打造AI与人类共研的开放科研平台,让AI生成的研究能高效发表。
aiXiv: A Next-Generation Open Access Ecosystem for Scientific Discovery Generated by AI Scientists
- 构建多智能体系统,支持人机协同撰写与评审论文。
- 实验证明迭代修改后AI生成论文质量显著提升。
- 适合推动自主科研的开发者和关注AI生成内容的研究者。
大语言模型的发展使AI代理能够自主提出科学假设、开展实验、撰写论文并进行同行评审。然而,大量AI生成的研究内容面临发布渠道分散且封闭的问题。传统期刊和会议依赖人工审稿,难以扩展,普遍拒收AI生成内容;现有预印本平台(如arXiv)缺乏严格的质控机制。为此,我们推出aiXiv——一个面向人类与AI科学家的下一代开源科研平台。其多智能体架构支持研究提案与论文的人机协作提交、评审与迭代优化,并通过API与MCP接口实现异构人机科学家的无缝集成,构建可扩展、可拓展的自主科研生态。大量实验表明,aiXiv能可靠地提升AI生成研究提案与论文的质量。本工作为下一代开放获取科研生态系统奠定基础,加速高质量AI生成研究成果的发表与传播。
原文摘要 · Abstract (English)
Recent advances in large language models (LLMs) have enabled AI agents to autonomously generate scientific proposals, conduct experiments, author papers, and perform peer reviews. Yet this flood of AI-generated research content collides with a fragmented and largely closed publication ecosystem. Traditional journals and conferences rely on human peer review, making them difficult to scale and often reluctant to accept AI-generated research content; existing preprint servers (e.g. arXiv) lack rigorous quality-control mechanisms. Consequently, a significant amount of high-quality AI-generated research lacks appropriate venues for dissemination, hindering its potential to advance scientific progress. To address these challenges, we introduce aiXiv, a next-generation open-access platform for human and AI scientists. Its multi-agent architecture allows research proposals and papers to be submitted, reviewed, and iteratively refined by both human and AI scientists. It also provides API and MCP interfaces that enable seamless integration of heterogeneous human and AI scientists, creating a scalable and extensible ecosystem for autonomous scientific discovery. Through extensive experiments, we demonstrate that aiXiv is a reliable and robust platform that significantly enhances the quality of AI-generated research proposals and papers after iterative revising and reviewing on aiXiv. Our work lays the groundwork for a next-generation open-access ecosystem for AI scientists, accelerating the publication and dissemination of high-quality AI-generated research content. Code: https://github.com/aixiv-org aiXiv: https://aixiv.science
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品;中文卡片由大模型生成,请以原文为准。