2 min readfrom Machine Learning

Seems ICML is rejecting MANY unanimous positively rated papers [D]

My 4444 (4443 pre-rebuttal) got rejected (as expected).

Just copying a reply I wrote a couple of days ago before decisions were out:

There seems to be a misalignment in the incentives of this year’s ICML reviews. The rebuttal phase is pushing hard to encourage reviewers to reconsider their scores, which has a good motivation. But in practice, it creates a distorted dynamic. ACs are seeking homogeneous ratings among reviewers. As a reviewer, I feel the pressure to increase my score to avoid prolonged back-and-forth discussions. I would assume there may be many reviewers who are not engaged but raise their scores just to end the discussion.

At the same time, reviewers who are initially positive often seem reluctant to update their scores, even after their concerns are addressed. I came across a review that said: “Thank you for the rebuttal. The paper is valuable. The rebuttal addressed all my concerns.” (rephrased to avoid directly locating the paper) Yet the score remained at 4.

It now makes me nervous (NOW I KNOW I WAS RIGHT!) since scores are inflated while the conference has a limited capacity. In a few days, we may see MANY uniformly positively rated papers rejected, just like last NeurIPS.

I would prefer to roll back to how peer review originally was: reviewers provide honest and independent evaluations; AC assess their quality and consistency; and borderline cases are resolved through AC discussion. The current mechanism feels unnecessarily complex and makes the already bad situation worse.

submitted by /u/AffectionateLife5693
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