Updated practice for review articles and position papers in ArXiv CS category

LLMs are not submitting these papers on their own, people are. As far as I'm concerned, whatever blame exists rests on those people and the system that rewards them.

LLMs are not the root of the problem here.

Blaming LLMs is unproductive. They are not going anywhere (especially since open source LLMs are so good.)

If we want to achieve real change, we need to accept that they exist, understand how that changes the scientific landscape and our options to go from here.

I don't think so. Youtube was a better place when it was just amateurs posting random shit.

Everybody "creates content" (like me when I take a picture of beautiful sunset).

There is no such thing as "quality". There is quality for me and quality for you. That is part of the problem, we can't just relate to some external, predefined scale. We (the sum of people) are the approximate, chaotic, inefficient scale.

Be my guest to propose a "perfect system", but - just in case there is no such system - we should make sure each of us "rewards" what we find of quality (being people or content creators), and hope it will prevail. Seemed to have worked so far.

Hiring and tenure review based on a candidate’s selected 5 best papers.

Already standard practice at a few enlightened places, I think. (of course this also probably increases the review workload for top venues)

To a lesser extent, bean-counting metrics like citations and h-index are an attempt to quantify non-volume-based metrics. (for non-academics, h-index is the largest N such that your N-th most cited paper has >= N citations)

Note that most approaches like this have evolved to counter “salami-slicing”, where you divide your work into “minimum publishable units”. LLMs are a different threat - from my selfish point of view, one of the biggest risks is that it takes less time to write a bogus paper with an LLM than it does for a single reviewer to review it. That threatens to upend the entire peer reviewing process.

Ditto for views, etc. Really what you care about as eg; youtube is conversions for the products that are advertised. Not impressions. But there's an attribution problem there.

Edit: For clarification I’m agreeing with OP

Fundamentally, we want research that offers something new (“what did we learn?”) and presents it in a way that at least plausibly has a chance of becoming generalizable knowledge. You call it gate-keeping, but I call it keeping published science high-quality.

Treat everyone equally. After 10 years of only quality you get chance to get back. Before that though luck.

[1] https://en.wikipedia.org/wiki/Grigori_Perelman [2] https://www.ams.org/notices/200808/tx080800930p.pdf

I don't think publishing a PGP key with your work does anything. There's no problem identifying the author of the work. The problem is identifying _untrustworthy_ authors. Especially in the face of many other participants in the system claiming the work is trusted.

As I understand it, the current system (in some fields) is essentially to set up a bunch of sockpuppet accounts to cite the main account and publish (useless) derivative works using the ideas from the main account. Someone attempting to use existing reasearch for it's intended purpose has no idea that the whole method is garbage / flawed / not reproducible.

If you can only trust what you, yourself verify, then the publications aren't nearly as useful and it is hard to "stand on the shoulders of giants" to make progress.

You might be vastly underestimating the cost of such a feature

"In the past few years, arXiv has been flooded with papers. Generative AI / large language models have added to this flood by making papers – especially papers not introducing new research results – fast and easy to write."

"Fast forward to present day – submissions to arXiv in general have risen dramatically, and we now receive hundreds of review articles every month. The advent of large language models have made this type of content relatively easy to churn out on demand, and the majority of the review articles we receive are little more than annotated bibliographies, with no substantial discussion of open research issues."

Surely a lot of them are also about LLMs: LLMs are the hot computing topic and where all the money and attention is, and they're also used heavily in the field. So that could at least partially account for why this policy is for CS papers only, but the announcement's rationale is about LLMs as producing the papers, not as their subject.

It is also turning people into spammers because it makes bluffers feel like experts.

ChatGPT is so revealing about a person's character.

I've never seen arXiv papers counted towards your publications anywhere that the number of your publications are used as a metric. Is USCIS different?

Beyond hosting cost, there is some prestige to seeing an arXiv link versus rando blog post despite both having about the same hurdle to publishing.

The idea is the site is for academic preprints. Academia has a long history of circulating preprints or manuscripts before the work is finished. There are many reasons for this, the primary one is that scientific and mathematical papers are often in the works for years before they get officially published. Preprints allow other academics in the know to be up to date on current results.

If the service is used heavily by non-academics to lend an aura of credibility to any kind of white paper then the service is less usable for its intended purpose.

It's similar to the use of question/answer sites like Quora to write blog posts and ads under questions like "Why is Foobar brand soap the right soap for your family?"

As one of those practitioners, I've found good review/survey papers to be incredibly valuable. They call my attention to the important publications and provide at least a basic timeline that helps me understand how the field has evolved from the beginning and what aspects people are focusing on now.

At the same time, I'll confess that I don't really see why most such papers couldn't be written by LLMs. Ideally by better LLMs than we have now, of course, but that could go without saying.

I don't understand the appeal of an (majorly-)LLM generated review paper. A good review paper is a hard task to write well, and frankly the only good ones I've read have come from authors who are at apex of their field (and are, in particular, strong writers). The 'lossy search' of an LLM is probably an outstanding tool for _refining_ a review paper, but for fully generating it? At least not with current LLMs.

No, not really. From the blog post:

> In the past few years, arXiv has been flooded with papers. Generative AI / large language models have added to this flood by making papers – especially papers not introducing new research results – fast and easy to write. While categories across arXiv have all seen a major increase in submissions, it’s particularly pronounced in arXiv’s CS category. > [...] > Fast forward to present day – submissions to arXiv in general have risen dramatically, and we now receive hundreds of review articles every month. The advent of large language models have made this type of content relatively easy to churn out on demand, and the majority of the review articles we receive are little more than annotated bibliographies, with no substantial discussion of open research issues.

Meanwhile, banning review articles written by humans would be harmful in many fields. I'm not in CPSC, but I'd hate to see this policy become the norm for all disciplines.

Anecdotal: A few weeks ago, I came across a story on HN where many commenters immediately recognized that an LLM had written the article, and the author had actually released his prompts and iterations. So it was not a one-shot prompt but more like 10 iterations, and still, many people saw that an LLM wrote it.

Huh, I guess it's only a subset of papers, not all of them. My brain doesn't work that way, because I don't like assigning custom rules for special cases (edit: because I usually view that as a form of discrimination). So sometimes I have a blind spot around the realities of a problem that someone is facing, that don't have much to do with its idealization.

What I mean is, I don't know that it's up to arXiv to determine what a "review article and position paper" is. Because of that, they must let all papers through, or have all papers face the same review standards.

When I see someone getting their fingers into something, like muddying/dithering concepts, shifting focus to something other than the crux of an argument (or using bad faith arguments, etc), I view it as corruption. It's a means for minority forces to insert their will over the majority. In this case, by potentially blocking meaningful work from reaching the public eye on a technicality.

So I admit that I was wrong to jump to conclusions. But I don't know that I was wrong in principle or spirit.