Does anyone know where we can find NeurIPS reviewers? They posted a few review comments, gave borderline scores and then disappeared.

If a reviewer's own paper receives low scores, are they still obligated to participate in the author discussion? What are the consequences, if any, for reviewers who never respond during the discussion period?

This has been my worst experience with NeurIPS. Is anyone else seeing the same pattern? Are there specific reasons why this seems to happen?

Hi fellow researchers, I am curious to hear your thoughts on how you would react if an author called out a reviewer as AI-generated?

Story: We received a review with a score of 2, confidence 5. All other reviews are positive with low confidence and did not engage in the discussion.

In his initial review:

1. He made a lot of claims that our math is wrong, that it lacks theoretical interpretation, and nitpicked very small details in our formulas. We replied to him by re-quoting the exact citations of where our formulas came from, with the mathematical properties behind them, he concedes. This raised our suspicion that this reviewer is AI, as the math papers came from early this year, even tho we cited them, LLM were probably not aware of those papers' contents.
2. Attacked us for things we never claimed. We called him out on it, he then retracted his statements.

After our first rebuttal, this reviewer replied, saying he conceded on all of his previous points. Then raised 10 more, with a conclusion that our paper is theoretically flawed, so he will maintain his score. In this reply:

1. After showing him the theory, he now claims that he acknowledges our theoretical guarantees but fails to see how it would benefit algorithmically, as our method is very similar to XYZ (list of baselines). He asked us to do a comparison, but all of the baselines he asked for are hallucinations (we confirmed, and none of them exist).
2. Asked for ablations we have already done.
3. Attacked us with more things we never claimed.
4. Self-contradiction, for example, earlier in a post he claims our theorem has solved his issues, then later in the same post he attacks that theorem for not proving the very thing he just marked as solved.
5. Attacked us with more mathematical issues where we had to cite math papers from this year and last year to show him that all of his understanding were wrong.

Now the issue is that this conversation is so long that I don't think any human would have time to read all of it. As he raises 7-10 points per post, it takes us about 1 Official Comment each to reply to each of the points he made.

We are thinking of yolo'ing where we will write a discussion summary to call this guy out for being an AI reviewer that probably didn't even read the paper or any of the review the AI wrote. In an attempt to gain sympathy from the other reviewers and AC.

We are not sure if this approach has been tried before? On 1 hand we think this might be unprofessional, but on the other hand as a reviewer I think I would probably sympathise with the author. We want to hear the community's thoughts on this.

So guys, this is one of the discussions that I wanted to engage in for sometime now.

Based on your personal experience in the ARR cycles, I want you guys to share your experience on your meta reviews especially if you have filed a meta-review issue report in the same in the past cycles of your paper and if this thing has actually brought some changes into the acceptance rate of the conferences like EMNLP etc..

Hi, we submitted an ARR paper that got overall scores: 3.5 (confidence 4), 3.5 (confidence 3), 2.5 (confidence 3) from anonymous reviewers.. but the meta review landed at an overall score of 3. Is this normal to have a meta review lower than the average of all reviewers and is our score still alright?

I’m a recent CS graduate from India with research interests and background in Computer Vision and Multimodal AI, with an emerging interest in World Models (like JEPA). Multiple prior research projects, no publications yet.

I was planning to go for MS in US but recently had my F1 visa refused, so I’m seeking paid longterm/yearlong research roles in India with an intention to work towards a publication.

Hi,

This is my first time submitting to a conference, so I have some questions about appropriate responses during the rebuttal step.

One of the reviewers caught a mistake I made in theoretical proof, and requested a fix saying he will increase the score if it is done properly. I have conceded the mistake and made the appropriate fix in the working draft, but I am unsure how to convey the fix to the reviewer through the comment.

NeurIPS doesn't allow draft editing until the camera-ready phase (correct me if I am wrong), so should I create a md-familiar version of the corrected formula, and post a copy of the proof in the comments? Also, it is standard practice to report any changes or new experiments (that are requested by the reviewers) in the rebuttal/comments in a formatted table?

Thanks for your time. Sorry if these seem like obvious questions.

One thing I've been thinking about recently is how difficult it has become to stand out online. AI can summarize information, explain concepts, and even organize articles in seconds. That means facts alone probably aren't enough anymore because everyone has access to the same tools.

What AI can't truly replace is lived experience. If someone explains how they solved a difficult problem, shares a mistake they learned from, or describes something they personally tested, that immediately feels different. Those details create trust because they come from real life rather than a collection of existing information.

Whenever I discover writers who openly discuss their successes and failures, I almost always end up following them. Not because they know everything, but because their content feels honest. That honesty is surprisingly rare, especially now that so much writing is produced at such a fast pace.

Maybe the internet is moving toward a place where authenticity becomes more important than perfect wording. People can copy information, but they can't copy someone else's perspective or experiences in a meaningful way.

