Neural Lexical Search with Learned Sparse Retrieval

Open Access
Authors
Publication date 2025
Book title SIGIR '25
Book subtitle Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval : July 13-18, 2025, Padua, Italy
ISBN (electronic)
  • 9798400715921
Event 48th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2025
Pages (from-to) 4122-4125
Number of pages 4
Publisher New York, NY: Association for Computing Machinery
Organisations
  • Faculty of Science (FNWI) - Informatics Institute (IVI)
Abstract

Learned Sparse Retrieval (LSR) techniques use neural machinery to represent queries and documents as learned bags of words. In contrast with other neural retrieval techniques, such as generative retrieval and dense retrieval, LSR has been shown to be a remarkably robust, transferable, and efficient family of methods for retrieving high-quality search results. This half-day tutorial aims to provide an extensive overview of LSR, ranging from its fundamentals to the latest emerging techniques. By the end of the tutorial, attendees will be familiar with the important design decisions of an LSR system, know how to apply them to text and other modalities, and understand the latest techniques for retrieving with them efficiently. Website: https://lsr-tutorial.github.io

Document type Conference contribution
Language English
Published at https://doi.org/10.1145/3726302.3731693
Other links https://www.scopus.com/pages/publications/105011828279
Downloads
3726302.3731693 (Final published version)
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