Neural Lexical Search with Learned Sparse Retrieval

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Abstract Summary
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.
Abstract ID :
NKDR228
Submission Type
Submission Topics
Johns Hopkins University, HLTCOE
Researcher
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ISTI-CNR
Research Scientist
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Human Language Technology Center Of Excellence, Johns Hopkins University
Senior Lecturer
,
University Of Glasgow
PhD Student
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University Of Amsterdam
PhD student
,
University Of Amsterdam
PhD student
,
University Of Amsterdam

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