What is an average publication outcome for an ML PhD? [D]

Our take

For a Machine Learning (ML) PhD, the average publication outcome by graduation often falls between three to five first-author papers in top-tier venues such as NeurIPS, ICML, ICLR, CVPR, ACL, and EMNLP. While this count can vary significantly based on factors like advisor support, lab culture, and subfield focus, achieving this range is generally seen as a solid benchmark.

I know publication count is not everything, and quality, contribution, advisor/lab culture, subfield, and luck all matter a lot. But to make the comparison easier, I’m curious about the publication-count side specifically.
For an ML PhD, what would you consider an average publication outcome by graduation?

For example, would something like 3–5 first-author papers at A/top-tier venues* be considered roughly average, or would that already be above average in ML?

By A*/top-tier, I’m thinking of venues such as NeurIPS, ICML, ICLR, CVPR, ACL, EMNLP, etc., depending on the subfield.

Important:
Again, I know paper count is a crude metric. I’m just trying to get a rough sense of what people in the field see as average, strong, or unusually strong.

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