Neural Approaches to Conversational AI
It provides a comprehensive overview for researchers and practitioners in conversational AI, but is incremental as it synthesizes existing work without introducing new methods.
This paper surveys neural approaches to conversational AI, categorizing systems into question answering agents, task-oriented dialogue agents, and chatbots, and reviews state-of-the-art methods, connections to traditional approaches, and ongoing challenges.
The present paper surveys neural approaches to conversational AI that have been developed in the last few years. We group conversational systems into three categories: (1) question answering agents, (2) task-oriented dialogue agents, and (3) chatbots. For each category, we present a review of state-of-the-art neural approaches, draw the connection between them and traditional approaches, and discuss the progress that has been made and challenges still being faced, using specific systems and models as case studies.