Workshops highlighted the role of user modelling in conversational information retrieval, indicating emerging trends.
Conversational Information Retrieval (CIR) has seen growing interest for a number of years, gaining momentum in recent years, driven in large part by the emergence of generative AI and the increasing capabilities of conversational agents. To date, much of the CIR research within the information retrieval community has concentrated on modelling the interactive processes between users and systems, with comparatively less attention given to explicitly modelling the user within these interactions. The UM-CIR 2024 sought to provide a forum for examination of the role of the user in CIR. Recognising that CIR continues to be an evolving area of investigation, the follow on ET-CIR 2024 workshop provided a platform for discussion of emerging trends in the field. Each workshop featured a combination of keynote and invited talks, panel discussions, and paper presentations that collectively emphasized the importance of incorporating user models and perspectives in the design and evaluation of CIR systems. Date: 12–13 December 2024. Website: https://um-cir.github.io.
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Acharya et al. (2025) studied this question.
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