Future of Information Retrieval Research in the Age of Generative AI
James Allan, Eunsol Choi, Daniel P. Lopresti, Hamed Zamani

TL;DR
This paper discusses the transformative impact of generative AI on information retrieval, highlighting future research directions, challenges, and opportunities based on expert discussions from a 2024 workshop.
Contribution
It provides a comprehensive vision and set of recommendations for integrating generative AI into IR research and practice, based on expert insights and collaborative discussions.
Findings
Identification of key research topics in IR-GenAI
Recommendations for future IR research and development
Highlighting challenges and opportunities in IR with generative AI
Abstract
In the fast-evolving field of information retrieval (IR), the integration of generative AI technologies such as large language models (LLMs) is transforming how users search for and interact with information. Recognizing this paradigm shift at the intersection of IR and generative AI (IR-GenAI), a visioning workshop supported by the Computing Community Consortium (CCC) was held in July 2024 to discuss the future of IR in the age of generative AI. This workshop convened 44 experts in information retrieval, natural language processing, human-computer interaction, and artificial intelligence from academia, industry, and government to explore how generative AI can enhance IR and vice versa, and to identify the major challenges and opportunities in this rapidly advancing field. This report contains a summary of discussions as potentially important research topics and contains a list of…
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Taxonomy
TopicsBig Data Technologies and Applications · Recommender Systems and Techniques · Topic Modeling
