I flagged two research papers for fake authors and both were accepted as orals

We are nowhere near AI being able to judge the quality of research (in fact, one might reasonably state that even most humans can't really judge the quality of research). Most things in society are not like math: we can't automate (via verification) our way out of noise overwhelming the signal.

Folks are willing to entirely abuse the public resource that is faithful, honest reviewing. (This is unsurprising; the abuse of the commons / public resources has been rising for a long time). There isn't a good solution other than something akin to draconian social scoring to limit access to the reviewing system.

We are rendering it irrelevant. If this is the norm for academia, I’m sympathetic to the folks looking to cut its funding.

It more looks like the breakdown of the current academic publication system, which was rotten to the core pre-AI and which internal contradictions are just accelerated by AI to the point of breakdown now.

  > because there are just so many papers at leading AI conferences

A low acceptance rate is unhealthy, especially in conferences (1 round of review). Papers just get recycled to the next conference, which, as is easy to model, creates an exponential feedback loop. It doesn't explain all the papers submitted, but it sure can explain a lot. Too much rejection is like shooting yourself in the foot.

Not to mention that it's just easy to reject works. All works are flawed, especially works that are in less mature domains. I see plenty a paper get rejected for lack of money. "Not enough experiments" is an common critique that's used inappropriately (along with the highly subjective "not novel enough" one) because it's fine to always want more but no lab has infinite funding. It is used lazily. The question shouldn't be about if your favorite benchmark is used, it should be if there isn't enough evidence to support the hypothesis or not. A mature domain where thousands of people work in it, yeah, that needs stronger evidence. A niche domain where dozens of people work in? Not as many required. Rejecting them ultimately slows down the progress of science because you require any new idea to outperform mature ideas. Ironically killing novelty as no one is going to, or even could (publish or perish), spend all the time and money to mature a niche all on their own.

AI is simply going to bury it as a useful system. What will grow from the ashes will be something much more dynamic, where verifiable data is the gold and the conclusions and associated details will persist only as the human-level translation.

I may generate slop from time to time, but I do my best to keep it to myself.

It's a sad thing. But the monetization and enshitification of journal publications over the decade or so, even prior to AI, certainly has not helped this trend.

Even with the technical debt. We have zillions of papers published, we know that most of them probably won't replicate, we don't know which ones.

The advantage of "publish or perish" is that it is based on something concrete. The system is gamed, for sure, and even more so with AI, but still, a paper which is cited a lot tend to be useful and the authors get rewarded.

Remove that metric, and for the lack of a better idea, it will just turn into a game of who has the best connections or who talks the most convincingly, I mean, even more than it is now.

This is certainly “directionally correct”, but keep in mind this is all highly uneven across fields and subfields. The people generating slop articles are mostly trying to publish big flashy things, and naturally ML research has it much worse than most other fields. There are many topics that are super important and interesting, but niche or obscure enough that no slop authors is trying to publish on them yet. So plenty of topics are still dominated by real earnest researchers doing their best, but they’re niche enough that you wouldn’t know about them unless you study that field.

Imagine being an author and paying to publish your novel. Also btw the editor is another author but has to proofread your book for free.

Many academics will publish preprints or their more popular papers on their own websites etc. It's just common sense because to academics they don't get paid a single cent by the publisher (and instead have to pay the publishers instead) and more publicity for them is always better than less.

Checking the content is of course a lot more difficult, but that doesn't magically become trivial with open-access journals: you still need to read and interpret what is being said in the paper and compare it to the claims being made in the citation. Granted, these days you could use AI for a first pass, but it's still going to be incredibly tedious work.

From my perspective, it's a clear manifestation of humanity's most pervasive failing - the one that defines every group, eventually.

    No One Anywhere Wants To Clean Their Own House.

I was forced to review 7 papers.

Now, how are these papers chosen for you?

You get to bid on which to review.

Bid on 30 papers out of 30,000.

I got none of those, and I had to review 7 papers I wasn't really competent enough to review.

As for it "being a thing": sadly yes. The number of papers has been steadily increasing over the years and the number of volunteer authors is simply not enough.

[1] https://aclrollingreview.org/incentives2025

There are already standard keys to index publications, like DOIs. Requiring a list of DOIs for citations would make a lot more sense and be somewhat feasible, but still doesn’t prevent errors in the author list given in the draft.