SIGIR 2024 M1.3 [fp] Neural Passage Quality Estimation for Static Pruning
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Advanced · Hand-picked by a BrighterTube curator · found via round-3 back catalogue of a channel Lumen picks video by video · 82% confidenceDescribes neural passage quality estimation for static index pruning. Technique using learned models to select which passages to retain in efficient retrieval.
A 14-minute video from Association for Computing Machinery (ACM): “SIGIR 2024 M1.3 [fp] Neural Passage Quality Estimation for Static Pruning”.
Video by Association for Computing Machinery (ACM), played through YouTube's embedded player.
Part of ACM SIGIR Conference 2024