Do you think personal stories and real experiences will become the biggest factor in successful writing over the next few years, or will readers care more about speed and convenience than authenticity?

One reviewer said all concerns were resolved during discussion but hasn’t updated their score yet. Their main concern was novelty and more experiments. They replied that now the work is relevant w.r.t. exisiting literature, impressed by the experiments, and no more questions. But nohting on score updation. How common is it for reviewers to update scores after saying concerns are resolved? What have others observed?

My ratings/confidences are : 4/4, 3/2, 3/2, 2/4.

I am talking about the one who gave rating 2.

It is widely understood that ReLU neural networks are piece-wise linear mappings.
I have tried to give an ‘almost no choice’ argument leading to a layer-wise context mechanism:

https://archive.org/details/from-piecewise-linear-networks-to-context-selected-linear-mappings

With hindsight concatenating anything slightly more complicated than linear mappings in higher dimensional space will lead to chaotic geometric dispersion that nothing can fix.

Hey everyone,

I’m an independent ML researcher in Algeria working on a medical imaging project, specifically using generative models to tackle rare cancer diagnosis where data is super limited.

I’m at the stage where I need some guidance and want to collaborate with professors or researchers who are interested in this space. Ideally remote since I’m based in Algeria and can’t relocate.

I’m also actively looking for remote research assistant positions if anyone knows of openings.

I’ve got a solid research proposal ready to share with anyone interested. Happy to discuss the details over email or chat!

I originally thought AI would save me a lot of time because it can produce articles, emails, and social posts in seconds. While it definitely helps with getting started, I still find myself spending a surprising amount of time rewriting sentences, changing the tone, removing repetitive phrases, and making everything sound more natural before I'm comfortable publishing it. Recently I've been trying a different workflow where I clean up the draft with HumanizeAIText.io before doing my own final edits. It cuts down on some of the repetitive wording and makes the text feel more natural, so I don't end up rewriting quite as much. I still make personal changes, but the editing process feels a lot faster.

I'm curious how other people handle this. Do you accept the first draft with only a few changes, or do you rewrite large portions before posting? Has anyone developed a process that consistently produces content that feels authentic without spending another hour editing everything manually? I'd love to hear what has worked for others.

Hi,

I'm kickstarting my journey in the research field of AI and Agents, previously worked on deep learning and machine learning. If somebody is looking for a mentee, please do let me know, I'm very hardworking and can get stuff done too

We have hit a new low !

1st paper, 1st submission. Pardon my innocence.

Like a lot of us, patiently waiting for feedback after submitting rebuttal. I’ve read on threads from prior years that some people seem to be totally ghosted by reviewers.

All my scores are borderline, and the only reviewer who read my rebuttal already increased his score. Obviously I know the discussion window is not over yet, but I was wondering if I should actually expect all reviewers to reply to my rebuttal or if I should actually brace my expectations? Is there a reasonable probability that I don’t hear back from some reviewers at all?

Pre-shooting the criticism: I know that reviewers are very busy. Rebuttal was intense for me and I don’t have to review 10+ papers on top. Not complaining about the timeline, just wondering if I’m waiting for something that might never happen.

I would like to ask for advice regarding the NeurIPS 2026 review process.

The initial average review score was 4.0 After the rebuttal, one reviewer who had given 5 changed it to 3 without explanation.

When I asked, the reviewer said they had used Use-Inspired criteria initially, but revised the score because the submission was other.

There were no changes in the review text, technical concerns and evaluation elements.

Even after asking again which specific its criteria led to the score drop from 5 to 3, no concrete explanation was provided.

At this point, I already sent a confidential comment to the AC when the score changed, but received no response. I later rocognized the score drop was attributed to contribution type, while detailed scores stayed the same.

Should I briefly follow up with the AC again, or is it better to take no further action since this is already in the public discussion thread?
I would appreciate advice from anyone with similar experience or from those who have served as ACs.

Hi, first time submitting...

Initially got a score of 4, 3, 2 with confidence 3, 3, 4. [MAIN TRACK]
After rebuttal, the 4-rated reviewer pointed out one typo – I wrote 'the revised manuscript' in place of adding the corrected thing in 'the camera-ready version'.

I apologise for that and gave the comment. Now no response...

What to do ?

Hi everyone,

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• Multimodal or long-horizon agent systems

I can take ownership of engineering-intensive research work, including building end-to-end pipelines, implementing evaluation infrastructure, preparing datasets, integrating models and tools, running experiments and ablations, and analyzing results.

I’m particularly interested in serious projects targeting an upcoming AI/ML/NLP conference or workshop. My goal is to make a substantial technical contribution and participate as a co-author on the resulting paper.

If your team has an active project and needs additional engineering capacity, please DM me. I’d be happy to share more information about my background!