Research
So Confused about Polarizing ICML Reviews [D]
This r/MachineLearning discussion thread addresses the common and frustrating experience of receiving highly polarizing reviewer scores for ICML paper submissions — for example, one reviewer rating a
This r/MachineLearning discussion thread addresses the common and frustrating experience of receiving highly polarizing reviewer scores for ICML paper submissions — for example, one reviewer rating a paper highly while another gives it a very low score. The post likely explores community perspectives on why such scoring inconsistencies occur, touching on broader concerns about review quality at ICML, including issues like reviewers misunderstanding papers, insufficient engagement with submissions, and potential LLM-generated reviews. It reflects a wider, ongoing debate in the ML research community about the fairness, consistency, and transparency of the peer review process at top-tier conferences.
Related
- Post Rebuttal ICML Average Scores? [D]
- [[d-dealing-with-an-unprofessional-reviewer-using-fake-referen|[D] Dealing with an unprofessional reviewer using fake references and personal attacks in ICML26]]
- [[d-how-are-reviewers-able-to-get-away-without-providing-ackno|[D] How are reviewers able to get away without providing acknowledgement in ICML 2026?]]
- ICML 2026 am I cooked? [D]
- Is the ICML 2026 final justification period still open? [R]
Source: r/MachineLearning | 2026-04-12