Dialogue Flow

Dialogue flow research focuses on understanding and improving the structure and coherence of conversations, particularly in the context of human-computer interaction and AI-driven dialogue systems. Current research emphasizes developing models that can effectively plan and manage dialogue turns, leveraging techniques like multi-agent systems, knowledge graphs, and dual-process frameworks to generate more natural, engaging, and goal-oriented conversations. This work is crucial for advancing the capabilities of conversational AI, impacting applications ranging from mental health counseling and customer service to educational tools and entertainment. The ultimate goal is to create AI systems that can participate in nuanced, contextually aware, and human-like dialogues.