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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

#191

Post by Hammershaft »

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 dramatically changes the perceived cost/benefit of laziness and negligence, which is leading to much more of it.

Re: Over fifty new hallucinations in ICLR 2026 submissions

#192

Post by bigstrat2003 »

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.

Uh yeah... I would not use that tool. A tool which doesn't do its job randomly is useless.

Re: Over fifty new hallucinations in ICLR 2026 submissions

#193

Post by cratermoon »

I believe we discussed this last week, for a different vendor. https://news.ycombinator.com/item?id=46088236

Headline should be "AI vendor’s AI-generated analysis claims AI generated reviews for AI-generated papers at AI conference".

h/t to Paul Cantrell https://hachyderm.io/@inthehands/115633840133507279

Re: Over fifty new hallucinations in ICLR 2026 submissions

#195

Post by kklisura »

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.

Re: Over fifty new hallucinations in ICLR 2026 submissions

#196

Post by KHRZ »

tialaramex wrote: post #139
stdbrouw wrote: post #101

Earlier quoted context omitted.

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…

Whether in the 1970s or now, it's too often the case that a paper says "Foo and Bar are X" and cites two sources for this fact. You chase down the sources, the first one says "We weren't able to determine whether Foo is X" and never mentions Bar. The second says "Assuming Bar is X, we show that Foo is probably X too". The paper author likely believes Foo and Bar are X, it may well be that all their co-workers, if ask…

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 propagated through the citation chain.

Re: Over fifty new hallucinations in ICLR 2026 submissions

#197

Post by figassis »

andy99 wrote: post #48
CapitalistCartr wrote: post #40

Earlier quoted context omitted.

I'm an industrial electrician. A lot of poor electrical work is visible only to a fellow electrician, and sometimes only another industrial electrician. Bad technical work requires technical inspectors to criticize. Sometimes highly skilled ones.

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…

It is absolutely the reviewers job to check citations. Who else will check and what is the point of peer review then? So you’d just happily pass on shoddy work because it’s not your job? You’re reviewing both the authors work and if there were people to at needed to ensure citations were good, you’re checking their work also. This is very much the problem today with this “not my problem” mindset. If it passes review, the reviewer is also at fault. Not excuses.

Re: Over fifty new hallucinations in ICLR 2026 submissions

#198

Post by kklisura »

rectang wrote: post #135
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.

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

It's not about resisting. It's about undermining any action whatsoever.

Re: Over fifty new hallucinations in ICLR 2026 submissions

#199

Post by dataflow »

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?

I don't commonly do this and I don't know many people who do this frequently either. But it depends strongly on the code, the risks, the gains of doing so, the contributor, the project, the state of testing and how else an error would get caught (I guess this is another way of saying "it depends on the risks"), etc.

E.g. you can imagine that if I'm reviewing changes in authentication logic, I'm obviously going to put a lot more effort into validation than if I'm reviewing a container and wondering if it would be faster as a hashtable instead of a tree.

> because I want to make sure my suggestion is correct.

In this case I would just ask "have you already also tried X" which is much faster than pulling their code, implementing your suggestion, and waiting for a build and test to run.

Re: Over fifty new hallucinations in ICLR 2026 submissions

#200

Post by saimiam »

bitwarrior wrote: post #172
saimiam wrote: post #165

Just today, I was working with ChatGPT to convert Hinduism's Mimamsa School's hermeneutic principles for interpreting the Vedas into custom instructions to prevent hallucinations. I'll share the custom instructions here to protect future scientists for shooting themselves in the foot with Gen AI. --- As an LLM, use strict factual discipline. Use external knowledge but never invent, fabricate, or hallucinate. Rules: L…

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 over a blog post on the same topic.

Regardless, somehow an LLM knows things for sure - that the daytime sky on earth is generally blue and glasses of wine are never filled to the brim.

This means that it is using hermeneutics of some sort to extract "the truth as it sees it" from the data it is fed.

It could be something as trivial as "if a majority of the content I see says that the daytime Earth sky is blue, then blue it is" but that's still hermeneutics.

This custom instruction only adds (or reinforces) existing hermeneutics it already uses.

> walking around thinking you have a solution to hallucinations

I don't. I know hallucinations are not truly solvable. I shared the actual custom instruction to see if others can try it and check if it helps reduce hallucinations.

In my case, this the first custom instruction I have ever used with my chatgpt account - after adding the custom instruction, I asked chatgpt to review an ongoing conversation to confirm that its responses so far conformed to the newly added custom instructions. It clarified two claims it had earlier made.

> 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.

There are specific rules in the custom instruction forbidding fabricating stuff. Will it be foolproof? I don't think it will. Can it help? Maybe. More testing needed. Is testing this custom instruction a waste of time because LLMs already use better hermeneutics? I'd love to know so I can look elsewhere to reduce hallucinations.

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