aiXiv: A Next-Generation Open Access Ecosystem for Scientific Discovery
  Generated by AI Scientists
Authors: name: Pengsong Zhang; name: Xiang Hu; name: Guowei Huang; name: Yang Qi; name: Heng Zhang; name: Xiuxu Li; name: Jiaxing Song; name: Jiabin Luo; name: Yijiang Li; name: Shuo Yin; name: Chengxiao Dai; name: Eric Hanchen Jiang; name: Xiaoyan Zhou; name: Zhenfei Yin; name: Boqin Yuan; name: Jing Dong; name: Guinan Su; name: Guanren Qiao; name: Haiming Tang; name: Anghong Du; name: Lili Pan; name: Zhenzhong Lan; name: Xinyu Liu
Published: 2025-08-20 23:16:41

Abstract: 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 is available at https://github.com/aixiv-org. Website is available at
https://forms.gle/DxQgCtXFsJ4paMtn8.