FARS: A Fully Automated Research System Deployed at Scale
Paper · 2026 · Qiong Tang, Tianxiang Sun, Xiangkun Hu et al.
Summary
Automated research agents can already propose ideas, run experiments, and draft manuscripts. However, the evidence for this mostly comes from hand-picked examples or a few tasks framed by humans. This paper asks how such a system behaves when it runs continuously across many topics, and how its output should be judged. The authors build FARS, a pipeline of dedicated agents for Ideation, Planning, Experiment, and Writing. The agents coordinate through a shared workspace that serves as project memory and as an auditable archive of proposals, code, logs, results, and drafts. In its first public deployment on AI/ML research, FARS completed 166 papers across 67 fine-grained topics. The authors kept weak and negative outputs rather than presenting only the best ones. Volunteer reviewers wrote 282 structured reviews covering 140 papers. Quality varied widely. Some papers were judged review-worthy or even strong, but narrow experiments, methodological flaws, and integrity problems kept appearing. The work offers a large-scale, inspectable test of fully autonomous research, showing that generation scales while reliable contribution still lags.
Key points
- The deployment produced 166 complete papers on 67 AI/ML topics. Some grew from nine seed topics given at launch, and the rest were emergent topics FARS found on its own. The agents ran on a cluster of 160 NVIDIA GPUs.
- Reviews were collected from March 21 to April 12, 2026. They yielded 282 reviews for 140 papers, and the 26 papers without a review were excluded from the statistics.
- Each review included an overall rating, sub-scores for soundness, presentation, and contribution, reviewer confidence, an integrity check, and disclosure of any LLM use.
- The AI Integrity Audit had reviewers compare each manuscript with its code, logs, and raw outputs. It checked eight failure modes, such as hallucinated citations, fabricated results, spurious novelty, and experimental-design pathologies.
- Three FARS papers (FA0328, FA0064, FA0029) were posted to arXiv after minimal human integrity review, with their content left unchanged.
Institutions
Fields, topics and concepts
📚 Shelves 5The field of science this work belongs to (OpenAlex fields).Computer Science · 19,503 worksArtificial Intelligence · 18,805 worksArts and Humanities · 17,959 worksLanguage and Linguistics · 17,789 worksHistory and Philosophy of Science · 83 works
Cite
Cite as Qiong Tang, Tianxiang Sun, Xiangkun Hu, Xiangyang Liu, Yiran Chen, Yunfan Shao, Bobo Li, Changze Lv, Cheng Xu, Chengsong Huang, Chunyang Li, Dizhan Xue, Hao Bai, Haodong Duan, Hengquan Guo, Hongyang He, Hongyi Chen, Hui Shen, Jiahao Yuan, Jiankai Sun, Jikang Cheng, Jinfeng Xu, Jingqi Tong, Jingye Chen, Jinxiu Liu, Jixuan Leng, Junchi Yu, Kaixun Jiang, Kun Xiang, Kunpeng Yao, Lang Feng, Liangqi Yuan, Longsen Gao, Meng Li, Qi Jia, Qiushi Sun, Shengyuan Ding, Shizhan Gong, Siru Zhong, Terry Jingchen Zhang, Tianle Gu, Tianyi Liang, Weijie Liu, Weikai Yang, Weizhi Fei, Xin Wang, Xinpeng Liu, Xuanwen Ding, Yihong Tang, Yuanli Wang, Yukun Jiang, Yuming Yang, Zhengbao He, Zhikai Chen, Zhikun Xu, Zhuang Li and Zihao Huang. 2026. FARS: A Fully Automated Research System Deployed at Scale. arXiv:2606.31651.
@misc{tang2026fars,
title = {{FARS: A Fully Automated Research System Deployed at Scale}},
author = {Qiong Tang, Tianxiang Sun, Xiangkun Hu, Xiangyang Liu, Yiran Chen, Yunfan Shao, Bobo Li, Changze Lv, Cheng Xu, Chengsong Huang, Chunyang Li, Dizhan Xue, Hao Bai, Haodong Duan, Hengquan Guo, Hongyang He, Hongyi Chen, Hui Shen, Jiahao Yuan, Jiankai Sun, Jikang Cheng, Jinfeng Xu, Jingqi Tong, Jingye Chen, Jinxiu Liu, Jixuan Leng, Junchi Yu, Kaixun Jiang, Kun Xiang, Kunpeng Yao, Lang Feng, Liangqi Yuan, Longsen Gao, Meng Li, Qi Jia, Qiushi Sun, Shengyuan Ding, Shizhan Gong, Siru Zhong, Terry Jingchen Zhang, Tianle Gu, Tianyi Liang, Weijie Liu, Weikai Yang, Weizhi Fei, Xin Wang, Xinpeng Liu, Xuanwen Ding, Yihong Tang, Yuanli Wang, Yukun Jiang, Yuming Yang, Zhengbao He, Zhikai Chen, Zhikun Xu, Zhuang Li and Zihao Huang},
year = {2026},
doi = {10.48550/arxiv.2606.31651},
eprint = {2606.31651},
archivePrefix = {arXiv},
url = {https://doi.org/10.48550/arxiv.2606.31651}
}References
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