Conversational Question Answering

Conversational Question Answering (CQA) focuses on building systems that can accurately answer questions posed within a dialogue context, addressing the challenges of understanding conversational nuances and dependencies. Current research emphasizes improving the robustness and efficiency of CQA models, particularly through techniques like query rewriting which reformulates conversational questions into simpler forms suitable for existing question-answering systems, and leveraging large language models enhanced by methods like reinforcement learning and data augmentation strategies. These advancements aim to improve the accuracy and applicability of CQA across diverse domains, including healthcare, where the ability to provide nuanced and contextually appropriate answers is crucial.