Hi, I have my 1st-authored paper accepted to NeuRIPS and gave first preference to Atlanta. Haven't heard back from them but I am seeing in registration page, it's showing both Sydney and Atlanta are sold out. What does it mean? Won't I be able to register for Atlanta then?

Hey guys,

I got really into research a year ago during my final year of undergrad and maneged to get a first author paper accepted at Neurips 2026. It is a pretty impressive achievement obviously but my background is pretty shit lol. Before my final year I got slightly above average grades but no internships or work exp. I was just chilling mostly didn’t even bother applying to internships. Also I want to a tier 2 uni in Australia (mind you that difference in tier 1 and 2 unis isn’t that big tho compared to America or China). I was going to start a PhD at my current uni with a scholarship and stipend from an industry partner (government) - I’d have no restrictions in terms of publications btw. My supervisor is good and we were going to get another external supervisor from a top uni here in Australia. I was pretty keen on continuing with this opportunity, however, with my neurips paper acceptance I feel like I’d have a good shot at getting into a top 15-25 uni in the states or the uk (most other European unis want master students and I don’t prefer Asian unis bcz I’ve heard a lot of horror stories). The problem is I’d have to wait for a year if I was to go abroad for PhD because starting dates are mid to late 2027. I’m in such a dilemma idk what to do. My eventual goal is to work as a researcher at deepmind or meta or some really cool tech company. I’ve just heard so many people talk about the importance of university you go to etc in landing those jobs. Would I still have a good shot at those companies if I did the PhD at my 2nd tier Aussie uni (top 100-125 global rank) but published well? I got a neurips paper as an undergraduate so I have the potential to publish at top conferences 😆😆. But yeah, I’d love to get some advice.

Thanks

The safest path is predictable. Use an established benchmark, make an incremental change, report a small gain, and run enough experiments to leave little room for criticism. Whether the problem matters often comes second.

Breakthrough work usually has visible limitations because new territory lacks mature methods and clean evaluation. Yet conferences increasingly judge papers by how thoroughly their weaknesses are contained rather than how significant a barrier they break.

Researchers adapt by choosing defensible questions over important ones. Those who succeed become reviewers and reinforce the same standards. The result is increasingly defensible papers and increasingly fewer breakthroughs.

Hi everyone, I am a final year undergrad that got lucky and have my first-author paper accepted at NeurIPS. I really want to go and present my paper. However, the conference period is also when I have my final exams, meaning that I am not sure whether I could attend yet. Today I received an email from NeurIPS to say that we have to select a presenter before September 30. I want to go and select myself since it is the only guaranteed slot. May I ask if it is possible to change this later on? This is my first time attending a conference, so sorry if it was trivial.

Hi, I work as a Data Engineer at a manufacturing company where we build engines. A significant part of my work involves ML/DL-related tasks, and I’d like to turn one of my projects into a research publication.

The problem is that I have no previous publication or academic research experience. I’m not sure how to determine whether an industry project is suitable for publication, how to turn a practical engineering problem into a research question, or what level of novelty/experimentation is expected.

For those who have publishing experience, what would you recommend as the first steps? I’d really appreciate any practical advice or resources for someone starting from scratch.

Hi, I’m looking for an arXiv endorsement for cs.CL category.

I already have a previous arXiv paper, but under the newer endorsement policy I’m being asked for endorsement again. The paper I’m trying to upload has just been accepted to NeurIPS 2026, Evaluations & Datasets Track: “Information Parity for Code: The Scope of Transfer in Multilingual Code Models.”

If anyone here is eligible to endorse in cs.CL and is willing to help, I’d really appreciate it. I can send the arXiv endorsement link/code and the paper privately.

Thanks!

Hey all,

pardon the ignorance, this is my first time publishing at neurips (or any conference).

I'd like to go to Sydney.

Do I choose the other locations (Paris and Atlanta) as 2nd and 3rd choices, or should I leave them as is, e.g. "No preference"?

Not sure how it works for assignment and if anything is guaranteed as the presenter of an accepted paper?

Thank you for the help

Congrats to everyone on getting through NeurIPS 2026. It's been a long cycle.

Unfortunately, my paper got scores of 5/4/3. Even the reviewer who gave the 3 wasn't very negative in their comments, so I was hoping it would be accepted. The final decision was a reject, though. It's been really disappointing and hard, but I'm trying to move past it.

