Just thought I'd highlight this issue to the ML community, since I recently had this problem arise and it might be useful for some. I had a coauthor who I knew was somewhat untrustworthy when it came to LLM use. This coauthor added some last-minute new references to the paper. The deadline was near, and I had a ton of other stuff to take care of. I asked them to ensure the references were correct. This coauthor confirmed that all references were correct. I trusted them. I submitted the paper. Turns out, I made a critical mistake in trusting them. All of these newly added references had hallucinations in them. The reviewer pointed out the hallucinated references and we withdrew the paper. Besides this reviewer, we had all accept scores: the scientific content of our paper was strong. Of course, this damages my reputation and the reputations of the rest of the coauthors. The takeaway is: check *all* references added to the paper, unless you are absolutely certain you can trust someone to not use LLMs. Hopefully this helps someone avoid this issue, because I worked tirelessly on this paper, in a very high pressure lab environment, and this whole situation has caused me a lot of grief. submitted by /u/treeman0469 [link] [Kommentare]
Learn GPU programming with lectures, hackathons, and working groups.
En Palacio Nacional, recibimos a Ben Horowitz, cofundador y socio general de la firma financiera Andreessen Horowitz. Coincidimos en que México es ejemplo de confianza y certeza económica. https://t.co/CAoZq76ctk
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