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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

#231

Post by auggierose »

amanaplanacanal wrote: post #213
auggierose wrote: post #60

Earlier quoted context omitted.

In short, a review has no objective value, it is just an obstacle to be gamed.

In theory, the review tries to determine if the conclusion reached actually follows from whatever data is provided. It assumes that everything is honest, it's just looking to see if there were mistakes made.

Honest or not should not make a difference, after all, the submitting author may believe themselves everything is A-OK.

The review should also determine how valuable the contribution is, not only if it has mistakes or not.

Todays reviews determine neither value nor correctness in any meaningful way. And how could they, actually? That is why I review papers only to the extent that I understand them, and I clearly delineate my line of understanding. And I don't review papers that I am not interested in reading. I once got a paper to review that actually pointed out a mistake in one of my previous papers, and then proposed a different solution. They correctly identified the mistake, but I could not verify if their solution worked or not, that would have taken me several weeks to understand. I gave a report along these lines, and the person who gave me the review said I should say more about their solution, but I could not. So my review was not actually used. The paper was accepted, which is fine, but I am sure none of the other reviewers actually knows if it is correct.

Now, this was a case where I was an absolute expert. Which is far from the usual situation for a reviewer, even though many reviewers give themselves the highest mark for expertise when they just should not.

Re: Over fifty new hallucinations in ICLR 2026 submissions

#232

Post by mk89 »

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.

> we are tacitly endorsing it.

We are, in fact, not tacitly but openly endorsing this, due to this AI everywhere madness. I am so looking forward to when some genius in some banks starts to use it to simplify code and suddenly I have 100000000 € on my bank account. :)

Re: Over fifty new hallucinations in ICLR 2026 submissions

#233

Post by sneak »

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.

> it is a discourse used solely for the purpose of not doing anything and not addressing anything about the underlying problem

Solely? Oh brother.

In reality it’s the complete opposite. It exists to highlight the actual source of the problem, as both industries/practitioners using AI professionally and safely, and communities with very high rates of gun ownership and exceptionally low rates of gun violence exist.

It isn’t the tools. It’s the social circumstances of the people with access to the tools. That’s the point. The tools are inanimate. You can use them well or use them badly. The existence of the tools does not make humans act badly.

Re: Over fifty new hallucinations in ICLR 2026 submissions

#234

Post by lesam »

scythmic_waves wrote: post #100
tpoacher wrote: post #82

Earlier quoted context omitted.

This is true, but here the equivalent situation is someone using a greek question mark (";") instead of a semicolon (";"), and you as a code reviewer are only expected to review the code visually and are not provided the resources required to compile the code on your local machine to see the compiler fail. Yes in theory you can go through every semicolon to check if it's not actually a greek question mark; but one as…

> as a code reviewer [you] are only expected to review the code visually and are not provided the resources required to compile the code on your local machine to see the compiler fail. As a PR reviewer I frequently pull down the code and run it. Especially if I'm suggesting changes because I want to make sure my suggestion is correct. Do other PR reviewers not do this?

If there’s anything I would want to run to verify, I ask the author to add a unit test. Generally, the existing CI test + new tests in the PR having run successfully is enough. I might pull and run it if I am not sure whether a particular edge case is handled.

Reviewers wanting to pull and run many PRs makes me think your automated tests need improvement.

Re: Over fifty new hallucinations in ICLR 2026 submissions

#235

Post by semi-extrinsic »

stdbrouw wrote: post #101
andy99 wrote: post #48

Earlier quoted context omitted.

I’ve reviewed a lot of papers, I don’t consider it the reviewers responsibility to manually verify all citations are real. If there was an unusual citation that was relied on heavily for the basis of the work, one would expect it to be checked. Things like broad prior work, you’d just assume it’s part of background. The reviewer is not a proofreader, they are checking the rigour and relevance of the work, which does…

The idea that references in a scientific paper should be plentiful but aren't really that important, is a consequence of a previous technological revolution: the internet. You'll find a lot of papers from, say, the '70s, with a grand total of maybe 10 references, all of them to crucial prior work, and if those references don't say what the author claims they should say (e.g. that the particular method that is employe…

It's also a consequence of the sheer number of building blocks which are involved in modern science.

