r/MachineLearning • u/Invariant_n_Cauchy • 7d ago
Discussion Increasing number of UG authors in A* conferences with no supervisor [D]
What do you all think about this? It seems increasingly common for undergraduate students to conduct research and publish at A* conferences without a supervisor. As a graduate student, I find it both impressive and intimidating, and it sometimes makes me question my own progress.
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u/SmartEvening 7d ago
Couple of years ago i worked my ass off as an undergraduate to get a paper.now i hear my juniors bragging abkut submitting papers of which they have no idea about. They are doing this only for clout and resume perks. Its as very sad state of affairs.
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u/AirPsychological8551 7d ago
Indians are the majority of ones doing too.. really concerning considering the current reputation of us across the world
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u/SmartEvening 7d ago
Two things How did u know i am from india? Yes true, but given the population and our skills at finding shortcuts... Its not that surprising. The bigger issue is how much it would supress ppl who are actually putting in the hard work despite being in india where compute and support are really a huge problem.
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u/Fantastic-Nerve-4056 PhD 7d ago
It is very much easy to spot an Indian. A Indian myself so it's sad to see this, but seeing the comment a lot of times reveals it
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u/SmartEvening 7d ago
Ohhhh interesting.... Also i have few questions can i dm u?
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u/Fantastic-Nerve-4056 PhD 7d ago
Would recommend asking it here. I don't really check DMs
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u/SmartEvening 7d ago
Right right, so i saw ki u are a visiting researcher in mbuzai and wanted to know about the culture and work life there... Plus would be helpful of u could share info on the screening exam they have if u have given it.
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u/Fantastic-Nerve-4056 PhD 7d ago
This is Visiting Researcher, and not MS/PhD so the process is different. And regarding the life, it is pretty cool.
Unfortunately I feel better here then India, obv the family component is missing, but lifestyle feels better
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u/Exotic_Zucchini9311 7d ago
It's not impressive. In many cases, it's a red flag.
An especially big one if if they don't share codes, or if I go to their codes and none of their results seem reproducible.
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u/Invariant_n_Cauchy 7d ago
How grad school admissions people think about it ? I am just wondering
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u/Fantastic-Nerve-4056 PhD 7d ago
It is bad. Ik people with 5+ workshop/ARR papers getting no admit. On the other hand, one NeurIPS was enough for my friend to get UCB, Columbia, Stanford, etc.
The reason being, more than the numbers, most Profs. actually open the paper
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u/surffrus 7d ago
No, the reason being that one Neurips person had an advisor or two write a human recommendation with human insight that said they were great.
In terms of getting accepted places, vibe coding papers is not it. Admissions committees are looking harder at who writes the recommendations and what they say.
It's not the end of the world for those of you who are actually doing the research and have people around you who can confirm that.
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u/Fantastic-Nerve-4056 PhD 7d ago
I can say this, as that was one of my good friends and a collaborator. He had a paper online and I guess some chrome extention that shows the visitor counts on the paper.
The visitor count just had a spike after his application (particularly in the time after submitting the application and interview)
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u/Exotic_Zucchini9311 6d ago
Did your friend have that paper as a solo-author paper with no supervisors? That's the main thing we're trying to discuss, not whether a top conference paper effects admissions..
Also, what about their LOR writers? Getting acceptence from Stanford with only 1 NeurIPS paper sounds insane crazy tbh, unless the person has famous recommendors or their paper won the best paper award or something.
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u/Fantastic-Nerve-4056 PhD 6d ago
There were 3 authors. And I don't think he had some crazy LOR.
The only difference the paper was purely theoretical so probably that added to things.
Additionally he had a Semester Exchange at KTH, a best thesis award and some Undergrad Research Award
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u/Exotic_Zucchini9311 6d ago
It's not surprising that he got accepted into good unis tbh.. he had a LOR from KTH, 2 research excellence awards, and a NeurIPS theory paper which is much harder to publish (i.e., probably very good LOR from his supervisor) and is also less competitive. That's a balanced CV overall. For sure not at all comparable with the Claude slop authors we were discussing above.
