Over fifty new hallucinations in ICLR 2026 submissions

If you look at their examples in the "Defining Hallucitations" section, I'd say those could be 100% human errors. Shortening authors' names, leaving out authors, misattributing authors, misspelling or misremembering the paper title (or having an old preprint-title, as titles do change) are all things that I would fully expect to happen to anyone in any field were things get ever got published. Modern tools have made the citation process more comfortable, but if you go back to the old days, you'd probably find those kinds of errors everywhere. If you look at the full list of "hallucinations" they claim to have discovered, the only ones I'd not immediately blame on human screwups are the ones where a title and the authors got zero matches for existing papers/people. If you really want to do this kind of analysis correctly, you'd have to match the claim of the text and verify it with the cited article. Because I think it would be even more dangerous if you can get claims accepted by simply quoting an existing paper correctly, while completely ignoring its content (which would have worked here).

> 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?

>Work which gives itself false authority by claiming to cite works that simply do not exist is the main concern surely?

You'd think so, but apparently it isn't for these folks. On the other hand, saying "we've found 50 hallucinations in scientific papers" generates a lot more clicks than "we've found 50 common citation mistakes that people make all the time"

There are other issues. In January they claimed that a US health report contained "fabricated" and "AI generated" citations with the headline being a claim from a Cigna Group report. Their claim it's fabricated is based on nothing more than the URL now being a redirect of the type common in corporate website reorgs.

I did some checking and found the report does exist, but the citation is still not quite correct. Then I discovered someone is running some LLM based citation checker already, which already fact checked this claim and did a correct writeup that seems a lot better than what this GPTZero tool does.

https://checkplease.neocities.org/maha/html/17-loneliness-73...

The mistakes in the citation are the sort of mistake that could have been made by both a human or an AI, really. The visualization in the report is confusing and does contain the 73% number (rounded up), but it's unclear how to interpret the numbers because it's some sort of "vitality index" and not what you'd expect based on how it's introduced. At first glance I actually mis-interpreted it the same way the report does, so it's hard to view this is as clear evidence of AI misuse. Yet the GPTZero folks do make very strong claims based on nothing more than a URL scraper script.