The 4th Workshop on AI Agent for Information Retrieval: Generating and Ranking
The field of information retrieval has significantly transformed with the integration of AI technologies. AI agents, especially those leveraging LLMs and vast computational power, have revolutionized in- formation retrieval, processing, and presentation. LLM agents, with advanced memory, reasoning, and planning capabilities, can perform complex tasks, engage in coherent conversations, and provide personalized responses. Despite these advancements, challenges such as ensuring relevance and accuracy, mitigating biases, providing real-time responses, and maintaining data security remain. This workshop aims to explore these challenges, share innovative solutions, and discuss future directions. It will provide a platform to bring together researchers and practitioners to discuss the latest theoretical advancements and practical implementations of AI agents in information retrieval. Topics include AI in search, recommendation, and personalization systems. By gathering a diverse group of experts, the workshop seeks to deepen the understanding of AI agents in information retrieval, advance the field, and enhance its societal impact. Participants will gain insights into cutting-edge research and emerging trends, and foster knowledge exchange and collaboration within the community.
Authors
- Wei Liu (ORCID: https://orcid.org/0000-0002-3003-1313)
- Julian McAuley (ORCID: https://orcid.org/0000-0003-0955-7588)
- Linsey Pang (ORCID: https://orcid.org/0000-0002-4784-9795)
- Philip S. Yu (ORCID: https://orcid.org/0000-0002-3491-5968)
- Qingsong Wen (ORCID: https://orcid.org/0000-0003-4516-2524)
- Zhiwei Liu (ORCID: https://orcid.org/0000-0003-1525-1067)
- Yongfeng Zhang (ORCID: https://orcid.org/0000-0002-0327-3261)
- Hua Wei (ORCID: https://orcid.org/0000-0002-3735-1635)
Institutions
- Rutgers, The State University of New Jersey (US)
- University of Technology Sydney (AU)
- Bellevue College (US)
- UC San Diego Health System (US)
- University of Illinois Chicago (US)
- Salesforce (United States) (US)
- Arizona State University (US)
Publication Details
- Published
- 2025-08-03
- DOI
- https://doi.org/10.1145/3711896.3737849
- Primary Topic
- Data Mining Algorithms and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Science Foundation
- Georgia Institute of Technology
- Arizona State University
- Institute for Catastrophic Loss Reduction
- Tencent
- University of Technology Sydney
- University of Illinois at Urbana-Champaign
- University of California, San Diego
- University of Illinois at Chicago
- Instituto de Ciencias del Mar y Limnología, Universidad Nacional Autónoma de México
- Lawrence Berkeley National Laboratory