Policy & Ethicsllmpeer reviewacademic conference
ICML Detects Reviewers Using LLMs, Rejects Papers
8.2
Organizers for the International Conference on Machine Learning (ICML) told Nature they rejected 497 papers — about 2% of submissions — after detecting authors had used large language models to review others' work. Conference staff embedded hidden prompts in submissions that exposed LLM-generated review text, identifying 506 reviewers and 795 suspect reviews. The move aims to enforce peer-review rules and prompt clearer conference policies.
Key Points
- 1Detected 506 reviewers produced 795 suspect reviews, prompting rejection of 497 papers (~2% submissions)
- 2Used hidden prompts in submissions that revealed LLM-generated reviewer text, exposing policy violations
- 3Signals stricter enforcement and forces conferences to clarify AI rules for peer review practices
Scoring Rationale
Strong, novel enforcement method with credible reporting; limited scope to academic peer review and policy debates.
Sources
Public references used for this report.
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