In the methods section, it's very common to say "We employ method barfoo [1] as implemented in library libbar [2], with the specific variant widget due to Smith et al. [3] and the gobbledygook renormalization [4,5]. The feoozbar is solved with geometric multigrid [6]. Data is analyzed using the froiznok method [7] from the boolbool library [8]." There goes 8, now you have 2 citations left for the introduction.

Re: Over fifty new hallucinations in ICLR 2026 submissions

#236

Post by sansseriff »

bossyTeacher wrote: post #220
KHRZ wrote: post #196

Earlier quoted context omitted.

LLMs can actually make up for their negative contributions. They could go through all the references of all papers and verify them, assuming someone would also look into what gets flagged for that final seal of disapproval. But this would be more powerfull with an open knowledge base where all papers and citation verifications were registered, so that all the effort put into verification could be reused, and errors p…

>LLMs can actually make up for their negative contributions. They could go through all the references of all papers and verify them, They will just hallucinate their existence. I have tried this before

I don’t see why this would be the case with proper tool calling and context management. If you tell a model with blank context ‘you are an extremely rigorous reviewer searching for fake citations in a possibly compromised text’ then it will find errors.

It’s this weird situation where getting agents to act against other agents is more effective than trying to convince a working agent that it’s made a mistake. Perhaps because these things model the cognitive dissonance and stubbornness of humans?

Re: Over fifty new hallucinations in ICLR 2026 submissions

#237

Post by somehnguy »

only-one1701 wrote: post #105
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.

Absolutely brutal case of engineering brain here. Real "guns don't kill people, people kill people" stuff.

Your second statement is correct. What about it makes it “engineering brain”?

Re: Over fifty new hallucinations in ICLR 2026 submissions

#238

Post by bitwarrior »

saimiam wrote: post #200
bitwarrior wrote: post #172

Earlier quoted context omitted.

Are you sure this even works? My understanding is that hallucinations are a result of physics and the algorithms at play. The LLM always needs to guess what the next word will be. There is never a point where there is a word that is 100% likely to occur next. The LLM doesn't know what "reliable" sources are, or "real knowledge". Everything it has is user text, there is nothing it knows that isn't user text. It doesn'…

> The LLM doesn't know what "reliable" sources are, or "real knowledge". Everything it has is user text, there is nothing it knows that isn't user text. It doesn't know what "verified" knowledge is. It doesn't know what "fake data" is, it simply has its model. Is it the case that all content used to train a model is strictly equal? Genuinely asking since I'd imagine a peer reviewed paper would be given precedence ove…

I think the salient point here is that you, as a user, have zero power to reduce hallucinations. This is a problem baked into the math, the algorithm. And, it is not a problem that can be solved because the algorithm requires fuzziness to guess what a next word will be.

Re: Over fifty new hallucinations in ICLR 2026 submissions

#239

Post by mannanj »

chistev wrote: post #217

Last month, I was listening to the Joe Rogan Experience episode with guest Avi Loeb, who is a theoretical physicist and professor at Harvard University. He complained about the disturbingly increasing rate at which his students are submitting academic papers referencing non-existent scientific literature that were so clearly hallucinated by Large Language Models (LLMs). They never even bothered to confirm their refer…

Isn't this an underlying symptom of lack of accountability of our greater leadership? They do these things, they act like criminals and thieves, and so the people who follow them get shown examples that it's OK while being told to do otherwise.

"Show bad examples then hit you on the wrist for following my behavior" is like bad parenting.

Re: Over fifty new hallucinations in ICLR 2026 submissions

#240

Post by rectang »

codywashere wrote: post #146
rectang wrote: post #135

Earlier quoted context omitted.

“X isn’t the problem, people are the problem.” — the age-old cry of industry resisting regulation.

what regulation are you advocating for here?

I’m not advocating, I’m making a high-level observation: Industry forever pushes for nil regulation and blames bad actors for damaging use.

But we always have some regulation in the end. Even if certain firearms are legal to own, howitzers are not — although it still takes a “bad actor” to rain down death on City Hall.

The same dynamic is at play with LLMs: “Don’t regulate us, punish bad actors! If you still have a problem, punish them harder!” Well yes, we will punish bad actors, but we will also go through a negotiation of how heavily to constrain the use of your technology.

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