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English(EN) M3OS: A Monte Carlo Graph Search-Orchestrated Multi-Agent LLM System for Evidence-Traced Molecular Optimization

M3OS系统通过多智能体LLM增强分子优化

研究人员开发了M3OS,一个新颖的多智能体系统,旨在利用大型语言模型(LLM)优化分子设计。该系统通过采用蒙特卡洛图搜索来链接已评估的候选分子、转化证据和任务约束,从而将推理过程与状态管理分离开来。M3OS利用具有特定角色上下文的专用智能体和一个持久化图来维护优化轨迹,在三个分子优化基准测试中表现优于现有方法。 AI

影响 该系统展示了一种将LLM与结构化搜索相结合以解决复杂优化任务的新颖方法,有望提高科学发现的效率。

排序理由 该集群描述了一个新系统和一份详细介绍其在基准测试中表现的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 Hugging Face Daily Papers 阅读 →

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M3OS系统通过多智能体LLM增强分子优化

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该集群描述了一个新系统和一份详细介绍其在基准测试中表现的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [2]

  1. arXiv cs.CL TIER_1 English(EN) · Shicheng Fang, Yuxin Wang, Zhuo Yang, Xiaohu Xu, Jiahao Lu, Chuanyuan Tan, Tong Zhu, Yining Zheng, Xipeng Qiu ·

    MARCO:用于条件分子优化的多轮代理强化学习

    arXiv:2609.36683v1 Announce Type: cross Abstract: Molecular optimization is inherently iterative: a candidate is proposed, evaluated against several objectives, and revised while preserving a relationship to the source molecule. Most instruction-following models instead emit one …

  2. Hugging Face Daily Papers TIER_1 English(EN) ·

    M3OS:一种蒙特卡洛图搜索编排的多智能体LLM系统,用于证据追踪的分子优化

    Small-molecule optimization integrates medicinal-chemistry reasoning and computational evidence through iterative, multi-objective decisions. When large language models (LLMs) reason over optimization histories stored primarily in conversational context, they must recover candida…