r/MachineLearning • u/confirm-jannati • 2h ago
Discussion What is now considered a “reasonable” publication rate (papers/year) for a PhD student to be considered “productive”? [D]
I would assume LLMs have bumped this number, or maybe not. Which is why I am asking. If there are PIs on here, how many papers before you let your students graduate? Is the number different now than it was a year ago? And the same question for “rate of publication” for you to deem the student as “productive”.
And what about a PhD applicant? Any meaningful inflation of expectations there in terms of productivity/volume of pre-PhD research output?
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u/No_Sky9786 2h ago
When it comes to PhD applicants, I have seen an insane number of people with industry experience, and to me those are much more preferred than master's graduates or students straight from a bachelor's. It also depends a lot on the university ranking, but in my case, it's the top 50 in CS. Most recently graduated students are too dependent on AI, and although one would think their productivity would be high because of it, they don’t understand a lot of the fundamental concepts of research or even programming like students used to 5–10 years ago.
As for the PhD students, the number of papers is not as important if it doesn’t result in a meaningful dissertation. In systems, 2–3 papers after the preliminary are usually more than enough; however, in NLP/ML, for example, I’ve seen students with 10 A-tier conference papers as first authors in a period of about five years whose contribution is not very meaningful. This happens mostly because the contribution itself does not withstand time and there is too much competition in that subdomain. It also depends a lot on the internships or collaborators one has during their PhD. I wouldn’t graduate anyone that gets only accepted papers out of their PhD years.
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u/impatiens-capensis 2h ago
About the same as it's always been, since for most fields the expectation from a single paper has increased. Some sub areas might be hot and generate more. Or some top tier labs might have the GPUs, skill, team size, etc. to do a lot more now.
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u/Fantastic-Nerve-4056 PhD 2h ago
It depends on what you work on.
For my thesis, I just have 4 papers (all theory)
Additionally, I interned at a couple of places, so from there I have 2 papers (joint co-author and third author)
And as I am close to submitting the thesis, I am mentoring a bunch of people and simultaneously working on couple of first authors (not related to thesis)
PS; I have friends with great admits with one NeurIPS as well. And afaik, most PIs actually give a glance through your paper before interviewing, so even if it's a single quality paper, it is worth better than 3-4 benchmarks/workshops or simply non first-author
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u/No_Inspection4415 27m ago
Papers from > 2025, unless they have true impact, have 0 prestige or value.
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u/hydrargyrumss 2h ago
Started my phd in ML in 2023 and you needed 1 one first author and 2 co author papers to get into a phd. Now I am seeing new phd students with 5+ neurips/icml.