Over fifty new hallucinations in ICLR 2026 submissions

Either op mistakes the hallucinated citations for the authors (most likely, although there's almost no "middle eastern names" among them) Or he checked some that do have the names listed (I found 4, all had either Chinese names or "western" names) Anyway the great majority of papers (good or bad) I've seen have Indian or Chinese names attached, attributing bad papers to brown people having an inferior culture is just blatantly racist

Yeah WTF? Both authors and reviewers are hidden. Is this comment just an attempt to whip up racist fervor?

I think it's an interesting question. Whether or not it can be discussed well here isn't so obvious.

You don't just accept the review as-is, though; You prompt it to be a skeptic and find a handful of specific examples of claims that are worth extra attention from a qualified human.

Unfortunately, this probably results in lazy humans _only_ reading the automated flagged areas critically and neglecting everything else, but hey—at least it might keep a little more garbage out?

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 employed is valid), then chances are that the current paper is weaker than it seems, or even invalid, and so it is extremely important to check those references.

Then the internet came along, scientists started padding their work with easily found but barely relevant references and journal editors started requiring that even "the earth is round" should be well-referenced. The result is that peer reviewers feel that asking them to check the references is akin to asking them to do a spell check. Fair enough, I agree, I usually can't be bothered to do many or any citation checks when I am asked to do peer review, but it's good to remember that this in itself is an indication of a perverted system, which we just all ignored -- at our peril -- until LLM hallucinations upset the status quo.

I think the root problem is that everyone involved, from authors to reviewers to publishers, know that 99.999% of papers are completely of no consequence, just empty calories with the sole purpose of padding quotas for all involved, and thus are not going to put in the effort as if.

This is systemic, and unlikely to change anytime soon. There have been remedies proposed (e.g. limits on how many papers an author can publish per year, let's say 4 to be generous), but they are unlikely to gain traction as thoug most would agree onbenefits, all involved in the system would stand to lose short term.

> 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 code review, but assuming good faith means you assume they didn't try to introduce a bug by adding this dependency. But I would should still check to make sure this new dep isn't some typosquatted package. That's the rigor I'm responsible for.

As a reviewer I at least skimmed the papers for every reference in every paper that I review. If it isn't useful to furthering the point of the paper then my feedback is to remove the reference. Adding a bunch of junk because it is broadly related in a giant background section is a waste of everyone's time and should be removed. Most of the time you are mostly aware of the papers being cited anyway because that is the whole point of reviewing in your area of expertise.

> I don’t consider it the reviewers responsibility to manually verify all citations are real

I guess this explains all those times over the years where I follow a citation from a paper and discover it doesn’t support what the first paper claimed.

Agreed. I used to review lots of submissions for IEEE and similar conferences, and didn't consider it my job to verify every reference. No one did, unless the use of the reference triggered an "I can't believe it said that" reaction. Of course, back then, there wasn't a giant plagiarism machine known to fabricate references, so if tools can find fake references easily the tools should be used.

>I don’t consider it the reviewers responsibility to manually verify all citations are real.

Doesn't this sound like something that could be automated?

for paper_name in citations... do a web search for it, see if it there's a page in the results with that title.

That would at least give you "a paper with this name exists".

I agree with you (I have reviewed papers in the past), however, made-up citations are a "signal". Why would the authors do that? If they made it up, most likely they haven't really read that prior work. If they haven't, have they really done proper due dilligence on their research? Are they just trying to "beef up" their paper with citations to unfairly build up credibility?

I am not an electrician, but when I did projects, I did a lot of research before deciding to hire someone and then I was extremely confused when everyone was proposing doing it slightly differently.

A lot of them proposed ways that seem to violate the code, like running flex tubing beyond the allowed length or amount of turns.

Another example would be people not accounting for needing fireproof covers if they’re installing recessed, lighting in between dwelling in certain cities…

Heck, most people don’t actually even get the permit. They just do the unpermitted work.

A couple had just moved in a house and called me to replace the ceiling fan in the living room. I pulled the flush mount cover down to start unhooking the wire nuts and noticed RG58 (coax cable). Someone had used the center conductor as the hot wire! I ended up running 12/2 Romex from the switch. There was no way in hell I could have hooked it back up the way it was. This is just one example I've come across.

Current state AI doesn’t have hands. How can it possibly be better at installing electrics than anyone?

Your post reads like AI precisely because while the grammar is fine, it lacks context - like someone prompted “reply that AI is better than average”.

Peer reviewers can also use AI tools, which will hallucinate a "this seems fine" response.

If AI fraud is good at avoiding detection via peer review that doesn’t mean peer review is useless.

If your unit tests don’t catch all errors it doesn’t mean unit tests are useless.

I think this is a bit unfair. The carpenters are (1) living in world where there’s an extreme focus on delivering as quicklyas possible, (2) being presented with a tool which is promised by prominent figures to be amazing, and (3) the tool is given at a low cost due to being subsidized.

And yet, we’re not supposed to criticize the tool or its makers? Clearly there’s more problems in this world than «lazy carpenters»?

At the very least, authors who have been caught publishing proven fabrications should be barred by those journals from ever publishing in them again. Mind you, this is regardless of whether or not an LLM was involved.

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.

> Modern tools have made the citation process more comfortable,

That also makes some of those errors easier. A bad auto-import of paper metadata can silently screw up some of the publication details, and replacing an early preprint with the peer-reviewed article of record takes annoying manual intervention.

I mean, if you’re able to take the citation, find the cited work, and definitively state ‘looks like they got the title wrong’ or ‘they attributed the paper to the wrong authors’, that doesn’t sound like what people usually mean when they say a ‘hallucinated’ citation. Work that is lazily or poorly cited but nonetheless attempts to cite real work is not the problem. Work which gives itself false authority by claiming to cite works that simply do not exist is the main concern surely?

Further, if I use AI-written citations to back some claim or fact, what are the actual claims or facts based on? These started happening in law because someone writes the text and then wishes there was a source that was relevant and actually supportive of their claim. But if someone puts in the labor to check your real/extant sources, there's nothing backing it (e.g. MAHA report).

>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.

The issue here is that many of the ‘hallucinations’ this article cites aren’t ’papers which do not exist’. They are incorrect author attributions, publication dates, or titles.

>It's not easy to hallucinate papers out of whole cloth, but LLMs can easily and confidently do it, quote paragraphs that don't exist, and do it tirelessly and at a pace unmatched by humans.

But no one is claiming these papers were hallucinated whole, so I don't see how that's relevant. This study -- notably to sell an "AI detector", which is largely a laughable snake-oil field -- looked purely at the accuracy of citations[1] among a very large set of citations. Errors in papers are not remotely uncommon, and finding some errors is...exactly what one would expect. As the GP said, do the same study on pre-LLM papers and you'll find an enormous number of incorrect if not fabricated citations. Peer review has always been an illusion of auditing.

1 - Which is such a weird thing to sell an "AI detection" tool. Clearly it was mostly manual given that they somehow only managed to check a tiny subset of the papers, so in all likelihood was some guy going through citations and checking them on Google Search.

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The problem isn't only papers it's that the world of academic computer science coalesced around conference submissions instead of journal submissions. This isn't new and was an issue 30 years ago when I was in grad school. It makes the work of conference organizes the little block holding up the entire system.