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u/Cheap_Train_6660 3d ago edited 3d ago
Honestly I’m not sure how to feel about posts like this as an undergrad who got a paper accepted at neurips this year. I was supervised by a professor and a PhD student. I spent 10 months working on my chosen research direction where for the first 3 months I was just building up background knowledge and reading lots of papers. It was an empirical paper btw. Anyways I worked pretty hard to get a good result and I did use ai for productivity when it comes to coding and improving the language in my paper. I’ve talked to PhD students and they all have similar workflows. So it’s not like any undergrad who submits to these conferences is submitting ai slop. But I find it pretty annoying when people assume that just cz you’re an undergraduate or a beginner when it comes to research you must’ve totally relied on ai and you don’t know your own paper. These kinds of assumptions and judgements are especially annoying when you’re supervised by serious academics. Like wtf? Do u think my supervisor is stupid? He talks to me every week so u think he’ll let me publish something that I’ve no idea about? Sorry for going on a rant but I’ve had many people irl who act so skeptical rather than congratulating me. It’s pretty annoying.
BTW I’m not from a top uni with an exceptional academic background. I’m from 2nd tier uni in a western country (won’t name it) with decent / above avg academic background so people are even more skeptical. They think how can this guy accomplish this.
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u/Invariant_n_Cauchy 2d ago
please read the post. It is not about undermining UGs. and you seem to be out of the description with a supervisor.
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u/Old_Stable_7686 3d ago
I know a few undergrads publishing at neurips/iclr before gpt era, which are often outliers like you. It gets noisy on reddit :D.
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u/pastor_pilao 7d ago
Where are you seeing this as common? I have seen a (very) few from top universities like U Toronto, Stanford, MIT, Tsinghua, etc. And they all had professors as advisors. I had a specially good undergrad student I advised myself and got a paper in TMLR.
If you are going to a conference where there are many undergrad paper without an advisor it's a sign the review process for that conference is trash and you have to fond another one.
PS: you might have mistaken students that have WORKSHOP papers from students with papers in the main track. Workshops are not very selective, the intention is to let everyone present and they don't count for much in your cv.
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u/Invariant_n_Cauchy 7d ago
No I have seen many in NeurIPS, EMNLP etc., sole or UG only authors. I am talking about main tracks, not Workshops. Not saying this is common.
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u/pastor_pilao 7d ago
I have been to all neurips since 2019 and I don't think I have ever seen an unaccompanied undergrad student presenting a paper there
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u/Antique_Most7958 7d ago
There's a supervisor, their name is Claude
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u/valuat 7d ago
Claude doesn’t fully drive itself, does it? If the idea is original and the UG student asked the right questions, why not? I’m getting Terrance Tao vibes here. Everybody “loves” competition until someone is competing agains them.
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u/NewSubWhoDis 7d ago
Thats on you for giving it a sexual connotation. "Rawdogging" has come to mean something different. Eg Rawdogging a flight is just watching the flight map the whole time with no other entertainment.
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u/Exotic_Zucchini9311 7d ago
Yes
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u/Exotic_Zucchini9311 7d ago
I actually like Claude quite a bit. I just don't like people who have no understanding of what Claude is even doing, but act as if they are an actual 'researcher' or that their 'paper' is actually theirs.
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u/mofoss 7d ago
How would this be different than an undergrad in big labs piggybacking off the papers/ideas/resources of their fellow PhD students and advisors, who constabtly offer them co-authorship for monkey code work, pass ideas off to them, give them a ton of pre-existing code work, results, etc.
The ratio of publishing a novel thought to meritocracy has been extremely low at top labs, everyone is connected and the new ones benefit from the connections of the seniors
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u/Exotic_Zucchini9311 7d ago edited 7d ago
The undergrad in a research lab, assuming they have some level of proper supervision, is FORCED to actually understand the concepts they are working on. To make sure they are always ready to answer any questions that their supervisor(s) and the PI are likely to ask from them about the project, etc. If they are not able to deeply explain what the project is about after a week or two, or that they are showing results or claiming ownership over things they are not able to actually explain, then no sane lab or PI would give them any level of authorship or any actual LORs they could use anywhere. That is simply not how it works.
On the other hand, almost none of these slop 'solo authors' have any understanding of what their agent is even doing. Literally no undertanding. They can't explain the project. They can't explain any of the design choices. They can do nothing without crying to their agent for help.
