Given that many of these detections are being made from references, I don't understand why we're not using automatic citation checkers.

Just ask authors to submit their bib file so we don't need to do OCR on the PDF. Flag the unknown citations and ask reviewers to verify their existence. Then contact authors and ban if they can't produce the cited work.

This is low hanging fruit here!

Detecting slop where the authors vet citations is much harder. The big problem with all the review rules is they have no teeth. If it were up to me we'd review in the open, or at least like ICLR. Publish the list of known bad actors and let is look at the network. The current system is too protective of egregious errors like plagiarism. Authors can get detected in one conference, pull, and submit to another, rolling the dice. We can't allow that to happen and we should discourage people from associating with these conartists.

AI is certainly a problem in the world of science review, but it's far from the only one and I'm not even convinced it's the biggest. The biggest is just that reviewers are lazy and/or not qualified to review the works they're assigned. It takes at least an hour to properly review a paper in your niche, much more when it's outside. We're over worked as is, with 5+ works to review, not to mention all the time we got to spend reworking our own works that were rejected due to the slot machine. We could do much better if we dropped this notion of conference/journal prestige and focused on the quality of the works and reviews.

Addressing those issues also addresses the AI issues because, frankly, *it doesn't matter if the whole work was done by AI, what matters is if the work is real.*