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Over fifty new hallucinations in ICLR 2026 submissions

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Re: Over fifty new hallucinations in ICLR 2026 submissions

#221

Post by jordanpg »

Muller20 wrote: post #210
jordanpg wrote: post #148

Does anyone know, from a technical standpoint, why are citations such a problem for LLMs? I realize things are probably (much) more complicated than I realize, but programmatically, unlike arbitrary text, citations are generally strings with a well-defined format. There are literally "specs" for citation formats in various academic, legal, and scientific fields. So, naively, one way to mitigate these hallucinations w…

In general, a citation is something that needs to be precise, while LLMs are very good at generating some generic high probability text not grounded in reality. Sure, you could implement a custom fix for the very specific problem of citations, but you cannot solve all kinds of hallucinations. After all, if you could develop a manual solution you wouldn't use an LLM. There are some mitigations that are used such as RA…

My point is that citations are constantly making headlines, yet at least at first glance, seems like an eminently solvable problem.

Re: Over fifty new hallucinations in ICLR 2026 submissions

#222

Post by pama »

Given how many errors I have seen in my years as a reviewer from well before the time of AI tools, it would be very surprizing if 99.75% of the ~20,000 submitted papers to didnt have such errors. If the 300 sample they used was truly random, then 50 of 300 sounds about right compared to errors I had seen starting in the 90s when people manually curated bintex entries. It is the author’s and editor’s job, not the reviewer’s, to fix the citations.

Re: Over fifty new hallucinations in ICLR 2026 submissions

#223

Post by [deleted] »

theoldgreybeard wrote: post #94
Forgeties79 wrote: post #63

Earlier quoted context omitted.

If my calculator gives me the wrong number 20% of the time yeah I should’ve identified the problem, but ideally, that wouldn’t have been sold to me as a functioning calculator in the first place.

If it was a well understood property of calculators that they gave incorrect answers randomly then you need to adjust the way you use the tool accordingly.

[deleted]

Re: Over fifty new hallucinations in ICLR 2026 submissions

#224

Post by [deleted] »

theoldgreybeard wrote: post #16

If a carpenter builds a crappy shelf “because” his power tools are not calibrated correctly - that’s a crappy carpenter, not a crappy tool. If a scientist uses an LLM to write a paper with fabricated citations - that’s a crappy scientist. AI is not the problem, laziness and negligence is. There needs to be serious social consequences to this kind of thing, otherwise we are tacitly endorsing it.

[deleted]

Re: Over fifty new hallucinations in ICLR 2026 submissions

#225

Post by dawnerd »

watwut wrote: post #127
MarkusQ wrote: post #68

This is as much a failing of "peer review" as anything. Importantly, it is an intrinsic failure, which won't go away even if LLMs were to go away completely. Peer review doesn't catch errors. Acting as if it does, and thus assuming the fact of publication (and where it was published) are indicators of veracity is simply unfounded. We need to go back to the food fight system where everyone publishes whatever they want…

Peer review was never supposed to check every single detail and every single citation. They are not proof readers. They are not even really supposed to agree or disagree with your results. They should check the soundness of a method, general structure of a paper, that sort of thing. They do catch some errors, but the expectation is not to do another independent study or something. Passed peer review is the first basi…

It would be crazy to expect them to verify every author is correct on a citation and to cross verify everything. There’s tooling that could be built for that and kinda wild isn’t a thing that’s run on paper submission.

Re: Over fifty new hallucinations in ICLR 2026 submissions

#226

Post by Yoofie »

kklisura wrote: post #195
theoldgreybeard wrote: post #16

If a carpenter builds a crappy shelf “because” his power tools are not calibrated correctly - that’s a crappy carpenter, not a crappy tool. If a scientist uses an LLM to write a paper with fabricated citations - that’s a crappy scientist. AI is not the problem, laziness and negligence is. There needs to be serious social consequences to this kind of thing, otherwise we are tacitly endorsing it.

> AI is not the problem, laziness and negligence is This reminds me about discourse about a gun problem in US, "guns don't kill people, people kill people", etc - it is a discourse used solely for the purpose of not doing anything and not addressing anything about the underlying problem. So no, you're wrong - AI IS THE PROBLEM.