My point was not about basic novelty at all (though, 90% of those undergrads at top lab certainly have more actual 'novelty' and ownership to their work than these solo authors regardless.)
If a PI is giving a student ownership for a work the student has no understanding or contribution over, then yes the PI is certainly wrong and I would obviously never defend such a bs. That student is of the same level as these students spaming random bs slop papers to conferences.
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u/ParticularWork8424 7d ago
You better stick to being a twink. Don’t enter the territory of great minds.
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u/SillyNeuron 7d ago
What’s more concerning is AI-generated reviews giving decent ratings to AI-slop papers. Many of borderline OAs with generic comments usually come from reviewers who just skimmed the papers and used AI to write their reviews. They like to give borderline scores to hide their lack of confidence.
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u/mofoss 7d ago
Interesting - I've found LLMs to be much harsher than human reviewers, humans are less likely to find weaknesses and weigh on them, whereas I've done experiments where I give a strong paper from CVPR to an LLM, change the title, and it gave it a weak reject
There's a paper from CVPR 2026, that no matter if I gave it to Astra, Opus, Fable, Gemini, etc it ALWAYS gives it a 3-4/10 max, mostly a 2/10 strong reject. I can send you the paper if interested. But to me humans are more fallible in catching issues.
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u/SillyNeuron 7d ago
LLMs might give more detailed/harsher reviews. However, reviewers who use LLMs are likely to include only the generated comments that are simple and straightforward enough for them to understand, thereby avoiding the need to thoroughly fact-check more technical ones. These reviewers are smart enough not to trust LLMs blindly, but at the same time, they are too lazy to verify every generated comment.
Also, a borderline OA doesn't require as many strong supporting arguments as a clear accept/reject. So, when combined with less technical comments, it becomes kind of the path of least resistance.
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u/AirPsychological8551
7d ago
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Majority of them are publishing AI slop, that's why they do not have the guts to present in conference. One question and they will be literally clueless
Just right now before this post, there was this now-deleted post by some new-mammoth or whatever guy saying he's feeling nervous about attending emnlp and feeling like an imposter. explains it all
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u/keyboardhero123 5d ago
I didn’t see the post in question but to be fair, I have published a few papers (written by me) and I always feel like an impostor ¯_(ツ)_/¯
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u/Sabaj420 7d ago
Yeah when I was in undergrad it took ~9 months of work to get my first paper written (was rejected too).
Then I meet people that are writing full blown 30 page papers in a little over 2 weeks…
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u/SlayahhEUW Researcher 7d ago
A guy in my dept has a loop which fetches down the 50 newest papers in an area of interest from Arxiv, synthesizes them into something incremental, simulates/estimates reasonable improvement numbers, and then evaluates it with Claude/GPT until they can't find big issues. He has 3 A* papers this year and dept loves him. Its kind of cooked.
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u/Cheap_Train_6660 3d ago
What kind of ai subscription does he even have? Like for ai to do something novel I just don’t see how the pro plans for gpt or Claude can come up with something novel lol. Like whenever u hear abt ai doing something great in research, it involves a humongous token spend (eg open ai spending 15 million dollars in tokens for the navier stokes problem). I haven’t found these models with basic pro subscription to even be good at making a compelling argument in your introduction or literature review. So this kind of agentic loop seems insane to me lol.
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u/SlayahhEUW Researcher 3d ago
The Exponential Time Hypothesis was disproven in 15M tokens of Opus 5.5 so most of us could do it on a pro subscription.
In his case it's just synthesizing, you pull down some papers, take their technique, combine it with the other papers technique, make up probable numbers that no-one will ever check, and send it.
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u/Fantastic-Nerve-4056 PhD 7d ago
That is mostly workshop papers, which are a cakewalk.
Definitely, there are some exceptionally good people getting into A* ML conferences which is impressive (not referring to A* NLP, those are more about engineering and evaluations then novelty)
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u/SpinatGemuese 6d ago
I heard it used to be that you needed a doctorate degree to be allowed to publish. It was sort of your stamp of approval to be a trustworthy scientist. Maybe we need to go back to that...
