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Over fifty new hallucinations in ICLR 2026 submissions

gptzero.me

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Re: Over fifty new hallucinations in ICLR 2026 submissions

#91

Post by QuadmasterXLII »

Ekaros wrote: post #81

One wonders why this has not been largely fully automated. If we track those citations anyway. Surely we have database of them and most of them are easily matched there. So only outliers need to be checked either as new latest papers or mistakes which should be close enough to something or real fakes. Maybe there just is no incentive for this type of activity.

It seems like the GPT zero team is automating it! Up to very recently, no one sane would cite a paper with correct title but make up random authors- and shortly, this specific signal will be goodhearted away by a “make my malpractice less detectable MCP,” so I can see why this automation is happening exactly now.

Re: Over fifty new hallucinations in ICLR 2026 submissions

#92

Post by analog31 »

Ekaros wrote: post #81

One wonders why this has not been largely fully automated. If we track those citations anyway. Surely we have database of them and most of them are easily matched there. So only outliers need to be checked either as new latest papers or mistakes which should be close enough to something or real fakes. Maybe there just is no incentive for this type of activity.

For that matter, it could be automated at the source. Let's say I'm an author. I'd gladly run a "linter" on my article that flags references that can't be tracked, and so forth. It would be no different than testing a computer program that I write before giving it to someone.

Re: Over fifty new hallucinations in ICLR 2026 submissions

#93

Post by imiric »

Forgeties79 wrote: post #63
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.

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.

Indeed. The narrative that this type of issue is entirely the responsibility of the user to fix is insulting, and blame deflection 101.

It's not like these are new issues. They're the same ones we've experienced since the introduction of these tools. And yet the focus has always been to throw more data and compute at the problem, and optimize for fancy benchmarks, instead of addressing these fundamental problems. Worse still, whenever they're brought up users are blamed for "holding it wrong", or for misunderstanding how the tools work. I don't care. An "artificial intelligence" shouldn't be plagued by these issues.

Re: Over fifty new hallucinations in ICLR 2026 submissions

#94

Post by theoldgreybeard »

Forgeties79 wrote: post #63
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.

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.

Re: Over fifty new hallucinations in ICLR 2026 submissions

#95

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

#96

Post by TimedToasts »

ghaff wrote: post #21
loloquwowndueo wrote: post #3

Earlier quoted context omitted.

I applaud your use of triple dashes to avoid automatic conversion to em dashes and being labeled an AI. Kudos!

This is a particular meme that I really don't like. I've used em-dashes routinely for years. Do I need to stop using them because various people assume they're an AI flag?

No, but you should be prepared to have people suspect you are using AI to create your responses.

C'est la vie.

The good news is that it will rectify itself and soon the output will lack even these signals.

Re: Over fifty new hallucinations in ICLR 2026 submissions

#97

Post by skobes »

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.

If LLMs produce fake citations, why would we trust LLMs to check them?

Re: Over fifty new hallucinations in ICLR 2026 submissions

#98

Post by llm_nerd »

pmontra wrote: post #61
llm_nerd wrote: post #19

Earlier quoted context omitted.

People will commonly hold LLMs as unusable because they make mistakes. So do people. Books have errors. Papers have errors. People have flawed knowledge, often degraded through a conceptual game of telephone. Exactly as you said, do precisely this to pre-LLM works. There will be an enormous number of errors with utter certainty. People keep imperfect notes. People are lazy. People sometimes even fabricate. None of th…

Fabricated citations are not errors. A pre LLM paper with fabricated citations would demonstrate will to cheat by the author. A post LLM paper with fabricated citations: same thing and if the authors attempt to defend themselves with something like, we trusted the AI, they are sloppy, probably cheaters and not very good at it.

>Fabricated citations are not errors.

Interesting that you hallucinated the word "fabricated" here where I broadly talked about errors. Humans, right? Can't trust them.

Firstly, just about every paper ever written in the history of papers has errors in it. Some small, some big. Most accidental, but some intentional. Sometimes people are sloppy keeping notes, transcribe a row, get a name wrong, do an offset by 1. Sometimes they just entirely make up data or findings. This is not remotely new. It has happened as long as we've had papers. Find an old, pre-LLM paper and go through the citations -- especially for a tosser target like this where there are tens of thousands of low effort papers submitted -- and you're going to find a lot of sloppy citations that are hard to rationalize.

Secondly, the "hallucination" is that this particular snake-oil firm couldn't find given papers in many cases (they aren't foolish enough to think that means they were fabricated. But again, they're looking to sell a tool to rubes, so the conclusion is good enough), and in others that some of the author names are wrong. Eh.

Re: Over fifty new hallucinations in ICLR 2026 submissions

#99

Post by vegabook »

grayhatter wrote: post #77
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.

I'll continue calling them hallucinations. That's a much more fitting term when you account for the reasonableness of people who believe them. There's also equally a huge breadth of different types of errors that don't pattern match well into, "made up bullshit" the same way calling them hallucinations do. There's no need to introduce that ambiguity when discussing something narrow. there's nothing wrong with anthrop…

Given that an (incompetent or even malicious) human put their names(s) to this stuff, “bullshit” is an even better and fitting anthropomorphization

Re: Over fifty new hallucinations in ICLR 2026 submissions

#100

Post by scythmic_waves »

tpoacher wrote: post #82
grayhatter wrote: post #71

Earlier quoted context omitted.

> The reviewer is not a proofreader, they are checking the rigour and relevance of the work, which does not rest heavily on all of the references in a document. I've always assumed peer review is similar to diff review. Where I'm willing to sign my name onto the work of others. If I approve a diff/pr and it takes down prod. It's just as much my fault, no? > They are also assuming good faith. I can only relate this to…

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?

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