•1 min read•from Machine Learning
Why doesn't the ML research community limit the number of submissions per author? [D]
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?
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