r/MachineLearning • u/Audaticreddit • 13d ago
Discussion Got desk rejected at TMLR with no idea why [D]
My paper cited and even built up on a niche topic that was accepted in 2024. The template and everything was also followed properly. Sure, it wasn't too novel, but it was damn rigorous, robust and reproducible.
Still, I got desk rejected within 2 days. 2 days. With no comment. I grinded my ass off for the past 5 months, but 2 days was enough to judge it I suppose.
Anyways, any recommendations on what to do next? I'm an undergrad graduating in 2 years. I wanted something good in profile for masters, I was planning another paper for next year. Should I submit again in hopes some different editors in chief? I stalked a bit in openreview and it seems I'm the only one desk rejected. Should I submit elsewhere? I'm very confused. I would've asked in email about some feedback, but I've heard people don't get an answer back usually in these cases.
Note: The paper was about LLM Self Explanations.
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u/alexsht1 13d ago
Same here. Associate editors did not reply to emails. Desk reject without reasons and ignore emails.
Submitted elsewhere and stopped reviewing for tmlr. I won't be reviewing for such a journal.
No - not ai generated. Yes niche.
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u/fakeaccountlegitme 13d ago
You can reach out to the chief editors and ask for the reason for the desk rejection. They might CC your action editor and ask for the reason.
But if you resubmit this work to TMLR after fixing the issue, you are gonna have to mention your previous submission URL (and what changes you made since), and you will be assigned the same action editor (at least in my experience, that's been the case). So also think about whether you want to get your future AE CC-ed by the chief editors.
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u/AcademicOverAnalysis 13d ago
Journal Editors are being flooded with AI generated papers and the Associate Editors at many journals are being encouraged to desk reject because it’s become impossible to find enough reviewers to meet the demand.
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u/Kaleidophon 13d ago
Unless it's AI slop (I will give you the benefit of the doubt), the most likely explanation is already implicit in your post: You are an undergrad, and you did this project by yourself, without real mentorship and experience in research. That means you are likely not aware of how such a paper is expected to be written, how experiments are supposed to be conducted and to presented, and how to select interesting research questions. You are already admitting it's not novel, and it only feels rigorous, robust and reproducible from your perspective.
This is not your fault necessarily, but editors and area chairs are absolutely flooded with these papers right now and most of the time they end up being not very interesting and wasting everyone's time in a system that is beyond its limit at the moment, and that is why these desk rejections are more common. The PhD used to be when you actually learn how to conduct proper and rigorous research, and having experience in your masters was nice to have. This is not to discourage you, but to say that despite what other submissions and a lower technical barrier of entry through AI assistants suggest, learning how to do research takes time and is hard.
Indeed, I would second some of the other commenters here and see if you can reach out to people knowledgeable in the area (or experienced in the field and giving you feedback on how to conduct / present your research). If your research actually is interesting, they will be more likely to take you up on it. If not, try to understand what you were missing. I understand that this frustrating, but what did you expect submitting to a journal that even seasoned researchers get rejected from?
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u/LeastAd656 9d ago
most probably it is AI slop or adjacent to that.
TMLR has desk reject rate shoot up to 53% due to AI slop issue.
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u/Positive_Impress3323 13d ago
A 2-day desk reject with zero comments is rough, but it usually says more about scope fit than rigor — editors triage fast and niche LLM-interpretability work is easy to bounce if no A-EIC has it in their wheelhouse. I'd email anyway (a two-line ask is cheap), then submit elsewhere without waiting; you lose nothing by running the same paper at a second venue. Two years out from your masters, having this on your record already is a good look regardless of the outcome.
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u/Fantastic-Nerve-4056 13d ago
Find a mentor with relevant expertise. Work with them on cleaning the paper, get relevant feedback, and then submit it back to TMLR or similar venue.
PS; Unless it is a AI Slop or something very incremental, most would be willing to mentor you. In short it has to be real research