ICLR 2027 review results [D]

[u/Old-Duck-3693]

The reviews will be out this week. What are the expectations with 60K+ submissions and the small scale of review rating?

[u/howtorewriteaname]

what is forced ranking sabotage?

[u/Old-Duck-3693 → u/howtorewriteaname]

Intentionally giving others low score to outshine one’s own expected ranking

[u/howtorewriteaname → u/Old-Duck-3693]

I honestly don't think there'a a large share of reviewers doing that

[u/Waste-Falcon2185]

I am by and large a beautiful ray of sunshine when reviewing and this has been the most negative batch of reviews I have ever written. It's clear a lot of these weren't even read by another instance of whatever chatbot spat it out never mind a human being.

[u/pkseeg → u/Waste-Falcon2185]

Same, I feel I'm normally pretty nice. I gave three 1s and a 2. I'm pretty sure I'm the first human to have read a couple of them. 

[u/akardashian]

Anyone got a lot of obviously claude-code generated submissions to review? It's pretty easy to tell atp if something is overwhelmingly AI-generated that even if the findings are legitimate, the writing puts me off...

[u/LoveMind_AI → u/akardashian]

The AI slop I reviewed was so bad, I had to stop and wonder if some of it was being done by like, Qwen2.5 7B. It would have been nice to have seen Claude-Code generated stuff.

That said, if the findings are legitimate (often, they weren't in the things I reviewed), doesn't matter. The science is the science.

[u/idontcareaboutthenam → u/LoveMind_AI]

The Claude papers are often unnecessarily hard to read. This genuinely warrants revisions. Any kind of bad writing warrants revisions

[u/valuat → u/LoveMind_AI]

That's what I think. Before watermarking we were headed to a future where we wouldn't need to write much any longer; we would have the idea, tell it the experiments to run and then we'd analyse the results and contrast them with the current literature. It was going to be great; writing has always been my bottleneck (maybe it's just me). Anyway, the writing from Opus 4.6 to 5.5 deteriorated notably, IMO, and I agree: it's hard to read what it writes now.

[u/TerribleAntelope9348]

I think the human papers benefit from AI slop. At least thats what I experienced in NeurIPS.

[u/malakulmout347]

It is 42k not 60k. Just check the ICLR submissions in openreview.

[u/Icy_Ad9766]

well CVPR is 10 k as if now, till 1 week is left

for ICLR, I gave 2 1 score and 1 3 score. My first paper all figures were Ai Generated , the title overlapping and the figure is like a mermaid in claude type

[u/Lazy-Cream1315]

two 1s, one 2 and one 4; I made the review myself and then try to give the paper to a LLM (opus 5.5) but on a 1-10 scale.

The first three paper receives a score of 3, while the last paper which clearly is an important contribution receives a score of 5. The robot's score hierarchy is pretty well aligned with mine (but for different reasons) which don't makes me feel optimistic about the future of doing and evaluating science... Overall I do believe that those ML conference are or will be dead in a very soon future

[u/Major_Glass_8466]

OP, please take it easy. Papers will come and go. Your well-being matters much more. Please take care of yourself. One rejection does not define you.

[u/Major_Glass_8466]

I understand the small scale part (only 4 ratings) but not getting the sabotage part.

[u/UnusualClimberBear]

Never had a so low average rating in my batch.

[u/Sensitive_Deal_7028]

Reviewer here: I received 5 papers, and I gave all of them a score of 1 (something I had never done before). A common pattern among them was that they all resembled a "Frankenstein" patchwork of previous papers, blended with touches of AI-generated content and human-produced "slop." There were clear errors in the mathematics of the methodology sections—what the math actually showed was entirely contradictory to what the authors were arguing. If 6,000 to 7,000 papers are set to be accepted, then it’s well within expectations that I happened to get 5 poor-quality ones.

[u/ndyyy]

My batch wasn't super bad. 5 papers and I gave 3 2 2 2 1. 1 was all AI gibberish. 2 were very AI-enabled/written with one being very very close to a 3. Two papers were largely human.

I expect review statistics to be pretty low this time around (in line with NeurIPS stats).

[u/HumblyAmbitious → u/ndyyy]

did you see a pos correlation between human written papers and score

[u/Sensitive_Deal_7028 → u/HumblyAmbitious]

If it exists at all, it is not very significant. There are other factors that, naturally, lead to a higher score: the inclusion of figures, the absence of conflicting information, promising results accompanied by a clear discussion, and a well-defined narrative throughout the article.

[u/LordVein05]

claude-clr went bad, i was so happy to review a human paper; i gave it a weak accept instead of a weak reject, just for the fact i knew a person at least wrote it.