# Exploring the use of AI authors and reviewers at Agents4Science

arXiv: https://arxiv.org/abs/2511.15534 · HTML: https://mlsanity.com/paper/2511.15534/

## Key facts

- Cited by 13 papers in the map (data through 14 Oct 2026).
- Builds on 0 of its 3 references that are in the map.
- First posted on arXiv 19 Nov 2025.

## Built on by (most cited first, 13 of 13)

- [Stop Automating Peer Review Without Rigorous Evaluation](https://mlsanity.com/paper/2605.03202/) (2026)
- [Agentic AI Scientists Are Not Built For Autonomous Scientific Discovery](https://mlsanity.com/paper/2605.08956/) (2026)
- [LLM hallucinations in the wild: Large-scale evidence from non-existent citations](https://mlsanity.com/paper/2605.07723/) (2026)
- [To Err Is Human: Systematic Quantification of Errors in Published AI Papers via LLM Analysis](https://mlsanity.com/paper/2512.05925/) (2025)
- [LLM-as-a-Reviewer: Benchmarking Their Ability, Divergence, and Prompt Injection Resistance as Paper Reviewers](https://mlsanity.com/paper/2605.25415/) (2026)
- [Gaming AI-Assisted Peer Reviews Poses New Risks to the Scientific Community](https://mlsanity.com/paper/2606.10159/) (2026)
- [Agentic Publication Protocol: An Attempt to Modernize Scientific Publication](https://mlsanity.com/paper/2606.27386/) (2026)
- [Distributed Denial of Science: How Indirect Data Poisoning of AI Systems Can Industrialize Scientific Fraud](https://mlsanity.com/paper/2607.10712/) (2026)
- [The Agentification of Scientific Research: A Physicist's Perspective](https://mlsanity.com/paper/2604.14718/) (2026)
- [PaperDoctor: Evidence-Grounded and Actionable Feedback for Scientific Papers in Progress](https://mlsanity.com/paper/2609.16995/) (2026)
- [RECLAIM: Can Agents Reproduce the Claims of Machine Learning Papers?](https://mlsanity.com/paper/2609.28850/) (2026)
- [Science or Slop?: Benchmarking and Mitigating Scientific Slop in AI-Generated Papers](https://mlsanity.com/paper/2610.00531/) (2026)
- [A Society of Researchers: Designing Institutions for Populations of Autonomous Research Agents](https://mlsanity.com/paper/2610.10468/) (2026)

## Abstract (arXiv)

There is growing interest in using AI agents for scientific research, yet fundamental questions remain about their capabilities as scientists and reviewers. To explore these questions, we organized Agents4Science, the first conference in which AI agents serve as both primary authors and reviewers, with humans as co-authors and co-reviewers. Here, we discuss the key learnings from the conference and their implications for human-AI collaboration in science.