Proactive Dialogue

Proactive dialogue systems aim to design conversational agents that guide interactions towards predefined goals, rather than simply responding reactively. Current research emphasizes developing models that effectively plan dialogue paths, often using techniques like bidirectional planning, reinforcement learning, and stochastic processes, to achieve target-oriented conversations while maintaining user engagement and trust. This field is crucial for improving human-computer interaction in various applications, from clinical information gathering to personalized recommendations, by creating more efficient and natural conversational experiences. The development of high-quality datasets and robust evaluation metrics remains a key challenge for advancing the field.