DRL4IR: 4th Workshop on Deep Reinforcement Learning for Information Retrieval

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Abstract

Information retrieval (IR) is one of the most important fields to help users find relevant information. The interaction between IR systems and users can be naturally formulated as a decision-making problem. In the last decade, deep reinforcement learning (DRL) has become a promising direction to utilize the high model capacity of deep learning to improve long-term gains. On the one hand, there have been emerging research works focusing on leveraging DRL for IR tasks while the fundamental information theory under DRL settings, the principle of RL methods for IR tasks, or the experimental evaluation protocols of DRL-based IR systems, has not been deeply investigated. On the other hand, the emerging ChatGPT also provides new insights and challenges for DRL-based IR. Therefore, we propose the fourth DRL4IR workshop at CIKM 2023, which provides a venue for both academia researchers and industry practitioners to present the recent advances of DRL-based IR system, to foster novel research, interesting findings, and new applications of DRL for IR. We will pay more attention to fundamental research topics and recent application advances such as ChatGPT, with an expectation of over 300 workshop participants.

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Xin, X., Zhang, W., Zhao, X., Zhao, L., Yang, G. H., Huang, J., & Yin, D. (2023). DRL4IR: 4th Workshop on Deep Reinforcement Learning for Information Retrieval. In International Conference on Information and Knowledge Management, Proceedings (pp. 5304–5307). Association for Computing Machinery. https://doi.org/10.1145/3583780.3615303

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