Conversational Question

Conversational question answering (CQA) focuses on building systems that can engage in multi-turn, context-aware dialogues to answer user questions, aiming for natural and informative interactions. Current research emphasizes improving query understanding and generation by leveraging large language models (LLMs) and incorporating techniques like query rewriting, retrieval augmentation, and reinforcement learning to optimize for both accuracy and conversational fluency. These advancements are significant for enhancing human-computer interaction in various applications, including customer service, education, and information retrieval, by enabling more natural and effective knowledge seeking.