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Paper2Agent:将研究论文重塑为交互式且可靠的AI智能体

Paper2Agent: Reimagining Research Papers As Interactive and Reliable AI Agents

September 8, 2025
作者: Jiacheng Miao, Joe R. Davis, Jonathan K. Pritchard, James Zou
cs.AI

摘要

我们推出Paper2Agent,一个将研究论文自动转化为AI代理的框架。Paper2Agent将研究成果从被动的人工制品转变为能加速下游应用、采纳与发现的主动系统。传统研究论文要求读者投入大量精力去理解并调整论文中的代码、数据及方法以适应自身工作,这为传播与重用设置了障碍。Paper2Agent通过自动将论文转化为一个知识渊博的研究助手型AI代理,解决了这一难题。它利用多个代理系统分析论文及其关联代码库,构建模型上下文协议(MCP)服务器,随后迭代生成并运行测试以精炼和强化最终的MCP。这些论文MCP可灵活连接至聊天代理(如Claude Code),通过自然语言执行复杂的科学查询,同时调用原论文中的工具和工作流。我们通过深入案例研究展示了Paper2Agent在创建可靠且能力强的论文代理方面的有效性。Paper2Agent创建了一个利用AlphaGenome解读基因组变异的代理,以及基于ScanPy和TISSUE执行单细胞和空间转录组学分析的代理。我们验证了这些论文代理能够复现原论文结果,并能正确执行用户的新查询。通过将静态论文转变为动态、交互式的AI代理,Paper2Agent引入了一种新的知识传播范式,并为AI协作科学家生态系统奠定了基础。
English
We introduce Paper2Agent, an automated framework that converts research papers into AI agents. Paper2Agent transforms research output from passive artifacts into active systems that can accelerate downstream use, adoption, and discovery. Conventional research papers require readers to invest substantial effort to understand and adapt a paper's code, data, and methods to their own work, creating barriers to dissemination and reuse. Paper2Agent addresses this challenge by automatically converting a paper into an AI agent that acts as a knowledgeable research assistant. It systematically analyzes the paper and the associated codebase using multiple agents to construct a Model Context Protocol (MCP) server, then iteratively generates and runs tests to refine and robustify the resulting MCP. These paper MCPs can then be flexibly connected to a chat agent (e.g. Claude Code) to carry out complex scientific queries through natural language while invoking tools and workflows from the original paper. We demonstrate Paper2Agent's effectiveness in creating reliable and capable paper agents through in-depth case studies. Paper2Agent created an agent that leverages AlphaGenome to interpret genomic variants and agents based on ScanPy and TISSUE to carry out single-cell and spatial transcriptomics analyses. We validate that these paper agents can reproduce the original paper's results and can correctly carry out novel user queries. By turning static papers into dynamic, interactive AI agents, Paper2Agent introduces a new paradigm for knowledge dissemination and a foundation for the collaborative ecosystem of AI co-scientists.
PDF223September 9, 2025