aiXiv: A Next-Generation Open Access Ecosystem for Scientific Discovery Generated by AI Scientists
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arXiv
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| Autori principali: | , , , , , , , , , , , , , , , , , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866908716479021056 |
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| author | Zhang, Pengsong Hu, Xiang Huang, Guowei Qi, Yang Zhang, Heng Li, Xiuxu Song, Jiaxing Luo, Jiabin Li, Yijiang Yin, Shuo Dai, Chengxiao Jiang, Eric Hanchen Zhou, Xiaoyan Yin, Zhenfei Yuan, Boqin Dong, Jing Su, Guinan Qiao, Guanren Tang, Haiming Du, Anghong Pan, Lili Lan, Zhenzhong Liu, Xinyu |
| author_facet | Zhang, Pengsong Hu, Xiang Huang, Guowei Qi, Yang Zhang, Heng Li, Xiuxu Song, Jiaxing Luo, Jiabin Li, Yijiang Yin, Shuo Dai, Chengxiao Jiang, Eric Hanchen Zhou, Xiaoyan Yin, Zhenfei Yuan, Boqin Dong, Jing Su, Guinan Qiao, Guanren Tang, Haiming Du, Anghong Pan, Lili Lan, Zhenzhong Liu, Xinyu |
| contents | 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 |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2508_15126 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | aiXiv: A Next-Generation Open Access Ecosystem for Scientific Discovery Generated by AI Scientists Zhang, Pengsong Hu, Xiang Huang, Guowei Qi, Yang Zhang, Heng Li, Xiuxu Song, Jiaxing Luo, Jiabin Li, Yijiang Yin, Shuo Dai, Chengxiao Jiang, Eric Hanchen Zhou, Xiaoyan Yin, Zhenfei Yuan, Boqin Dong, Jing Su, Guinan Qiao, Guanren Tang, Haiming Du, Anghong Pan, Lili Lan, Zhenzhong Liu, Xinyu Artificial Intelligence Computation and Language 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 |
| title | aiXiv: A Next-Generation Open Access Ecosystem for Scientific Discovery Generated by AI Scientists |
| topic | Artificial Intelligence Computation and Language |
| url | https://arxiv.org/abs/2508.15126 |