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GPTZero finds 100 new hallucinations in NeurIPS 2025 accepted papers

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Re: GPTZero finds 100 new hallucinations in NeurIPS 2025 accepted papers

#81

Post by blackbear_ »

armcat wrote: post #57

This is awful but hardly surprising. Someone mentioned reproducible code with the papers - but there is a high likelihood of the code being partially or fully AI generated as well. I.e. AI generated hypothesis -> AI produces code to implement and execute the hypothesis -> AI generates paper based on the hypothesis and the code. Also: there were 15 000 submissions that were rejected at NeurIPS; it would be very intere…

Whether the code is AI generated or not is not important, what matters is that it really works.

Sharing code enables others to validate the method on a different dataset.

Even before LLMs came around there were lots of methods that looked good on paper but turned out not to work outside of accepted benchmarks

Re: GPTZero finds 100 new hallucinations in NeurIPS 2025 accepted papers

#82

Post by StableAlkyne »

cogman10 wrote: post #2

Yuck, this is going to really harm scientific research. There is already a problem with papers falsifying data/samples/etc, LLMs being able to put out plausible papers is just going to make it worse. On the bright side, maybe this will get the scientific community and science journalists to finally take reproducibility more seriously. I'd love to see future reporting that instead of saying "Research finds amazing che…

> I'd love to see future reporting that instead of saying "Research finds amazing chemical x which does y" you see "Researcher reproduces amazing results for chemical x which does y. First discovered by z".

Most people (that I talk to, at least) in science agree that there's a reproducibility crisis. The challenge is there really isn't a good way to incentivize that work.

Fundamentally (unless you're independent wealthy and funding your own work), you have to measure productivity somehow, whether you're at a university, government lab, or the private sector. That turns out to be very hard to do.

If you measure raw number of papers (more common in developing countries and low-tier universities), you incentivize a flood of junk. Some of it is good, but there is such a tidal wave of shit that most people write off your work as a heuristic based on the other people in your cohort.

So, instead it's more common to try to incorporate how "good" a paper is, to reward people with a high quantity of "good" papers. That's quantifying something subjective though, so you might try to use something like citation count as a proxy: if a work is impactful, usually it gets cited a lot. Eventually you may arrive at something like the H-index, which is defined as "The highest number H you can pick, where H is the number of papers you have written with H citations." Now, the trouble with this method is people won't want to "waste" their time on incremental work.

And that's the struggle here; even if we funded and rewarded people for reproducing results, they will always be bumping up the citation count of the original discoverer. But it's worse than that, because literally nobody is going to cite your work. In 10 years, they just see the original paper, a few citing works reproducing it, and to save time they'll just cite the original paper only.

There's clearly a problem with how we incentivize scientific work. And clearly we want to be in a world where people test reproducibility. However, it's very very hard to get there when one's prestige and livelihood is directly tied to discovery rather than reproducibility.

Re: GPTZero finds 100 new hallucinations in NeurIPS 2025 accepted papers

#83

Post by yepyeaisntityea »

No surprises. Machine learning has, at least since 2012, been the go-to field for scammers and grifters. Machine learning, and technology in general, is basically a few real ideas, a small number of honest hard workers, and then millions of fad chasers and scammers.

Re: GPTZero finds 100 new hallucinations in NeurIPS 2025 accepted papers

#85

Post by paulmist »

emil-lp wrote: post #26
bonsai_spool wrote: post #14

This suggests that nobody was screening this papers in the first place—so is it actually significant that people are using LLMs in a setting without meaningful oversight? These clearly aren't being peer-reviewed, so there's no natural check on LLM usage (which is different than what we see in work published in journals).

As one who reviews 20+ papers per year, we don't have time to verify each reference. We verify: is the stuff correct, and is it worthy of publication (in the given venue) given that it is correct. There is still some trust in the authors to not submit made-up-stuff, albeit it is diminishing.

I'm surprised the conference doesn't provide tooling to validate all references automatically.

Re: GPTZero finds 100 new hallucinations in NeurIPS 2025 accepted papers

#86

Post by pessimizer »

wing-_-nuts wrote: post #68
empath75 wrote: post #50

Earlier quoted context omitted.

I think a _single_ instance of an LLM hallucination should be enough to retract the whole paper and ban further submissions.

