IMHO (not a paper writer, but read a lot during my grad school years), the Genie is out of the bottle. The only way forward, as I see it, is using LLMs for reviews also. Basically, filter all submitted papers with an LLM and ask it to summarize it, find the biggest weaknesses and main strong points, etc. that a human can then use to review the paper. Basically, LLM-as-a-reviewer .
Personally, I would love to see a conference where people are explicitly encouraged to use LLMs for doing the work and writing the papers, and LLMs are used to review them too.
The Medium comments on this post are also on point. Running the same experiment with accepted papers is a good control. Running a similar experiment with reviewers would be interesting, but more obnoxious because they are not being paid.
I would keep a private blacklist (shadow ban) the authors who wasted several hours of a reviewer's time to prove they were not legitimate. The existence of such a list would be problematic, though.
Could the same system we use here be applied? Accepted authors could "vouch" for "dead" papers in case they were "auto-killed"?
This system is broken and providing more evidence that it is broken isn't much of a step towards fixing it.
One larger problem here is the value of a research paper is rarely the specific knowledge it adds but in the process of researching that adds to the collective knowledge+experience of those involved, especially training graduate students. AI papers shortcut this entirely. Academia has a lot to answer for this too by making papers the currency of success. AI generated papers are almost shortcut learning at a full system level.
I'm not familiar with the world of academic publishing, so I want to ask: how is the industry making sure that submissions aren't at least partially AI-generated?
Is it standard practice for authors to have to defend their submissions via interview like this? If not, why not?
Does the vetting process vary with the quality of the publisher?
As an outsider, it's extremely worrying that anyone would even attempt to submit an AI-generated paper for publication in an academic journal. At that level I would have assumed literally everybody should know better than to even try.
> Is it standard practice for authors to have to defend their submissions via interview like this? If not, why not?
It isn't, but maybe it should be. For post-grad qualifications oral defense is standard, and I didn't mind defending my central thesis then, and won't mind now.
Peer review has its historical issues, but the landscape of science and science-publishing has changed. New problems of authorship and authorial-understanding are now challenged by LLMs writing (at least) good sounding papers - some of which might be of acceptable quality in subject (I am not against AI in the sciences; some of the math work has been great). On the other hand: I am against authors not understanding their own work. High repute journals may need to add "oral exams" to the paper acceptance process...
I wonder how the ratios would change for papers at different parts of the review process. For what fraction of published papers are the authors unable to answer basic questions about them?
I think authenticity and trust will command a (larger) premium in this new age of slop.
The article highlights how only one out of ten paper’s authors were able to answer questions thoroughly and at a high level. This indicates an overwhelming percentage of authors are slopping up their work with AI and submitting it without even reading it.
No doubt this is happening, but I wonder how many authors of papers "slated for desk rejection" 10 years ago could answer questions about their papers? We'd need that comparison to understand if this is a new problem or if AI is just a new source of content that the authors of poorly-written papers are using.
Personally, I would love to see a conference where people are explicitly encouraged to use LLMs for doing the work and writing the papers, and LLMs are used to review them too.
I would keep a private blacklist (shadow ban) the authors who wasted several hours of a reviewer's time to prove they were not legitimate. The existence of such a list would be problematic, though.
Could the same system we use here be applied? Accepted authors could "vouch" for "dead" papers in case they were "auto-killed"?
This system is broken and providing more evidence that it is broken isn't much of a step towards fixing it.
Is it standard practice for authors to have to defend their submissions via interview like this? If not, why not?
Does the vetting process vary with the quality of the publisher?
As an outsider, it's extremely worrying that anyone would even attempt to submit an AI-generated paper for publication in an academic journal. At that level I would have assumed literally everybody should know better than to even try.
It isn't, but maybe it should be. For post-grad qualifications oral defense is standard, and I didn't mind defending my central thesis then, and won't mind now.
EDIT: I found a live link on arxiv https://arxiv.org/html/2609.20481v1
https://chorasimilarity.wordpress.com/2026/06/13/a-captcha-f...
At the moment this was seen as a tongue in cheek proposal.
The article highlights how only one out of ten paper’s authors were able to answer questions thoroughly and at a high level. This indicates an overwhelming percentage of authors are slopping up their work with AI and submitting it without even reading it.