reviewpaper.ai

Policies

LLM policies for authors and reviewers, by venue

Most venues let authors use LLMs as tools, with disclosure for anything substantial. Nearly all of them forbid reviewers from pasting a submission into a public chatbot. Here is each venue's rule and the official link.

Last checked against official sources on .

The short version

  • Authors may use LLMs as tools at almost every venue, but are fully responsible for the content. More and more venues require disclosure (ICLR 2027, KDD, AISTATS 2027, ARR), and fabricated citations get papers rejected.
  • Reviewers are held to a much stricter standard. Most venues forbid putting a submission into a public LLM, and several (CVPR, ECCV, ICCV, AISTATS, ICML Policy A) forbid LLM use in reviewing outright. Breaking the rule can get the reviewer's own papers desk-rejected.
  • Policies change every cycle. Each row links to the official page; that page always wins.

Major venues: authors and reviewers

Checked 2026-10-12. Click the icon for the official policy.

VenueAuthorsReviewers
NeurIPS 2026Authors are fully responsible for all content, including verifying every citation. LLMs can't be authors.NeurIPS 2026 runs a sanctioned-LLM experiment: on some assigned papers reviewers may use only the sanctioned LLM; on all others any LLM use is forbidden, and sharing a submission with an unsanctioned LLM breaks confidentiality.
ICLR 2027A mandatory AI-use section (not counted in the page limit). Disclosure is required for uses such as synthetic data, mathematical claims and interpreting results. An LLM-produced falsehood or plagiarism can lead to desk rejection.Limited, responsible use to polish writing, with mandatory disclosure. Irresponsible reviews can lead to desk rejection of the reviewer's own papers.
ICML 2026Authors choose whether their paper may be reviewed under Policy B (limited LLM help) or must stay under Policy A (no LLMs).ICML 2026 assigns each reviewer Policy A (no LLMs) or Policy B (LLMs may help understand the paper and polish wording, but may not identify strengths/weaknesses or write the review). Violations can get the reviewer's own papers desk-rejected.
CVPR 2026 (2027 policy not yet published)Any tools are allowed, but authors are responsible for what they submit. Papers citing non-existent material are rejected.CVPR 2026 does not allow LLMs to be used to write reviews or meta-reviews, and no substantial paper or review content may be shared with an LLM. Violations can lead to desk rejection of the reviewer's own papers.
ACL Rolling ReviewUse of AI for writing or coding, and its scope, must be disclosed in the Responsible NLP checklist. AI can't be an author.ARR forbids using generative AI to create the first draft of a review or meta-review. Light language editing is allowed, but manuscripts and reviews must not be uploaded to non-privacy-preserving tools.
AAAI-27Generative AI may be used judiciously; authors are fully responsible, and non-existent references are sanctionable.No explicit AAAI reviewer-LLM rule was found, but reviewer confidentiality rules in practice forbid uploading submissions to external LLMs. AAAI supplies its own official AI review, and reviewers must not duplicate content from other reviews.
IJCAI-ECAI 2026Authors take full responsibility; LLM-generated text that is part of the methodology must be documented. AI can't be an author.IJCAI-ECAI 2026 lets reviewers use generative AI only to improve the readability of their own review text, after removing anything identifying or confidential; submissions or their technical content must never be uploaded to tools without confidentiality guarantees.
KDD 2026Any use of generative AI tools must be disclosed in the submission form.KDD 2026 requires any use of generative AI during reviewing to be disclosed in the review form, and forbids uploading any passage of a paper under review to a generative AI tool.
AISTATS 2027An AI Use Statement is required (missing it means desk rejection). Hidden prompts aimed at AI reviewers count as misconduct.Reviewers may not generate reviews with an LLM or delegate judgment to one; sanctions include desk rejection.
TMLRLLMs are allowed as general-purpose assistive tools. Authors are fully responsible, and LLMs can't be authors.TMLR lets reviewers use LLMs and other tools to assist, e.g. to look up notation or polish grammar, but reviewers must form their own understanding of the paper and take responsibility for their reviews. Largely LLM-generated reviews are closely examined.

