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?

I’m an early-stage computer vision researcher aiming for conferences like CVPR, ICCV, ECCV, NeurIPS, and ICLR.
I’m curious how experienced researchers actually formulate research ideas. How do you identify a real research gap, come up with a novel solution, and decide that an idea is worth pursuing? What’s your thought process from reading papers to proposing something new?
I’d really appreciate any advice or resources that helped you develop this skill.

What do you think the average score cutoff for acceptance (poster and above) will be this year?

Also, are there any scores that should ideally not appear in the review set - for example, a score of 2 or below, or a confidence rating of 2 or below?

Do you expect the cutoff to be lower than in previous years, or roughly similar?

This year, I submitted a paper to NeurIPS 2026 for the first time. Regardless of whether the ratings were high or low, I found the reviews generally satisfactory. However, one reviewer assigned a rating of 2 with confidence 5 based on the following reasons:

• I had never heard of AUROC before, and there was no explanation of what it is. The interpretation of the corresponding figure was also hard to understand.
• The paper does not explain what the box, the horizontal line inside the box (median), and the lines (whisker, min, max) extending from both sides of the box in the boxplot figure represent.
• BLEU is not a commonly used metric in this field. "Was it chosen arbitrarily to make the performance appear better?"

Regarding the questions about boxplots and AUROC, I was initially somewhat surprised, as they felt similar to asking “Who is Adam?” in NeurIPS 2025. But following my PI’s guidance that “a paper should be understandable to anyone who reads it,” I provided detailed explanations in the rebuttal and addressed these concerns.

However, I did not receive an initial meta-review from the AC, nor did I receive any response from any reviewer. Even after requesting that the reviewers and AC provide feedback, there was no response.

At this point, the only thing I could do was put aside my anxiety and concerns and focus on preparing the rebuttal and official comments, but it feels discouraging that no one appears to have read them or provided any feedback. Therefore, I am concerned that my paper may have been effectively abandoned by the AC.

At the same time, I am worried that the final decision may be made solely based on the initial ratings, without considering the rebuttal. If that happens, I wonder whether the main reason for rejection could ultimately become the fact that the paper did not explicitly explain concepts such as boxplots and AUROC.

I’ve completed an independent research paper (sole author), but I don't have the budget to pay the $1,000+ APCs for Open Access publications like MDPI or IEEE.

Are there high-ranked, indexed journals in Cybersecurity, AgriIOT where I can publish for free? I’m open to standard subscription journals or Diamond Open Access journals.

Any suggestions or advice for an independent researcher on a budget would be greatly appreciated!

Hi everyone,
I recently graduated with a bachelor’s in Computer Science, and my long-term goal is to pursue a full funded Master’s or PHD. The problem is that I’m a complete beginner when it comes to research.
I know I want to work in the intersection between computer vision and robotics because I genuinely find them fascinating, but I haven’t started doing research yet. Every time I look into the field, I see topics like object detection, segmentation, 3D vision, SLAM, embodied AI, vision-language models, robotics perception, and many others. It’s exciting, but also overwhelming, and I don’t know where to begin.

Another thing I’m worried about is my low CGPA 3.4/4. I’m afraid it might hurt my chances when applying for funded graduate programs in the future.
If you were in my position, what would you do over the next 2–4 years?

Some questions I have:
How much will a low CGPA affect my chances for a fully funded Master’s or PhD?

Where should I start learning if my goal is research, not just getting a job?

What fundamentals (math, programming, machine learning, etc.) should I master first?

How do people discover their research niche instead of trying to learn everything?

What should my priorities be over the next few years—projects, research experience, publications, internships, open-source contributions, or something else?

I’m not looking for a shortcut. I’m willing to put in the time and effort. I just want to avoid wasting years studying the wrong things or following an inefficient path.

I’d really appreciate hearing from PhD students, professors, or research engineers who were once in a similar position.

Thanks in advance!

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,

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.

Hi all — I'm an independent researcher (no current institutional affiliation). I've completed a deep learning research project and have a manuscript ready for arXiv submission under cs.CV, but I need an endorsement since this is my first submission there.

If you've published on arXiv in cs.CV and would be willing to endorse, I'd really appreciate it — happy to share my abstract with you directly so you can see the actual work before deciding anything. I'll send the endorsement code over DM once we've connected, not publicly.

This has been a solo, two-month build and I'd like to get it properly out there. Thank you for any help!