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Tutorial on Neural Lexical Search with Learned Sparse Retrieval

Session Information

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/

Mar 29, 2026 13:30 - 17:00(Europe/Amsterdam)
Venue : Lecture room D
20260329T1330 20260329T1700 Europe/Amsterdam Tutorial on Neural Lexical Search with Learned Sparse Retrieval

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/

Lecture room D ECIR2026 conference-secretariat@blueboxevents.nl

Sub Sessions

Neural Lexical Search with Learned Sparse Retrieval

Tutorials 01:30 PM - 05:00 PM (Europe/Amsterdam) 2026/03/29 11:30:00 UTC - 2026/03/29 15:00:00 UTC
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 model, know how to apply them to text and other modalities, and understand the latest techniques for retrieving with them efficiently.
Presenters
AY
Andrew Yates
Johns Hopkins University, HLTCOE
Co-Authors
CL
Carlos Lassance
Cohere
CR
Cosimo Rulli
Researcher , ISTI-CNR
Eugene Yang
Research Scientist, Human Language Technology Center Of Excellence, Johns Hopkins University
SM
Sean MacAvaney
Senior Lecturer, University Of Glasgow
SS
Siddharth Singh
PhD Student, University Of Amsterdam
TN
Thong Nguyen
PhD Student, University Of Amsterdam
YL
Yibin Lei
PhD Student, University Of Amsterdam
199 visits

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Johns Hopkins University, HLTCOE
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 Sérgio Nunes
University of Porto | INESC TEC
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