NVIDIA pointed to an ICML paper that separates unintended memorization from real generalization. Its headline estimate, about 3.6 bits per parameter, gives privacy and scaling debates a concrete capacity number.
A March 18 Reddit thread on r/MachineLearning debated whether ICML 2026 went too far by desk-rejecting submissions tied to reviewers who violated Policy A. ICML's official materials confirm the two-policy system, the sanction language, and a watermark-based detection process that was manually reviewed rather than based on generic AI-text detectors.
A 184-point r/MachineLearning thread discussed reported ICML enforcement against no-LLM review violations, with commenters focusing on canary-based detection and coauthor risk.
A reviewer in r/MachineLearning says an ICML paper in a no-LLM track reads as if it was fully generated by AI, opening a blunt discussion about enforcement, review burden, and whether writing quality itself has become a policy signal.
A high-engagement r/MachineLearning thread (score 390, 52 comments) raised concerns that hidden prompt-like PDF text could conflict with ICML’s no-LLM review policy and create process confusion.