Why doesn't the ML research community limit the number of submissions per author? [D]

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Summary

A researcher questions why the ML community doesn't limit submissions per author to manage review quality, citing successful practices in other fields like Security and Computer Architecture.

I am currently working across multiple research communities, and I've noticed that the ML community is struggling with a massive volume of submissions, which is affecting review quality (as we are seeing in the recent ARR cycles). I am wondering what the reasoning is for not limiting the number of submissions per author? This practice has been successfully used in other research areas for years, such as Security (e.g., CCS) or Computer Architecture (e.g., DAC), to help keep workloads manageable. Is there a particular cultural reason why the ML community chooses a different approach?
Original Article

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