Core Insights - A recent analysis revealed that over 21% of the review comments at the ICLR 2026 conference were generated by AI models, highlighting the increasing reliance on AI in academic peer review processes [1][5][19] - The ICLR conference, one of the top three in machine learning, is experiencing a surge in submissions, leading to increased pressure on reviewers [4][11] - The findings come shortly after ICLR implemented strict regulations regarding the use of large language models (LLMs) in the review process, creating a stark contrast between policy and practice [6][8][20] Summary by Category AI in Peer Review - 21% of review comments were identified as fully AI-generated, with an additional 35% being partially AI-edited, leaving only 43% as purely human-written [1][2] - AI-generated reviews were longer and scored higher on average compared to human-written reviews, indicating a potential bias in the evaluation process [2][3] ICLR Conference Context - ICLR 2026 is set to take place in April 2024 in Rio de Janeiro, Brazil, with nearly 20,000 submissions expected, significantly higher than previous years [4] - The conference has been criticized for the quality of reviews, with reports of aggressive language and low scores, leading to dissatisfaction among authors [8][10] Regulatory Environment - ICLR recently established stringent policies requiring authors to disclose the use of AI in their submissions, with penalties for non-compliance [6][8] - Other conferences, such as CVPR 2025 and NeurIPS 2025, are also addressing the use of AI in reviews, with varying degrees of strictness [11][12] Broader Implications - The increasing use of AI in academic reviews raises questions about the integrity and reliability of the peer review process [19][20] - The trend suggests a shift in the roles of human reviewers and AI, prompting a reevaluation of how academic evaluations are conducted [19][20]
AI写论文，AI评阅，AI顶会ICLR完成「AI闭环」，1/5审稿意见纯AI给出
3 6 Ke·2025-11-17 06:10