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Add six papers on multi-agent systems and scientific discovery #23

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20 changes: 20 additions & 0 deletions README.md
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Expand Up @@ -183,6 +183,10 @@ This repository serves as a comprehensive survey of context engineering techniqu
<a href="https://github.com/Graph-RAG/GraphRAG/" target="_blank">
<img src="https://img.shields.io/github/stars/Graph-RAG/GraphRAG.svg?style=social" alt="GitHub stars">
</a></li>
<li><i><b>The Landscape of Agentic Reinforcement Learning for LLMs: A Survey</b></i>, Zhang et al., <a href="https://arxiv.org/abs/2509.02547" target="_blank"><img src="https://img.shields.io/badge/arXiv-2025.09-red" alt="arXiv Badge"></a>
<a href="https://github.com/xhyumiracle/Awesome-AgenticLLM-RL-Papers" target="_blank">
<img src="https://img.shields.io/github/stars/xhyumiracle/Awesome-AgenticLLM-RL-Papers.svg?style=social" alt="GitHub stars">
</a></li>
</ul>

<b>Benchmarks</b>
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<li><i><b>Model Context Protocol (MCP)</b></i>, Anthropic, <a href="https://github.com/modelcontextprotocol" target="_blank"><img src="https://img.shields.io/badge/GitHub-2024-white" alt="GitHub Badge"></a>
</li>
<li><i><b>CoMAS: Co-Evolving Multi-Agent Systems via Interaction Rewards</b></i>, Xue et al., <a href="https://arxiv.org/abs/2510.08529" target="_blank"><img src="https://img.shields.io/badge/arXiv-2025.10-red" alt="arXiv Badge"></a>
</li>
<li><i><b>Achilles Heel of Distributed Multi-Agent Systems</b></i>, Zhang et al., <a href="https://arxiv.org/abs/2504.07461" target="_blank"><img src="https://img.shields.io/badge/arXiv-2025.04-red" alt="arXiv Badge"></a>
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</ul>


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<li><i><b>Agent-Pro: Learning to Evolve Coder Agents via Proposal-based Programming</b></i>, Zhang et al., <a href="https://arxiv.org/abs/2402.17574" target="_blank"><img src="https://img.shields.io/badge/arXiv-2024.05-red" alt="arXiv Badge">
</a></li>
<li><i><b>GenoTEX: An LLM Agent Benchmark for Automated Gene Expression Data Analysis</b></i>, Liu et al., <a href="https://arxiv.org/abs/2406.15341" target="_blank"><img src="https://img.shields.io/badge/MLCB-2025.06-blue" alt="MLCB Badge"></a>
<a href="https://github.com/Liu-Hy/GenoTEX" target="_blank">
<img src="https://img.shields.io/github/stars/Liu-Hy/GenoTEX.svg?style=social" alt="GitHub stars">
</a></li>
</ul>


Expand Down Expand Up @@ -1706,6 +1718,14 @@ This discipline is foundational for unlocking the full potential of LLMs in prod
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<li><i><b>Solving Olympiad Geometry without Human Demonstrations</b></i>, Trinh et al., <a href="https://www.nature.com/articles/s41586-023-06747-5" target="_blank"><img src="https://img.shields.io/badge/Nature-2024.01-blue" alt="Nature Badge"></a>
</li>
<li><i><b>GenoMAS: A Multi-Agent Framework for Scientific Discovery via Code-Driven Gene Expression Analysis</b></i>, Liu et al., <a href="https://arxiv.org/abs/2507.21035" target="_blank"><img src="https://img.shields.io/badge/arXiv-2025.07-red" alt="arXiv Badge"></a>
<a href="https://github.com/Liu-Hy/GenoMAS" target="_blank">
<img src="https://img.shields.io/github/stars/Liu-Hy/GenoMAS.svg?style=social" alt="GitHub stars">
</a></li>
<li><i><b>aiXiv: A Next-Generation Open Access Ecosystem for Scientific Discovery Generated by AI Scientists</b></i>, Zhang et al., <a href="https://arxiv.org/abs/2508.15126" target="_blank"><img src="https://img.shields.io/badge/arXiv-2025.08-red" alt="arXiv Badge"></a>
<a href="https://github.com/aixiv-org/aiXiv" target="_blank">
<img src="https://img.shields.io/github/stars/aixiv-org/aiXiv.svg?style=social" alt="GitHub stars">
</a></li>
</ul>

<b>AI for Science Integration and Future Directions</b>
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