A Three-Pass Method to Triage AI Conference Papers Without Burnout

A machine learning researcher has shared a practical workflow for managing the overwhelming volume of papers published at major AI conferences like NeurIPS, ICLR, ICML, and CVPR. Rather than browsing entire proceedings, the approach starts with a specific topic and uses tools like Paper List to gauge the scope of relevant literature before committing time. Papers are then filtered through three passes — a 10-second title-and-abstract check, a one-minute scan of figures and results, and a full read reserved only for survivors. The researcher caps their active reading list at around 10 papers, rotating out older ones unless they remain directly relevant to ongoing work. The core argument is that reducing decision cost — knowing what not to read — saves more time than improving reading speed alone.