Explore a cutting-edge approach to information retrieval in this 13-minute conference talk from SIGIR 2024. Delve into the concept of Generative Retrieval via Term Set Generation, presented by authors Peitian Zhang, Zheng Liu, Yujia Zhou, Zhicheng Dou, Fangchao Liu, and Zhao Cao. Learn how this innovative technique, part of the broader GenIR (Generative Information Retrieval) field, leverages Large Language Models (LLMs) to potentially revolutionize search methodologies. Gain insights into how term set generation can enhance retrieval processes and understand its implications for the future of search technologies.
Generative Retrieval via Term Set Generation - The Future of Search with LLMs
Association for Computing Machinery (ACM) via YouTube
Overview
Syllabus
SIGIR 2024 M2.1 [fp] Generative Retrieval via Term Set Generation
Taught by
Association for Computing Machinery (ACM)
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