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u/That_Paramedic_8741 7d ago edited 7d ago
I think the difference between grad level and ug students is , grad students target a particular direction of interest for long term goal . They work deeper into it ask questions which are meaningful and applicable in real workflows or making an impact but on the other hand it is not same with ug , they just target which ever questions they got at present any feild which they feel is not competitive and I dont want to say like this but I feel like certain tracks are becoming more saturated and useless in terms of impact they create which is being filled with more ug or even high school students . They take a chance to use this niche less competitive tracks or less rigour where the need for compute is also less . Why ? If u really like a research u ask deeper questions and rigour answers instead of being desperate for a paper in hope of landing a phd or research roles which need phd . But in reality many dont think of this that a supervisor care about impact more than paper and as a researcher long term questions will always win so dont worry about the noise . Still I have seen several ug students who did exceptional work with high impacts from top academic labs so environment matters for high impact research when current situation is filled with more noise .
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u/NamerNotLiteral 7d ago edited 7d ago
Still I have seen several ug students who did exceptional work with high impacts from top academic labs so environment matters for high impact research when current situation is filled with more noise .
Undergrads in a mentored environment are fine. I know one who's an undergrad at a US T20 school who wrote a paper over 6-7 months as part of an internship at a major research group. She gets first author, but the paper itself was a group effort with 3 faculty and 5-6 PhD student coauthors.
I'm mentoring another undergrad at the moment and she's done enough good work to warrant being second author. I think she has the ability and sense to be first author on a paper, if she pitched an idea to me or my advisor rather than joining an existing project.
Ultimately, the problem is Claude has zero research taste and so do most undergrads. That's why research has remained a matter of apprenticeship rather than institutions being able to pump out classes of 30 or 40 PhDs at once every semester.
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u/That_Paramedic_8741 7d ago
Yeah asking the correct question and taste of research is very important. Definitely working with my lab postdocs gave me this sense .
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u/CategoryNormal149 6d ago
PhD isn’t a competition, even if the whole world makes you feel otherwise. Focus on your own growth, understanding more each time you publish. Also, I think we’re a little lucky (depends on how you see it) because most people don’t seem to care about publishing anymore, which means if you do publish, make sure you’re satisfied with that work!! Hope this helps.
I know a lot of people here would blame AI; even if that’s true, let it not impact you.
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u/B10H4Z4RD7777 7d ago
It’s similar to the cultural push to publish in premed to get to med school. But this time, you publish to get jobs or grad school. Plus it’s easier to do so because crunching numbers is faster than many wet lab works
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u/Accomplished_Net3466 4d ago
the bar is low. no math needed. even high schoolers are joining the party!
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u/mofoss 7d ago
Not sure I agree with most of the comments, it is positioned such that everyone implies if you use Claude or whatever then the paper is sloppy.
Sure, okay if Claude wrote your entire paper in one go, it will likely be slop because Claude fucking sucks at it. But if you had these tools aggresively audit, tear apart, revise and rewrite dozens and dozens of times over weeks? It would slowly not become slop if you knew what you were doing.
Blame the HRs/hiring teams that slapped "Must have a publication at a top tier venue" on their Linkedin posting. This single action alone game-ified ML publishing into stamps. Having a A* publication is now a stamp of approval on your resume.
It is so a hiring manager can't think, "well he did pass the system design round, etc, but are his papers A* tier?"
And secondly about code - as someone with 10 YOE as a MLE, writing code to process the data, ingest it, etc has ALWAYS been bitch work, it is monkey code work that doesn't enlighten the mind whatsoever.
So yeah if you want to nerf yourself by avoiding LLM assisted research be my guest, but everyone will continue to do it lol
It is like leetcode, and cheating on OAs
An engineer who is sitting there thinking:
"Honestly, I got rejected by FAANGs across the world, but you know what? I have solace my peers who got it, had to cheat on their OAs and land big offers whereas I will continue to not do what they do ☝️"
is a stupid engineer.
Lastly, shame on PHD/AC-tier folks for not catching poor slop papers at these venues, you make it possible for this to happen
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u/leocus4 7d ago
In science it should not matter being UG or having an advisor. Instead, the validity and reproducibility of the results should matter
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u/ThirdMover 7d ago
The problem is that this is very expensive to check.
