Comment by an0malous

Comment by an0malous 3 days ago

5 replies

Why not just reject papers authored by LLMs and ban accounts that are caught? arXiv’s management has become really questionable lately, it’s like they’re trying to become a prestigious journal and are becoming the problem they were trying to solve in the first place

tarruda 3 days ago

> Why not just reject papers authored by LLMs and ban accounts that are caught?

Are you saying that there's an automated method for reliably verifying that something was created by an LLM?

  • an0malous 3 days ago

    If there wasn’t, then how do they know LLMs are the problem?

orbital-decay 3 days ago

What matters is the quality. Requiring reviews and opinions to be peer-reviewed seems a lot less superficial than rejecting LLM-assisted papers (which can be valid). This seems like a reasonable filter for papers with no first-party contributions. I'm sure they ran actual numbers as well.

catlifeonmars 3 days ago

It’s articles (not papers) _about_ LLMs that are the problem, not papers written _by_ LLMs (although I imagine they are not mutually exclusive). Title is ambiguous.

  • dabber 3 days ago

    > It’s articles (not papers) _about_ LLMs that are the problem, not papers written _by_ 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.