Insights from the ICLR Peer Review and Rebuttal Process
Amir Hossein Kargaran, Nafiseh Nikeghbal, Jing Yang, Nedjma Ousidhoum
TL;DR
The paper analyzes ICLR 2024 and 2025 OpenReview data to quantify how author rebuttals and reviewer interactions alter final scores, focusing on before vs after rebuttal changes and the timing of contributions. It combines traditional statistics with LLM-based text categorization to identify factors driving score changes, finding that initial scores and co-reviewer ratings are strong predictors and that rebuttals most affect borderline papers, especially when containing evidence-backed clarifications. Reviewer disagreement narrows after rebuttals, particularly for high-quality submissions, and timing matters, with middle-period rebuttals being more effective. The work provides practical guidance for authors on rebuttal strategies and offers a data-and-toolful framework for improving fairness and efficiency in large-scale peer review, with open data and code for reproducibility.
Abstract
Peer review is a cornerstone of scientific publishing, including at premier machine learning conferences such as ICLR. As submission volumes increase, understanding the nature and dynamics of the review process is crucial for improving its efficiency, effectiveness, and the quality of published papers. We present a large-scale analysis of the ICLR 2024 and 2025 peer review processes, focusing on before- and after-rebuttal scores and reviewer-author interactions. We examine review scores, author-reviewer engagement, temporal patterns in review submissions, and co-reviewer influence effects. Combining quantitative analyses with LLM-based categorization of review texts and rebuttal discussions, we identify common strengths and weaknesses for each rating group, as well as trends in rebuttal strategies that are most strongly associated with score changes. Our findings show that initial scores and the ratings of co-reviewers are the strongest predictors of score changes during the rebuttal, pointing to a degree of reviewer influence. Rebuttals play a valuable role in improving outcomes for borderline papers, where thoughtful author responses can meaningfully shift reviewer perspectives. More broadly, our study offers evidence-based insights to improve the peer review process, guiding authors on effective rebuttal strategies and helping the community design fairer and more efficient review processes. Our code and score changes data are available at https://github.com/papercopilot/iclr-insights.