Neural Passage Quality Estimation for Static Pruning - Efficiency for Search
Association for Computing Machinery (ACM) via YouTube
Build the Finance Skills That Lead to Promotions — Not Just Certificates
Get 20% off all career paths from fullstack to AI
Overview
Google, IBM & Meta Certificates — All 10,000+ Courses at 40% Off
One annual plan covers every course and certificate on Coursera. 40% off for a limited time.
Get Full Access
Explore a 14-minute conference talk from SIGIR 2024 focused on Neural Passage Quality Estimation for Static Pruning. Delve into the research presented by authors Xuejun Chang, Debabrata Mishra, Craig Macdonald, and Sean MacAvaney as they discuss innovative approaches to improve search efficiency. Learn about the latest advancements in static pruning techniques and how neural networks are being utilized to estimate passage quality, potentially revolutionizing information retrieval systems.
Syllabus
SIGIR 2024 M1.3 [fp] Neural Passage Quality Estimation for Static Pruning
Taught by
Association for Computing Machinery (ACM)