I dunno about banning them, humans without LLMs make mistakes all the time, but I would definitely place them under much harder scrutiny in the future.

Hallucinations aren't mistakes, they're fabrications. The two are probably referred to by the same word in some languages.

Institutions can choose an arbitrary approach to mistakes; maybe they don't mind a lot of them because they want to take risks and be on the bleeding edge. But any flexible attitude towards fabrications is simply corruption. The connected in-crowd will get mercy and the outgroup will get the hammer. Anybody criticizing the differential treatment will be accused of supporting the outgroup fraudsters.

Re: GPTZero finds 100 new hallucinations in NeurIPS 2025 accepted papers

#87

Post by tasuki »

smallpipe wrote: post #13

Could you run a similar analysis for pre-2020 papers? It'd be interesting to know how prevalent making up sources was before LLMs.

Also, it'd be interesting how many pre-2020 papers their "AI detector" marks as AI-generated. I distrust LLMs somewhat, but I distrust AI detectors even more.

Re: GPTZero finds 100 new hallucinations in NeurIPS 2025 accepted papers

#88

Post by warkdarrior »

StableAlkyne wrote: post #82
cogman10 wrote: post #2

Yuck, this is going to really harm scientific research. There is already a problem with papers falsifying data/samples/etc, LLMs being able to put out plausible papers is just going to make it worse. On the bright side, maybe this will get the scientific community and science journalists to finally take reproducibility more seriously. I'd love to see future reporting that instead of saying "Research finds amazing che…

> I'd love to see future reporting that instead of saying "Research finds amazing chemical x which does y" you see "Researcher reproduces amazing results for chemical x which does y. First discovered by z". Most people (that I talk to, at least) in science agree that there's a reproducibility crisis. The challenge is there really isn't a good way to incentivize that work. Fundamentally (unless you're independent weal…

> If you measure raw number of papers (more common in developing countries and low-tier universities), you incentivize a flood of junk.

This is exactly what rewarding replication papers (that reproduce and confirm an existing paper) will lead to.

Re: GPTZero finds 100 new hallucinations in NeurIPS 2025 accepted papers

#89

Post by gcr »

pessimizer wrote: post #76
gcr wrote: post #58

Earlier quoted context omitted.

Going through a retraction and blacklisting process is also a lot of work -- collecting evidence, giving authors a chance to respond and mediate discussion, etc. Labor is the bottleneck. There aren't enough academics who volunteer to help organize conferences. (If a reader of this comment is qualified to review papers and wants to step up to the plate and help do some work in this area, please email the program chair…

That's exactly why the inclusion of a hallucinated reference is actually a blessing. Instead going back and forth with the fraudster, just tell them to find the paper. If they can't, case closed. Massive amount of time and money saved.

Isn't telling them to find the paper just "going back and forth with a fraudster"?

One "simple" way of doing this would be to automate it. Have authors step through a lint step when their camera-ready paper is uploaded. Authors would be asked to confirm each reference and link it to a google scholar citation. Maybe the easy references could be auto-populated. Non-public references could be resolved by uploading a signed statement or something.

There's no current way of using this metadata, but it could be nice for future systems.

Even the Scholar team within Google is woefully understaffed.

My gut tells me that it's probably more efficient to just drag authors who do this into some public execution or twitter mob after-the-fact. CVPR does this every so often for authors who submit the same paper to multiple venues. You don't need a lot of samples for deterrence to take effect. That's kind of what this article is doing, in a sense.

Re: GPTZero finds 100 new hallucinations in NeurIPS 2025 accepted papers

#90

Post by derf_ »

gcr wrote: post #28

NeurIPS leadership doesn’t think hallucinated references are necessarily disqualifying; see the full article from Fortune for a statement from them: https://archive.ph/yizHN > When reached for comment, the NeurIPS board shared the following statement: “The usage of LLMs in papers at AI conferences is rapidly evolving, and NeurIPS is actively monitoring developments. In previous years, we piloted policies regarding th…

This will continue to happen as long as it is effectively unpunished. Even retracting the paper would do little good, as odds are it would not have been written if the author could not have used an LLM, so they are no worse off for having tried. Scientific publications are mostly a numbers game at this point. It is just one more example of a situation where behaving badly is much cheaper than policing bad behavior, and until incentives are changed to account for that, it will only get worse.
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