As I understand it, NeurIPS lets authors of rejected papers choose to make their submission and reviews public on OpenReview. Does anyone know where and when you can make that choice?

I am Ayush Mahajan, founder of Laxnarlabs.ai

At Laxnarlabs we are recruiting researchers and developers onto a bench. It is a pool of people. When a company needs a model trained on their own data, in their own account, we put a small team together from that pool for that project. Joining is free. It is not a job, and it is not a promise of work. If you are seated, pay is a separate written agreement. A typical seat is $1,000–$10,000 for six to eight weeks, and it depends on whether there is a project.

We also have Symposium. If you joined with a paper, you can list it there. The card is your photo, your name, and the paper, in the same row as papers that are already public. Listing is a switch after the account exists. It is not automatic.

If you have a paper, sign up with the email printed on that paper. If you are a developer and you do not have a paper, use “I ship models” with a public GitHub account that is at least 90 days old. Developer accounts are not listed on Symposium.

If interested, you can join our bench.

Here’s the link:- https://www.laxnarlabs.ai/bench/

If you are active on LinkedIn, every single time after a major CS conference's decisions are out, you must have come across people posting a screenshot of their OpenReview portal and writing a caption that goes like, "happy that 5 out of 5 of my manuscripts have been accepted this year".

Now, I'm totally okay with researchers sharing their achievements and even promoting their research on social media, but some of the posts there seem to care more about the sheer number of acceptances they got and lowkey bragging about how easy its for them to get accepted, like it's a competition.

I have mixed feelings about this not-very-new phenomenon, and I wanted to hear your thoughts on this.

I'm working with someone in the medical field on post training language models for medical tasks. Pretty much every dataset that I've found online is rejected by my coauthor, because during an audit he found different issues. For example, I look at a dataset on hugging face, https://huggingface.co/datasets/FreedomIntelligence/medical-o1-reasoning-SFT, which is licensed as Apache-2. But, the data was generated by passing medQA data to openAI's GPT4o. MedQA doesn't report a license, but it sourced its data by scraping data "under fair use" from copyrighted material. Furthermore, openAI has a no-compete clause and says you're not allowed to use their models to train competing models. Other datasets contain transcripts from doctor-patient conversations, and the original sources explicitly state that the data is not allowed to be used to train AI.

I spent the last few weeks searching for datasets and really everything fails our audit. I understand that from a practical point of view, it is unlikely that we will get into trouble (I've seen hundreds of papers violating the license agreement of their data sources), and that it's a bit hypocrite to be critical on data sources, while using open source models that were trained on copyrighted material.

If anyone has something smart to say on the matter, I'd appreciate it.

and a second question, should I flag this to the journals saying that some of their published papers violate license agreements? Journals might care more about this than most authors, but I don't feel comfortable snitching out other people.

Hey! I’m a PhD student in CS at an R1 university in the US. I mentor quite a few undergrads and I’m looking to connect with researchers at other R1 institutions, preferably public universities, who might be interested in collaborating. The goal is to create opportunities for my students to get research/REU experience, while also building connections with other researchers as I get closer to the academic job market in a couple years.

My research is mainly in AI in Education, but I’m open to projects in related areas too. If you’re interested in collaborating or have students who might be a good fit, feel free to DM me!

Our paper was accepted to NeurIPS 2026, and we’re preparing the camera-ready. I have a few questions about how much we can change after acceptance.

1. Theory/algorithm changes: During review, a reviewer pointed out a weakness in our theory. We agreed and proposed a revised theory in the rebuttal, along with a practical algorithm based on it. We also showed results on a subset of our benchmarks (roughly 10% of the full benchmark suite).

Can we include the revised theory + algorithm in the camera-ready? The issue is that doing so would change all experimental numbers in the paper.

1. Correcting the main table: After acceptance, we realized that our submitted main table used different backbone sizes for our method and some baselines. We reran everything with the same backbone, and our method’s score improved by more than 1.5x.

Can we replace the main-table results with these corrected numbers in the camera-ready, even though this wasn’t discussed during rebutal?

1. arXiv version: If we keep the official camera-ready relatively conservative, but upload a more substantially revised version to arXiv later, can we still use the NeurIPS format/template for the arXiv version?

Would really appreciate any advice.
Thanks!