Inquiry into ICML 2026 Review Dynamics
The post inquires about the current review dynamics for ICML 2026, particularly the average scores after the rebuttal phase. It also asks if tools like PaperCopilot reflect the true score distributions.
Why it matters
Understanding the review dynamics for major ML conferences like ICML is important for researchers to gauge the competitiveness and expectations of the review process.
Key Points
- 1Curious about the average scores for ICML 2026 reviews after the rebuttal phase
- 2Asking if tools like PaperCopilot accurately represent the true score distributions
- 3Seeking insights from reviewers or those with knowledge of the review process
Details
The post is inquiring about the current state of the review process for ICML 2026, a prominent machine learning conference. The author is particularly interested in understanding the average scores assigned to papers after the rebuttal phase, where authors have the opportunity to respond to reviewer comments. They also wonder if tools like PaperCopilot, which provide statistics on ICML submissions, accurately reflect the true score distributions. The author is seeking insights from those who have experience as reviewers or have access to information about the review process.
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