2 min readfrom Machine Learning

NeurIPS 2026 Reviews Are Out Today (22 July, AoE) — Discussion Thread [D]

Reviews drop today. This thread is for reactions, celebrations, commiserations, and anything useful in between.

First: if you got good reviews, say so. There's a norm in these threads where only the bad news gets aired, and it skews everyone's sense of what's normal. Post your wins.

Second, the thing worth repeating every cycle: the review process is noisy, and that noise is measured, not folklore. The NeurIPS consistency experiments (2014, repeated 2021) found that a large fraction of accepted papers would have been rejected by an independent second committee. Reviewer assignment, load, and luck of the draw account for a lot. A score is a weak signal about your work and a strong signal about the process that produced it.

That cuts both ways. It's not a license to dismiss every criticism as noise — it's a reason to weight reviews by the quality of the argument rather than the number attached to them. The reviewer who found a real hole in your evaluation did you a favor, even if the tone was rough. The one who clearly skimmed did not, regardless of the score.

So: prioritize the reviews that make the paper better. Fix what's fixable, contest what's genuinely wrong, and concede the rest gracefully in the rebuttal.

Things worth discussing:

  • Reviews that caught something you'd missed
  • Rebuttal strategy — what's worth contesting vs. conceding, and when new experiments actually shift a score
  • Patterns you're seeing this cycle (missing baselines, compute comparisons, ablation depth, reproducibility asks)
  • Framing a response when a reviewer has clearly misread the submission
  • Backup plans: ICLR, AISTATS, workshops

Please paraphrase rather than paste review text, and no speculation about reviewer or AC identities.

To anyone who got bad news: this doesn't define your research impact. Plenty of heavily-cited work took two or three cycles to land somewhere. Rejection is a scheduling problem.

How did everyone do?

submitted by /u/Afraid_Difference697
[link] [comments]

Want to read more?

Check out the full article on the original site

View original article