DRL4IR: 4th Workshop on Deep Reinforcement Learning for Information Retrieval
Xin Xin, Xiangyu Zhao, Jin Huang, Weinan Zhang, Li Zhao, Dawei Yin, Grace Hui Yang · 2023
\AcIR 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.