编辑丨 机器之心 点击下方 卡片 ，关注" 具身智能之心 "公众号 >> 点击进入→ 具身 智能之心 技术交流群 更多干货，欢迎加入国内首个具身智能全栈学习社区： 具身智能之心知识星球（戳我） ，这里包含所有你想要的! 刚过去的这个周末，围绕 ICLR 2026 审稿意见中很多被标记为完全由 AI 生成的说法，引发了社区热烈讨论。本届会议将于 2026 年 4 月 23 日至 27 日在巴西里约 热内卢举行。 随着首轮分数的公布，有第三方机构开始对 ICLR 2026 的审稿意见进行系统性统计，其中发现了大量 AI 审稿的现象。 在对 75800 篇论文的审稿意见统计中，竟然 有 21% 完全由 AI 生成 、4% 重度由 AI 编辑、9% 中度由 AI 编辑、22% 轻度由 AI 编辑， 完全由人类（审稿人）撰 写的仅占 43% 。 图源： X@ Graham Neubig 并且还呈现出一些趋势，包括 AI 审稿意见篇幅更长、AI 审稿更可能给出高分 。 这项统计是由 潘格拉姆实验室（Pangram Labs） 完成的，这是一家专门检测 AI 生成（自动撰写或由大语言模型生成文字内容）的科技公司。此次，该机 ...

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]