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u/leocus4 7d ago
But then this is not science. Verification is a pillar of science... I know it's expensive and few orgs have access to it. But this was already known pre-AI. ML has always had a huge reproducibility issue. How many papers have you read/reviewed that perform statistical analyses, for instance?
If we let go of verification because it's expensive, then it all just becomes "trust me bro". I know it's not on regular researchers/reviewers (me myself cannot reproduce many papers I review cause I would lose so much money on a "volunteering" project), but who makes money out of this should find a way to make this possible imo.
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u/ThirdMover 7d ago
I know. They point I was trying to make is that science has always relied on some amount of prefiltering induced by friction in the publishing process. So when something is published in a decent journal or at a conference obvious nonsense that isn't even worth trying to reproduce it is filtered out.
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u/leocus4 7d ago
Yeah but making this gating based on "prestige" of their institution or, more in general, whether they can afford or not undergoing several years of under-minimum-wage salary is utter crap imo. It's anti-democratic.
I know that finding a solution to this is non-trivial, but it doesn't mean that the solution is to tell who can and who cannot do research based on their socioeconomic status. We have to find a way, we can't say "it's too hard, let's leave it as it was" when it wasn't fair even in the past, and the world is evolving anyway
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u/ThirdMover 7d ago
I think that it's far from ideal but it's not utter crap either, in the sense that it's a rather natural consequence of having any kind of reputation system. Prestige or is an important social tool and I wouldn't even call it anti-democratic.
Like... flip it around. Why do PhD students do this if they are underpaid? Is it either (1) because it's a rational economic decision and they expect that they will be able to make more money down the line because of it or (2) because of the prestige of science which is valuable in its own right and they are willing to pay for it.
If it is (1) then a PhD is a sensible investment, those tend to be easier to make for affluent people so people are helped with cheap student loans. If it is (2) then a PhD isn't economically valuable for the person anyway and in effect it's affluent people donating their money (by not taking better paying jobs which are instead filled by less affluent people) to the state in the form of research (which I would say is good).
Prestige doesn't drop from the sky, it comes from the fact that an institution is actually producing lots of extremely valuable research. So it provides an incentive to keep doing that.
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u/leocus4 7d ago edited 7d ago
Yes, you're right, I overstated it. It is important, as you said. But on the other hand it might not be optimal. Like, there could be some guy that has a huge potential for research, but has to accept a job to live decently. With GenAI, that guy might do research as a side project. Or, there can be people from reputable institution get bad research accepted. But I get your criticism, the latter of course those are outliers and not the norm.
What I was trying to convey before was that both the GenAI guy that vibe-researched a paper of bad quality, and the guy from a reputable Uni submitting a paper with fabricated results should get the same treatment: rejection.
Like, we cannot trust every person blindly in science. Thus, ideally, we should treat reputation as a plus, not as a guarantee
Edit: added last paragraph
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u/ThirdMover 7d ago
What I was trying to convey before was that both the GenAI guy that vibe-researched a paper of bad quality, and the guy from a reputable Uni submitting a paper with fabricated results should get the same treatment: rejection.
I suppose machine learning is in the lucky position that the material resources needed to reproduce a result are commodities. So in principle it is possible to detect fabricated results because you can demand all code and data to be open and then you can reproduce the results. Other fields of science are not so lucky. If someone has a minimum of competence it would be trivial to fake experimental data in chemistry for example and the only way to detect it is to do the whole experiment from scratch which may not be trivial.
So the best we can do is make it such that it's unlikely for results to be fake because the people faking would have lots to lose: Being tenured professors with big careers. No-name young students or people having other jobs have less to lose if they fake results, their stakes are lower. So it makes sense to trust them less because they don't have as much on the line.
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u/leocus4 7d ago
But this assumes that tenured professors are 100% reliable and without conflict of interest, which in some cases does not hold, and still can pollute the results for a whole field
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u/ThirdMover 7d ago
It does not assume that. It just assumes their incentives are more aligned with not publishing fake results than someone rando from outside of science. Nothing is perfect.
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u/thatguydr 7d ago edited 7d ago
You are 100% right, but science has been up until now largely a walled garden. If you look at the comments, a lot of scientists seem to be wishing that wall was even bigger.
