OmniScientist：构建人类与AI科学家协同进化的科研生态系统

摘要

随着大语言模型（LLM）的快速发展，AI智能体在科学任务中的表现日益成熟，涵盖假设生成、实验设计乃至论文撰写等环节。此类智能体系统常被称为"AI科学家"。然而，现有AI科学家大多将科学发现简化为独立的搜索或优化问题，忽视了科学研究本质上是社会性协作行为这一事实。现实世界的科学活动依赖于由协作机制、贡献归属、同行评议及结构化科学知识网络构成的复杂科研基础设施。由于缺乏对这些关键维度的建模，现有系统难以建立真正的研究生态系统或与人类科学界深度互动。为弥补这一缺陷，我们提出OmniScientist框架，将人类科研的底层机制显式编码至AI科学工作流中。该框架不仅实现了从数据基础、文献综述、研究构思、实验自动化、科学写作到同行评审的端到端自动化，还通过模拟人类科学系统提供全方位基础设施支持，包括：（1）基于引文网络与概念关联的结构化知识体系；（2）支持多智能体无缝协作及人类研究者参与的开放式科研协议（OSP）；（3）基于双盲用户投票与Elo排序的开放评估平台（ScienceArena）。这一基础设施使智能体既能理解并利用人类知识体系，又能实现协作共演，最终培育出可持续、可扩展的创新生态系统。

English

With the rapid development of Large Language Models (LLMs), AI agents have demonstrated increasing proficiency in scientific tasks, ranging from hypothesis generation and experimental design to manuscript writing. Such agent systems are commonly referred to as "AI Scientists." However, existing AI Scientists predominantly formulate scientific discovery as a standalone search or optimization problem, overlooking the fact that scientific research is inherently a social and collaborative endeavor. Real-world science relies on a complex scientific infrastructure composed of collaborative mechanisms, contribution attribution, peer review, and structured scientific knowledge networks. Due to the lack of modeling for these critical dimensions, current systems struggle to establish a genuine research ecosystem or interact deeply with the human scientific community. To bridge this gap, we introduce OmniScientist, a framework that explicitly encodes the underlying mechanisms of human research into the AI scientific workflow. OmniScientist not only achieves end-to-end automation across data foundation, literature review, research ideation, experiment automation, scientific writing, and peer review, but also provides comprehensive infrastructural support by simulating the human scientific system, comprising: (1) a structured knowledge system built upon citation networks and conceptual correlations; (2) a collaborative research protocol (OSP), which enables seamless multi-agent collaboration and human researcher participation; and (3) an open evaluation platform (ScienceArena) based on blind pairwise user voting and Elo rankings. This infrastructure empowers agents to not only comprehend and leverage human knowledge systems but also to collaborate and co-evolve, fostering a sustainable and scalable innovation ecosystem.

OmniScientist：构建人类与AI科学家协同进化的科研生态系统

OmniScientist: Toward a Co-evolving Ecosystem of Human and AI Scientists

摘要

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