[D] Saw this papaer from ICLR with scores 2,2,2,4 and got accepted, HOW

2026-02-06 · Source: Machine Learning · Field: Technology & Digital — Artificial Intelligence & Machine Learning · Depth: Intermediate, short

Summary

A discussion thread from ICLR highlights the controversial acceptance of a paper with exceptionally low reviewer scores (2, 2, 2, 4) and a reported formatting violation, sparking debate over the role and power of Area Chairs (ACs) in the peer review process. Participants express frustration, noting instances where papers with high average scores (e.g., >6 or 8, 6, 4, 4) were rejected, while this low-scoring paper was accepted. Speculation arises regarding potential reasons for AC overrides, including author influence, the perceived "nitpicky" nature of reviews, or ACs independently recognizing a paper's merit despite reviewer feedback. The absence of reviewer responses to rebuttals, due to identity leaks, further complicated this year's ICLR review cycle.

Key takeaway

For research scientists navigating conference submissions, understand that Area Chair discretion significantly impacts acceptance, even overriding low reviewer scores or high scores. You should focus on clear presentation and robust rebuttals, as ACs may prioritize a paper's core contribution over reviewer "nitpicks." Be aware that formatting errors can lead to desk rejection, regardless of scientific merit.

Key insights

Area Chair overrides in peer review can lead to controversial paper acceptance/rejection decisions, especially with low reviewer scores.

Principles

• AC decisions are often perceived as arbitrary.
• Reviewer scores may not fully reflect paper merit.
• Formatting violations can lead to desk rejection.

In practice

• Scrutinize AC decisions for consistency.
• Ensure strict adherence to formatting guidelines.
• Prepare thorough rebuttals addressing reviewer concerns.

Topics

• ICLR Review Process
• Peer Review System
• Area Chair Decisions
• Reviewer Scores
• Paper Formatting

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Editorial summary, takeaway, and curation by AIssential. Original article published by Machine Learning.