1: https://hn.algolia.com/?dateRange=all&page=0&prefix=true&que...

There are also rings of reviewer fraud going on where groups of people in these niche areas all get assigned their own papers and recommend acceptance and in many cases the AC is part of this as well. Am not saying this is common but it is occurring.

It feels as if every layer of society is in maximum extraction mode and this is just a single example. No one is spending time to carefully and deeply review a paper because they care and they feel on principal that’s the right thing to do. People did used to do this.

But what's the proof? How do you prove (with any rigor) a given text is AI-generated?

h/t to Paul Cantrell https://hachyderm.io/@inthehands/115633840133507279

21%...? Am I reading it right? I bet no one expected it's so low when they clicked this title.

ok of course the human reviewers could still use AI here but then so could the authors, ad infinitum..

I’ve been to CVPR, NeurIPS and AGI conferences over the last decade and they used to be where progress in AI was displayed.

No longer. Progress is all in your github and increasingly only dominated by the “new” AI companies (Deepmind, OAI, Anthropic, Alibaba etc…)

No major landscape shifting breakthroughs have come out of CSAIL, BAIR, NYU, TuM etc in ~the last 5 years.

I’d expect this will continue as the only thing that matters at this point is architecture data and compute.

The problem is the entire article is made up. Sure, the author can trace client-side traffic, but the vast majority of start-ups would be making calls to LLMs in their backend (a sequence diagram in the article even points this out!!), where it would be untraceable. There is certainly no way the author can make a broad statement that he knows what's happening across hundreds of startups.

Yet lots of comments just taking these conclusions at face value. Worse, when other commenters and myself pointed out the blatant impossibility of the author's conclusion, got some responses just rehashing how the author said they "traced network traffic", even though that doesn't make any sense as they wouldn't have access to backends of these companies.

In general, what bothers me the most is the lack of transparency from researchers that use LLMs. Like, give me the text and explicitly mention that you used LLM for it. Even better, if one links the prompt history.

The lack of transparency causes greater damage than the using LLM for generating text. Otherwise, we will keep chasing the perfect AI detector which to me seems to be pointless.

That is a tad bit too much...

For the record I actually like the AI writing style. It's a huge improvement in readability over most academic writing I used to come across.

On the one hand (and the most important thing, IMO) it's really bad to judge people on the basis of "AI detectors", especially when this can have an impact on their career. It's also used in education, and that sucks even more. AI detectors have bad rates, can't detect concentrated efforts (i.e. finetunes will trick every detector out there, I've tried) can have insane false positives (the first ones that got to "market" were rating the declaration of independence as 100% AI written), and at best they'll only catch the most vanilla outputs.

On the other hand, working with these things, and just being online is impossible to say that I don't see the signs everywhere. Vanilla LLMs fixate on some language patterns, and once you notice them, you see them everywhere. It's not just x; it was truly y. Followed by one supportive point, the second supportive point and the third supportive point. And so on. Coupled with that vague enough overview style, and not much depth, it's really easy to call blatant generations as you see them. It's like everyone writes in linkedin infused mania episodes now. It's getting old fast.

So I feel for the people who got slop reviews. I'd be furious. Especially when its faux pas to call it out.

I also feel for the reviewers that maybe got caught in this mess for merely "spell checking" their (hopefully) human written reviews.

I don't know how we'll fix it. The only reasonable thing for the moment seems to be drilling into everyone that at the end of the day they own their stuff. Be it a homework, a PR or a comment on a blog. Some are obviously more important than the others, but still. Don't submit something you can't defend, especially when your education/career/reputation depends on it.

However, almost every peer review I was a part of, pre- and post-LLM, had one reviewer who provided a questionable review. Sometimes I'd wonder if they'd even read the submission, and sometimes, there were borderline unethical practices like trying to farm citations through my submission. Luckily, at least one other diligent reviewer would provide a counterweight.

Safe to say that I don't find it surprising, and hearing / reading others' experiences tells me it's yet another symptom of a barely functioning mechanism that is peer review today.

Sadly, it's the best mechanism that institutions are willing to support.

Many of the researchers may not have native command of English and even if, AI can help in writing in general.

Obviously I’m not referring to pure AI generated BS.

Many of us use AI to not write text, but re-write text. My favorite prompt: "Write this better." In other words, AI is often used to fix awkward phrasing, poor flow, bad english, bad grammar etc.

It's very unlikely that an author or reviewer purely relies on AI written text, with none of their original ideas incorporated.

As AI detectors cannot tell rewrites from AI-incepted writing, it's fair to call them BS.

Ignore...

hoisted by your own petard

And, if your AI can't write a paper, are you even any good as an AI researcher? :^)

It's inevitable that faces will be devoured by AI Leopards.

I increasingly see AI generated slop across the internet - on twitter, nytimes comments, blog/substack posts from smart people. Most of it is obvious AI garbage and it's really f*ing annoying. It largely has the same obnoxious style and really bad analogies. Here's an (impossible to realize) proposal: any time AI-generated text is used, we should get to see the whole interaction chain that led to its production. It would be like a student writing an essay who asks a parent or friend for help revising it. There's clearly a difference between revisions and substantial content contribution.

The notion that AI is ready to be producing research or peer reviews is just dumb. If AI correctly identifies flaws in a paper, the paper was probably real trash. Much of the time, errors are quite subtle. When I review, after I write my review and identify subtle issues, I pass the paper through AI. It rarely finds the subtle issues. (Not unlike a time it tried to debug my code and spent all its time focused on an entirely OK floating point comparison.)

For anecdotal issues with PL: I am working on a 500 word conference abstract. I spent a long while working on it but then dropped it into opus 4.5 to see what would happen. It made very minimal changes to the actual writing, but the abstract (to me) reads a lot better even with its minimal rearrangements. That surprises me. (But again, these were very minimal rearrangements: I provided ~550 words and got back a slightly reduced, 450 words.) Perhaps more interestingly, PL's characterizations are unstable. If I check the original claude output, I get "fully AI-generated, medium". If I drop in my further refined version (where I clean up claude's output), I get fully human. Some of the aspects which PL says characterize the original as AI-generated (particular n-grams in the text) are actually from my original work.

The realities are these: a) ai content sucks (especially in style); b) people will continue to use AI (often to produce crap) because doing real work is hard and everyone else is "sprinting ahead" using the semi-undetectable (or at least plausibly deniable) ai garbage; c) slowly the style of AI will almost certainly infect the writing style of actual people (ugh) - this is probably already happening; I think I can feel it in my own writing sometimes; d) AI detection may not always work, but AI-generated content is definitely proliferating. This *is* a problem, but in the long run we likely have few solutions.

Yes, AI slop is an issue. But throwing more AI at detecting this, and most importantly, not weighing that detection properly, is an even bigger problem.

And, HN-wise, "this seems like AI" seems like a very good inclusion in the "things not to complain about" FAQ. Address the idea, not the form of the message, and if it's obviously slop (or SEO, or self-promotion), just downvote (or ignore) and move on...

If they had a conference on, say, the Americans, wouldn't it be fair for Americans to have a seat at the table?