The 4th Workshop on Deep Reinforcement Learning for Information Retrieval
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.
The DRL4IR@CIKM2023 workshop will be held as a full-day event in conjunction with
. The concepts and keywords are required. Submissions can be of varying length from 4 to 8 pages. References do not count against the page limit. All submissions must be original and not simultaneously submitted to another journal or conference.
Papers that include text generated from a large-scale language model (LLM) such as ChatGPT are prohibited unless this produced text is presented as a part of the paper’s experimental analysis. AI tools may be used to edit and polish authors’ work, such as using LLMs for light editing of their own text (e.g., automate grammar checks, word autocorrect, and other editing work), but text “produced entirely” by AI is not allowed.
All submissions will be double-blind peer reviewed by the program committee and judged by their relevance to the workshop, scientific novelty, and technical quality.
Please note that at least one of the authors of each accepted paper must register for the workshop and present the paper either remotely or on location (strongly preferred).
We encourage but do not require authors to release any code and/or datasets associated with their paper.