AI-Generated Papers in the NeurIPS 2026 Position Paper Track – NeurIPS Blog

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June 2 2026

AI-Generated Papers in the NeurIPS 2026 Position Paper Track

Communication Chairs 2026

2026 Conference

This year, the NeurIPS 2026 Position Paper Track made the decision to require that all papers be substantially human-written, with AI used for only copy-editing or similar peripheral changes to the main text. While we recognize that thoughtful use of AI can result in productivity gains in research, the use of AI to write papers creates an acute risk for the peer review system. As Position Paper Track chairs, we took a conservative approach in policy this year as we believe in argumentative work like position papers, excessive use of AI in writing submitted papers has little benefit for the research community as a whole. AI-generated text is often slick, but can depart significantly from the authors’ original intention. In this case, submitting AI-generated text for peer review externalises the cost of verifying that work, imposing it on reviewers. Where AI-generated text is not itself incoherent or otherwise misguided, this raises questions about the appropriate attribution of credit.

To assess if authors were largely abiding by this policy, we partnered with Pangram, a leading AI detection modeling company. We worked closely with Pangram to ensure, as per their enterprise-level data agreement, that zero data would be retained through the usage of their model. After several independent analyses to verify the correctness of this model and rule out scenarios in which significant false positives would be created, we are now making the difficult decision to uphold our policy, under which:

178 submissions (18.4% of all submissions) will be desk rejected

123 submissions (12.7%) will be requested to provide evidence of substantial human engagement or risk a desk reject.

In this blog post, we will lay out our analyses informing this decision, and provide our perspective as organizers.

Why this policy?

We reproduce here the 2026 PPT AI policy:

Use of AI : While we recognise the productivity gains that can be realised through judicious use of AI in research, due to the risk to the integrity of individual projects and of the review system as a whole, the position paper track is establishing the following explicit guardrails on AI use in preparing and reviewing submissions.

While AI tools may be used in the research that leads to the final paper, the final paper must itself be substantially written by human authors, meaning that AI is used only for copy-editing or similar peripheral changes to the main text.

At submission time, authors will be required to state how AI tools were used in the preparation of the paper, if at all, and to attest that they have not used AI in ways contrary to the above rule.

Because papers submitted to the position paper track are confidential, reviewers will be required to commit to not using AI tools to write their reviews.

Reviewers and authors found to have contravened their commitments not to use AI may be subject to desk-rejection of any work submitted to the position paper track.

Note that the Position Paper Track’s LLM policy differs from the Main Program’s LLM policy. Authors are responsible for understanding policy pertaining to the specific track they are submitting to, and abiding by it.

The use of AI to write papers creates an acute risk to the peer review system. Proactive steps are necessary to build the norms and institutions that will preserve its integrity. This policy is an attempt to begin that process.

It is of course possible that a paper’s authors could use AI responsibly, (1) personally verifying every line of AI output, and (2) ensuring that the AI does nothing more than rephrase ideas for which humans are solely responsible. However, by submitting work that is immediately recognisable and verifiable as being substantially AI-generated, authors make it impossible for readers to know that (1) and (2) obtain, leaving reviewers with little choice but to rely upon author declarations. Unfortunately, given the volume of submissions that appear non-compliant, relying on author declarations is insufficient.

We do not expect that our policy and our approach will be the last word on handling AI-generated research. Every research field will have to confront the same problem, and a range of solutions may be reasonable. We have sought to use the evidence available to us to identify submissions that appear to be non-compliant with our policy. But we are also introducing a new approach to auditing AI use by establishing appropriate provenance. Authors whose submissions show significant AI involvement must provide an audit trail that clearly demonstrates that they complied with the policy. We expect that in future years this kind of audit trail will become a default.

AI detection with Pangram suggests substantial AI use among this year’s...