identifier for each question or task.
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+question (string): The original deepresearch question compiled from MiroVerse.
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+answer (string): The final answer to the question.
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+messages (list): A list of messages representing the GPT-OSS 120B deep research trajectory, including intermediate reasoning steps, tool calls, observations, and model responses throughout the problem-solving process.
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+## How to use this dataset?
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