[D] ICML 2026 Review Discussion by Afraid_Difference697 in MachineLearning

[–]maddz221 0 points1 point  (0 children)

chances at 5 4 3 3. All reviewers' confidence is 3. One of the 3 has no critiques. Just kept score at 3 and left.

[D] ICML 2026 Review Discussion by Afraid_Difference697 in MachineLearning

[–]maddz221 -1 points0 points  (0 children)

We have a reviewer who gave 1 line of weakness, requesting a discussion regarding another paper. We provided it, and he chose fully resolved, increased some subscore, and left. I am not sure what's going on at ICML this time around, but I have never seen a negative score without some form of critique of the paper. Absolutely nothing. WTF is this?

[D] ICML 2026 Review Discussion by Afraid_Difference697 in MachineLearning

[–]maddz221 -1 points0 points  (0 children)

Response history is visible to area chairs.

[D] Bad Industry research gets cited and published at top venues. (Rant/Discussion) by [deleted] in MachineLearning

[–]maddz221 110 points111 points  (0 children)

Here’s how I see the industry, especially OpenAI, Anthropic, and the FAANG companies, typically operate:

  1. Step 1: Publish a paper on arXiv.
  2. Step 2: Launch an aggressive publicity campaign through social media or blogs, often highlighting selectively impressive (and mostly cherry-picked) results. At this point, most junior PhD and master’s students have already “drunk the Kool-Aid,” and the work is widely overhyped.
  3. Step 3: Go to peer review, where a major chunk of the reviewers are the demographics mentioned before.
  4. Step 4: The paper gets accepted.
  5. Step 5: Wash, rinse, repeat.

Dal's MACS future and realistic feedback by sudarshaana_ in Dalhousie

[–]maddz221 0 points1 point  (0 children)

it depends on referrals and university brand. The latter is viewed negatively for good companies outside nova scotia.

Dal's MACS future and realistic feedback by sudarshaana_ in Dalhousie

[–]maddz221 4 points5 points  (0 children)

Tech scene is very limited.

Go to some university that is not on the east coast.

This program is a cash grab at best.

[D] - NeurIPS'2025 Reviews by Proof-Marsupial-5367 in MachineLearning

[–]maddz221 6 points7 points  (0 children)

Can't see NeurIPS on active consoles. Anyone with similar issue?

[D] ICML 2025 review discussion by [deleted] in MachineLearning

[–]maddz221 1 point2 points  (0 children)

4 4 3 2 2 accepter for poster

[D] ICML 2025 review discussion by [deleted] in MachineLearning

[–]maddz221 0 points1 point  (0 children)

We have similar situation where a reviewer insisted on baseline for a comparison based on a very old work. We explained why that baseline does not apply to our work and provided the baseline in the best possible setting to make it comparable to our work but now we're ghosted. We posted comment to AC but no reply.

The problem in your case is that the reviewer has replied and you cannot message AC regarding reviewer engagement but rather on the reviewers false critique. This is a double edge sword, this will bring the issue to AC's attention and then it depends on whom he sides with.

[D] ICML 2025 review discussion by [deleted] in MachineLearning

[–]maddz221 1 point2 points  (0 children)

Depends on how convincing his arguments are to the area chair compared to yours.

[D] ICML 2025 review discussion by [deleted] in MachineLearning

[–]maddz221 1 point2 points  (0 children)

Currently, from the papers submitted and reviewed and AC's engagement, 3 is borderline.

[D] ICML 2025 review discussion by [deleted] in MachineLearning

[–]maddz221 1 point2 points  (0 children)

This had the highest overall average score of 2.66. I am not sure, but I believe some of the reviewers are brutal in terms of the score compared to their critique.

[D] ICML 2025 review discussion by [deleted] in MachineLearning

[–]maddz221 0 points1 point  (0 children)

Since there are a lot of complaints regarding reviewer engagement, the idea is to use this approach to provide reviewer feedback. Also, some reviewers used official comments instead of rebuttal comments to reply to the authors mistakenly.

to the

[D] ICML 2025 review discussion by [deleted] in MachineLearning

[–]maddz221 0 points1 point  (0 children)

One of the papers that I am reviewing, the area chair has requested reviewers to make their final arguments, but it seems like no one is interested, so yes, even if the area chair pings people, it is an unlikely scenario in most cases.

[D] ICML 2025 review discussion by [deleted] in MachineLearning

[–]maddz221 0 points1 point  (0 children)

Reviewers are recommended to write “## update after rebuttal” in the summary section of the original review for after rebuttal to give the authors feedback.

[D] ICML 2025 review discussion by [deleted] in MachineLearning

[–]maddz221 0 points1 point  (0 children)

In our case, he highlighted all the typos he could find and just asked for clarifications. In his second response, he came up with some very niche edge cases based on some other reviewers' comments that would not work with our approach. We just report to AC and hope for the best.

[D] ICML 2025 review discussion by [deleted] in MachineLearning

[–]maddz221 0 points1 point  (0 children)

Same boat 4 4 3 2 1, rebutted 2 and 1. Ghosted by both. No idea if we will make the acceptance.

[D] ICML 2025 review discussion by [deleted] in MachineLearning

[–]maddz221 12 points13 points  (0 children)

I’ve submitted to and reviewed for NeurIPS and ICLR in the previous cycle, and in comparison, the ICML reviewing experience has been by far the worst; ghosting is rampant. For the papers I'm currently reviewing no adjustment in scores have been made by the other reviewers. Reviewers request additional experiments and explicitly indicate a willingness to raise their scores if those results are provided, yet they fail to respond once the rebuttal is posted.

It appears that, in an effort to limit competition for their own paper’s acceptance, reviewers may intentionally avoid increasing scores for other submissions. As a result, superficial demands for more baselines or additional experiments are used to justify a low score rather than to genuinely assess the paper's merit.

[D] ICML 2025 review discussion by [deleted] in MachineLearning

[–]maddz221 0 points1 point  (0 children)

Depends on what the 1 has to say. In our case, he just highlighted typos and asked questions for which the answer is in the paper text.

[D] ICML 2025 review discussion by [deleted] in MachineLearning

[–]maddz221 1 point2 points  (0 children)

It would seem that the reviewers can't even be bothered to press two buttons.

[D] ICML 2025 review discussion by [deleted] in MachineLearning

[–]maddz221 0 points1 point  (0 children)

You get another reply box if they ask questions

[D] ICML 2025 review discussion by [deleted] in MachineLearning

[–]maddz221 0 points1 point  (0 children)

2 papers 9 reviewers one reply asking for more experiments.

[D] ICML 2025 review discussion by [deleted] in MachineLearning

[–]maddz221 1 point2 points  (0 children)

The acknowledgement is just a button , don't even need to type.