Preprint site arXiv is banning computer-science reviews: here’s why

Researchers who use hallucinated references to face arXiv ban

The preprint server is the latest to impose stiff penalties on authors who contribute to AI ‘slop’ — but not everyone is convinced it’s the right approach.

arXiv Changes Rules After Getting Spammed With AI-Generated 'Research' Papers

Cornell University’s arXiv will no longer accept Computer Science reviews and position papers.

ArXiv to Ban Researchers for a Year if They Submit AI Slop

The change comes as arXiv and others struggle to manage an influx of AI-generated materials masquerading as rigorous science.

arXiv Is Rate Limiting Submissions Because It Can’t Keep up With AI Slop

The academic publisher said submissions have doubled in the past two years and moderators are having a hard time keeping up.

Fair Moderation, Equitable Access, and AI: arXiv’s Updated Rate Limit Policy

arXiv, and the scientific community at large, are facing a watershed moment. Scholarly publishing is currently changing at a rapid pace, and we are seeing a…

Content Moderation - arXiv info

arXiv is a forum for professional members of the scientific community, providing rapid distribution of new research. As part of the service all submissions are subject to moderation. Material submitted to arXiv is expected to be self-contained and of interest, relevance, and value to the disciplines we serve.

Major AI conference flooded with peer reviews written fully by AI

Nature - Controversy has erupted after 21% of manuscript reviews for an international AI conference were found to be generated by artificial intelligence.

Attention Authors: Updated Practice for Review Articles and Position Papers in arXiv CS Category

arXiv’s computer science (CS) category has updated its moderation practice with respect to review (or survey) articles and position papers. Before being…

The future of peer review requires AI support, not AI bans

Letter to the Editor

Banning Open Source AI Would Be A Mistake

This post was originally an op-ed co-authored with Kevin Xu of Interconnected for a general, non-technical audience.

How AI slop is causing a crisis in computer science

Preprint repositories and conference organizers are having to counter a tide of ‘AI slop’ submissions.

Wikipedia Bans AI-Generated Content

“In recent months, more and more administrative reports centered on LLM-related issues, and editors were being overwhelmed.”

AI-Assisted Peer Review at Scale: The AAAI-26 AI Review Pilot

Scientific peer review faces mounting strain as submission volumes surge, making it increasingly difficult to sustain review quality, consistency, and timeliness. Recent advances in AI have led the community to consider its use in peer review, yet a key unresolved question is whether AI can generate technically sound reviews at real-world conference scale. Here we report the first large-scale field deployment of AI-assisted peer review: every main-track submission at AAAI-26 received one clearly identified AI review from a state-of-the-art system. The system combined frontier models, tool use, and safeguards in a multi-stage process to generate reviews for all 22,977 full-review papers in less than a day. A large-scale survey of AAAI-26 authors and program committee members showed that participants not only found AI reviews useful, but actually preferred them to human reviews on key dimensions such as technical accuracy and research suggestions. We also introduce a novel benchmark and find that our system substantially outperforms a simple LLM-generated review baseline at detecting a variety of scientific weaknesses. Together, these results show that state-of-the-art AI methods can already make meaningful contributions to scientific peer review at conference scale, opening a path toward the next generation of synergistic human-AI teaming for evaluating research.