Knowledge Grounded Dialogue

Knowledge-grounded dialogue focuses on building conversational agents that can access and utilize external knowledge sources to generate informative and factually consistent responses. Current research emphasizes improving the accuracy and relevance of knowledge selection, addressing issues like hallucinations and inconsistencies through techniques such as multi-stage prompting, modular architectures separating reasoning from response generation, and reinforcement learning to align model outputs with factual knowledge. These advancements are significant for creating more reliable and engaging conversational AI systems with applications in various fields, including question answering, personalized tutoring, and customer service.