ICML 2026 Decision [D]

2026-04-29 · Source: Machine Learning · Field: Science & Research — Research Methodology & Innovation · Depth: Advanced, quick

Summary

A Reddit discussion thread on r/MachineLearning captures the intense anticipation and anxiety surrounding the upcoming ICML 2026 paper decisions. Contributors express their impatience by constantly refreshing OpenReview and the Reddit thread itself, with some noting that Reddit often provides earlier updates for high submission numbers. Beyond the wait, the discussion also highlights significant frustrations with the peer review process, including instances of reviewers "ghosting" submissions, providing unhelpful feedback, or lowering scores despite rebuttals addressing all concerns. Some participants are already preparing for NeurIPS resubmissions due to perceived unfairness in the ICML review cycle. As decisions begin to trickle in, users are sharing their acceptance statuses, with one user reporting a regular accept for submission 5XXX and another for submission 10k.

Key takeaway

For AI Scientists and Research Scientists awaiting conference decisions, recognize that the review process can be inconsistent and frustrating. Instead of solely relying on official channels, monitor community discussions on platforms like Reddit for early announcements and shared experiences. Be prepared to adapt your strategy, such as planning for resubmission to alternative conferences like NeurIPS, if initial outcomes are unfavorable or feedback is unconstructive.

Key insights

The ICML 2026 decision period is marked by high anxiety and frustration over the peer review process.

Principles

• Peer review quality varies significantly.
• Community forums accelerate decision dissemination.

In practice

• Monitor community forums for early decision announcements.
• Prepare for resubmission to other conferences like NeurIPS.

Topics

• ICML 2026
• Paper Submission
• Peer Review Process
• Decision Notification
• Academic Anxiety

Best for: AI Scientist, Research Scientist, AI Student

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