Future of Information Retrieval Research in the Age of Generative AI

• URL: http://arxiv.org/abs/2412.02043v1
• Date: Tue, 03 Dec 2024 00:01:48 GMT
• Title: Future of Information Retrieval Research in the Age of Generative AI
• Authors: James Allan, Eunsol Choi, Daniel P. Lopresti, Hamed Zamani,
• Abstract summary: 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, a visioning workshop was held in July 2024 to discuss the future of IR in the age of generative AI. This report contains a summary of discussions as potentially important research topics and contains a list of recommendations for academics, industry practitioners, institutions, evaluation campaigns, and funding agencies.
• Score: 61.56371468069577
• License:
• 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 recommendations for academics, industry practitioners, institutions, evaluation campaigns, and funding agencies.

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