Re-Thinking Re-Ranking

Re-ranking systems often rely on a ‘cascading’ approach, where an initial set of documents is re-sorted to create a final result list. However, this method has a critical flaw: it can miss out on the most relevant documents by filtering them out too early, which reduces recall and hampers overall performance. In this talk, I will share an alternative to the cascading approach that brings in additional relevant documents during the re-ranking process. This technique improves the efficiency and effectiveness of both vector search and heavy-weight re-rankers. I’ll also discuss ongoing efforts to bring this technique from academia to industry. Cascading is dead, long live re-ranking!

Sean MacAvaney

University of Glasgow

Sean MacAvaney is a Lecturer (Assistant Professor) at the University of Glasgow. As a researcher, he develops new techniques for using AI in search engines. As a teacher, he brings the latest research into the lecture hall to inspire and train the next generation of search engineers and researchers.