Conversational Search: From Fundamentals to Frontiers in the LLM Era

Conversational search enables multi-turn interactions between users and systems to fulfill users' complex information needs. During this interaction, the system should understand the users' search intent within the conversational context and then return the relevant information through a flexible, dialogue-based interface. The recent powerful large language models (LLMs) with capacities of instruction following, content generation, and reasoning, attract significant attention and advancements, providing new opportunities and challenges for building up intelligent conversational search systems. This tutorial aims to introduce the connection between fundamentals and the emerging topics revolutionized by LLMs in the context of conversational search. It is designed for students, researchers, and practitioners from both academia and industry. Participants will gain a comprehensive understanding of both the core principles and cutting-edge developments driven by LLMs in conversational search, equipping them with the knowledge needed to contribute to the development of next-generation conversational search systems.

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Publication Details

Published
2025-07-13
DOI
https://doi.org/10.1145/3726302.3731686
Citations
5
Primary Topic
Artificial Intelligence in Law
Type
article
Field-Weighted Citation Impact
42.61

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article

Conversational Search: From Fundamentals to Frontiers in the LLM Era

Jian‐Yun Nie, Fengran Mo, Mohammad Aliannejadi, Chuan Meng
5 citations
Artificial Intelligence in Law
42.61
article

Conversational Search: From Fundamentals to Frontiers in the LLM Era

Jian‐Yun Nie, Fengran Mo, Mohammad Aliannejadi, Chuan Meng
article en
5 citations

Abstract

Conversational search enables multi-turn interactions between users and systems to fulfill users' complex information needs. During this interaction, the system should understand the users' search intent within the conversational context and then return the relevant information through a flexible, dialogue-based interface. The recent powerful large language models (LLMs) with capacities of instruction following, content generation, and reasoning, attract significant attention and advancements, providing new opportunities and challenges for building up intelligent conversational search systems. This tutorial aims to introduce the connection between fundamentals and the emerging topics revolutionized by LLMs in the context of conversational search. It is designed for students, researchers, and practitioners from both academia and industry. Participants will gain a comprehensive understanding of both the core principles and cutting-edge developments driven by LLMs in conversational search, equipping them with the knowledge needed to contribute to the development of next-generation conversational search systems.

Amsterdam University of the Arts (NL), Université de Montréal (CA), University of Amsterdam (NL)
Natural Sciences and Engineering Research Council of Canada
Quality Education
Openalex Percentile: Top 0%
Artificial Intelligence in Law
42.61
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