Other venues: reviewer rules

Author-side rules for these venues are usually in the call for papers. Reviewer rules from each venue's guidelines:

UAI 2026UAI 2026 does not allow LLMs to write reviews or meta-reviews; they may be used only to check grammar, and the reviewer is responsible for all submitted text.
COLT 2026COLT 2026 reviewers must not share submissions with any LLM; models may be used like books or Wikipedia to understand technical points, without leaking confidential information.
EMNLP 2026ARR forbids using generative AI to create the first draft of a review or meta-review. Light language editing is allowed, but manuscripts and reviews must not be uploaded to non-privacy-preserving tools.
NAACL 2027ARR forbids using generative AI to create the first draft of a review or meta-review. Light language editing is allowed, but manuscripts and reviews must not be uploaded to non-privacy-preserving tools.
COLING 2027ARR forbids using generative AI to create the first draft of a review or meta-review. Light language editing is allowed, but manuscripts and reviews must not be uploaded to non-privacy-preserving tools.
EACL 2027ARR forbids using generative AI to create the first draft of a review or meta-review. Light language editing is allowed, but manuscripts and reviews must not be uploaded to non-privacy-preserving tools.
AACL 2026ARR forbids using generative AI to create the first draft of a review or meta-review. Light language editing is allowed, but manuscripts and reviews must not be uploaded to non-privacy-preserving tools.
COLM 2026COLM 2026 requires reviewers to disclose any LLM use, cosmetic or substantive; reviewers remain fully responsible for their reviews.
ICCV 2025ICCV 2025 does not allow LLMs or online chatbots in any part of the reviewing process; LLM-generated reviews are "highly irresponsible" and can lead to desk rejection of all the reviewer's papers.
ECCV 2026ECCV 2026 does not allow LLMs to write reviews or meta-reviews, locally or via API, and no substantial paper or review content may be shared with an LLM (including for translation). Grammar checkers and background research are allowed. Violations can desk-reject the reviewer's own papers.
WACV 2027WACV lists reviews generated by LLMs as highly irresponsible, which can lead to desk rejection of the reviewer's own papers.
WWW 2027The WWW 2026 industry track required reviewers to commit not to rely on LLMs and forbade uploading paper content to any LLM; the research-track call states no reviewer rule, and ACM's peer-review policy forbids uploading confidential submissions to generative AI.
SIGIR 2026SIGIR follows the ACM Peer Review Policy and requires that referees not use AI systems to create their reviews; LLM-generated reviews are treated as highly irresponsible.
ICASSP 2026IEEE policy forbids processing any content of a manuscript under review through a public AI platform (a confidentiality breach). ICASSP 2026 organizers report using the rebuttal phase to identify AI-generated reviews.
Interspeech 2026No Interspeech reviewer LLM rule was found. The ISCA Code of Ethics allows authors to use generative AI only for editing and polishing, with disclosure; treat submissions as confidential and do not upload them to LLMs.
ACM MM 2026ACM MM 2026 allows AI tools only to polish review language; clear evidence of AI-generated reviews can get the reviewer's own papers desk-rejected. ACM policy forbids uploading confidential submissions to generative AI.
CoRL 2026CoRL 2026 reportedly allows AI help for literature search, clarifying concepts and polishing wording, but forbids uploading manuscripts to tools without enterprise confidentiality and requires reviewers to disclose tools used; judgments must be the reviewer's own. (Official page currently empty; unverified.)
MLSys 2026No MLSys reviewer LLM policy is published. Authors may not submit papers whose content is generated by LLMs alone (unless illustrative or part of the experiments). Treat submissions as confidential and do not upload them to LLMs.

What this means for authors

  • Check every citation in your bibliography exists and says what you claim. Several venues now reject papers with hallucinated references.
  • If an LLM did more than polish wording (generated data, proofs, analysis), disclose it the way your venue asks.
  • Don't hide prompts aimed at AI reviewers in your PDF. AISTATS 2027 explicitly treats it as misconduct.
  • Pre-submission feedback on your own unpublished paper is your call. Pick a tool that doesn't train on your paper and lets you delete it.
If you're a reviewer: follow your venue's rule above. Uploading a submission you were assigned to any external tool, including this one, breaks confidentiality at most venues.

For your own paper, before you submit

reviewpaper.ai is an author tool: you upload your own draft and get simulated reviews in your target venue's form. Your paper is stored privately, never used to train models and never shared with any venue. First three runs free.

Review my paper, 3 free

Sources

reviewpaper.ai is not affiliated with any of these venues or its organizers. Rules change between cycles; the official pages above always win.