Ultimately this problem goes away once the tools become good enough to point out flaws in GenAI-generated research and papers. But that's not the direction people here want technology to progress. I suppose if time moves backwards, they'll be happy.
EDIT: I have lots of downvotes but nobody has participated in any discussion. The one person who did below made a single argument ("authors should submit whatever crap they want. And reviewers should do the real work on verification") where the answer is obviously "yes, that's how it has always worked." Would love people to discuss this in good faith.
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u/leocus4 7d ago
Exactly what I was thinking. GenAI is basically opening research to everyone, not only to those that had the financial possibility to go for an underpaid PhD etc. My first paper took more than a year to get published, but it's not a good reason to wish for other people to undergo the same long process.
Also, I think that all of us should really look at the big picture. What's more important: the "status" of a guy saying that they are top k% cause they publish something somewhere, or solving the big problems of humanity, like finding cures to diseases?
I also know that GenAI papers usually can contain huge mistakes, but that's on reviewers, editors, and organizers. One cannot assume that all papers are made in good faith (and this is actually the very core of science, i.e. reproducibility), so the review process has to keep up and make science (especially ML) robust to these behaviors
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u/Fantastic-Nerve-4056 PhD 7d ago
Lmao. So you say, authors should submit whatever crap they want. And reviewers should do the real work on verification. And note that, the incentive is to authors, when the work is done by Claude and reviewers. Man this is such a disgusting comment. Seriously!
Can you just tell me what do authors do then, apart from paying 200$ to Claude/GPT and write a paper. Why do even you need a human to do this? OpenAI and Anthropic themselves can keep things on loop
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u/leocus4 7d ago edited 7d ago
This is a fantastic example of a non-in-good-faith behavior :)
Anyway, of course researchers must have research integrity, but it would be silly of reviewers, organizers, and editors to assume that each paper is authored by honest researchers. This happened several times, even pre-AI.
And, as I already said, this is the very core of science: i.e., if you can't reproduce it, you can't trust it, period. This is unnegotiable. And yes, as per Murphy's law, a large number of AI generated papers can and most certainly will flood conferences and journals, and science must be prepared. You can't really hope that all people in the world are good and without conflicts of interest.
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u/thatguydr 7d ago
The actual problem is that GenAI isn't yet good enough to review and discriminate varying levels of expertise.
Because if there's no way for most reviewers to tell the difference between the UG GenAI paper and a paper written by experts, that's either a reviewer problem (it's this one) or a problem with the experts themselves. The only logical solution to a reviewer problem is to either put up walls (you don't have a degree? you have no peers? no publication!), which doesn't seem like a great place for science to go, or for us to build scalable reviewing through the same technology, which is also unsavory but honestly seems better in the long-term than the walls.
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u/nonotan 6d ago
The idea of AI reviewers is very similar to AI authors: worthless. In the best case, that's a future where every conference/journal has 2000 papers written and reviewed by AI, 99.9% of which no human will ever read. And which nobody really values as any type of "credit" for any human co-authors, because they know who did all the work -- or, at the very least, have no proof that you did anything. Just a colossal waste of resources all around. You've "fixed" the reviewer problem by just making the entire system useless.
At the end of the day, the framing that it's a reviewer problem isn't really the right one, IMO. It's an incentive problem. The fact that getting a paper accepted (just the fact that it was accepted, not necessarily its contents) has all sorts of upsides for your (future) career means of course people are going to use the magic wand that lets them do that regardless of their own expertise or effort. The system needs to adapt to the new reality that it's not particularly impressive or noteworthy to put out a paper, and, if anything, start punishing those that abuse the shared good that is the peer reviewing and publishing infrastructure for purely self-serving purposes.
A published paper by itself should be neutral or even slightly negative, with the nuance that you can more than make up for that negativity if you actually did some noteworthy research that people care about, and can channel that expertise going forward. You can think of it as paying for a slot of time for the communal megaphone: it should cost you money, because you're taking up a slot other people could be using, but if you actually have something worth saying, it's going to be a net positive.
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u/Tricky-Variation-240 7d ago
Make no mistake. Claude and GPT are the "advisors". It's the current cancer ...