Neural Lexical Search with Learned Sparse Retrieval
| Authors |
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|---|---|
| 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) |
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| 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 |
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| 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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