No, the OP is right in this case. Did you read TFA? It was "peer reviewed".

> Worryingly, each of these submissions has already been reviewed by 3-5 peer experts, most of whom missed the fake citation(s). This failure suggests that some of these papers might have been accepted by ICLR without any intervention. Some had average ratings of 8/10, meaning they would almost certainly have been published.

If the peer reviewers can't be bothered to do the basics, then there is literally no point to peer review, which is fully independent of the author who uses or doesn't use AI tools.

Re: Over fifty new hallucinations in ICLR 2026 submissions

#227

Post by hnfong »

ls612 wrote: post #150
jqpabc123 wrote: post #2

The legal system has a word to describe AI "slop" --- it is called "negligence". And as the remedy starts being applied (aka "liability"), the enthusiasm for AI will start to wane. I wouldn't be surprised if some businesses ban the use of AI --- starting with law firms.

The legal system has a word to describe software bugs --- it is called "negligence". And as the remedy starts being applied (aka "liability"), the enthusiasm for software will start to wane. What if anything do you think is wrong with my analogy? I doubt most people here support strict liability for bugs in code.

I don't even think GP knows what negligence is.

Generally the law allows people to make mistakes, as long as a reasonable level of care is taken to avoid them (and also you can get away with carelessness if you don't owe any duty of care to the party). The law regarding what level of care is needed to verify genAI output is probably not very well defined, but it definitely isn't going to be strict liability.

The emotionally-driven hate for AI, in a tech-centric forum even, to the extent that so many commenters seem to be off-balance in their rational thinking, is kinda wild to me.

Re: Over fifty new hallucinations in ICLR 2026 submissions

#228

Post by garden_hermit »

grayhatter wrote: post #151
pron wrote: post #115

Earlier quoted context omitted.

That is not, cannot be, and shouldn't be, the bar for peer review. There are two major differences between it and code review: 1. A patch is self-contained and applies to a codebase you have just as much access to as the author. A paper, on the other hand, is just the tip of the iceberg of research work, especially if there is some experiment or data collection involved. The reviewer does not have access to, say, vid…

> That is not, cannot be, and shouldn't be, the bar for peer review. Given the repeatability crisis I keep reading about, maybe something should change? > 2. The software is also self-contained. That's "prodcution". But a scientific paper does not necessarily aim to represent scientific consensus, but a finding by a particular team of researchers. If a paper's conclusions are wrong, it's expected that it will be refu…

> Given the repeatability crisis I keep reading about, maybe something should change?

The replication crisis — assuming that it is actually a crisis — is not really solvable with peer review. If I'm reviewing a psychology paper presenting the results of an experiment, I am not able to re-conduct the entire experiment as presented by the authors, which would require completely changing my lab, recruiting and paying participants, and training students & staff.

Even if I did this, and came to a different result than the original paper, what does it mean? Maybe I did something wrong in the replication, maybe the result is only valid for certain populations, maybe inherent statistical uncertainty means we just get different results.

Again, the replication crisis — such that it exists — is not the result of peer review.

Re: Over fifty new hallucinations in ICLR 2026 submissions

#229

Post by JTbane »

michaelcampbell wrote: post #70

After an interview with Cory Doctorow I saw recently, I'm going to stop anthropomorphizing these things by calling them "hallucinations". They're computers, so these incidents are just simply Errors.

Nah it's very apt and perfectly encapsulates output that looks plausible but is in fact factually incorrect or made up.

Re: Over fifty new hallucinations in ICLR 2026 submissions

#230

Post by dawnerd »

dclowd9901 wrote: post #28

To me, this is exactly what LLMs are good for. It would be exhausting double checking for valid citations in a research paper. Fuzzy comparison and rote lookup seem primed for usage with LLMs. Writing academic papers is exactly the _wrong_ usage for LLMs. So here we have a clear cut case for their usage and a clear cut case for their avoidance.

Shouldn’t need an llm to check. It’s just a list of authors. I wouldn’t trust an llm on this, and even if they were perfect that’s a lot of resource use just to do something traditional code could do.
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