Neural Lexical Search with Learned Sparse Retrieval

Andrew Yates - University of Amsterdam
Carlos Lassance - Cohere
Cosimo Rulli - ISTI-CNR
Eugene Yang - Human Language Technology Center of Excellence, Johns Hopkins University
Macavaney Sean - University of Glasgow
Siddharth Singh - University of Amsterdam
Thong Nguyen - University of Amsterdam
Yibin Lei - University of Amsterdam

DOI: https://doi.org/10.1145/3726302.3731693

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

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Andrew, Yates
University of Amsterdam
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