ML Conferences Tighten Rules, Adding LLM Use and Co-author Conduct to Desk Rejection Criteria

Major machine learning conferences like NeurIPS, ICML, and ICLR are increasingly implementing stricter policies that can lead to desk rejection of papers. Historically, rejections were primarily due to issues with the paper itself, such as exceeding page limits or violating anonymity. However, recent updates to conference guidelines now include reasons like a co-author's poor reviewing history, improper use of LLMs, conflicts of interest, or even collusion among authors. AI

IMPACT Academic publishing standards are evolving to address AI's role in research, potentially impacting how AI research is submitted and reviewed.

RANK_REASON The item discusses policy changes and guidelines for academic conferences, which falls under research-related policy. [lever_c_demoted from research: ic=1 ai=1.0]

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• NeurIPS
• ICLR
• LLM

• policy
• paper

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