aiXiv: A Next-Generation Open Access Ecosystem for Scientific Discovery
  Generated by AI Scientists
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.
68a8113e39413c456c05b1dc
Pengsong Zhang
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2025-08-22T13:07:00.348Z
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Pengsong Zhang
user
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Xiang Hu
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Guowei Huang
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2025-08-25T08:21:30.876Z
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Guowei Huang
user
Oliver12315
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Yang Qi
68a8113e39413c456c05b1e0
Heng Zhang
68a8113e39413c456c05b1e1
Xiuxu Li
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2025-08-25T08:21:28.123Z
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Xiuxu Li
user
Aplome
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Jiaxing Song
68a8113e39413c456c05b1e3
Jiabin Luo
admin_assigned
2025-08-22T13:07:10.454Z
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Jiabin Luo
user
King-play
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Yijiang Li
claimed_verified
2025-09-05T14:17:09.426Z
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William Li
user
williamium
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Shuo Yin
68a8113e39413c456c05b1e6
Chengxiao Dai
claimed_verified
2025-08-25T08:21:25.960Z
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DAI, CHENG XIAO
user
dcx666
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Eric Hanchen Jiang
68a8113e39413c456c05b1e8
Xiaoyan Zhou
68a8113e39413c456c05b1e9
Zhenfei Yin
claimed_verified
2025-09-03T08:30:01.695Z
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Zhenfei Yin
user
JeremyYin
68a8113e39413c456c05b1ea
Boqin Yuan
68a8113e39413c456c05b1eb
Jing Dong
68a8113e39413c456c05b1ec
Guinan Su
68a8113e39413c456c05b1ed
Guanren Qiao
68a8113e39413c456c05b1ee
Haiming Tang
68a8113e39413c456c05b1ef
Anghong Du
68a8113e39413c456c05b1f0
Lili Pan
68a8113e39413c456c05b1f1
Zhenzhong Lan
68a8113e39413c456c05b1f2
Xinyu Liu
aiXiv: A Next-Generation Open Access Ecosystem for Scientific Discovery
  Generated by AI Scientists
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.
aiXiv is an open-access platform that facilitates the submission, review, and refinement of scientific proposals and papers by both human and AI scientists, enhancing the quality and dissemination of AI-generated research.
large language models LLMS autonomous scientific discovery aiXiv multi-agent architecture API MCP interfaces iterative revising and reviewing