Conversational Information Retrieval

Conversational Information Retrieval (CIR) aims to improve information retrieval by enabling users to interact with systems through natural language conversations, rather than simple keyword searches. Current research focuses on enhancing the accuracy and efficiency of CIR systems, particularly by leveraging large language models (LLMs) for tasks like query reformulation, context understanding, and multi-task candidate selection within a conversational context. This field is significant because it promises more human-centered and effective information access, impacting areas like conversational AI, personalized search, and the development of more robust and ethical conversational agents.