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.

翻译：本文件调查了过去几年发展起来的对对话性AI的神经方法,我们将对话系统分为三类:(1) 回答问题的人,(2) 任务导向的对话代理人,(3) 聊天室。 对于每一类,我们提出对最新神经学方法的审查,指出这些方法与传统方法之间的联系,并讨论已经取得的进展和仍然面临的挑战,使用具体的系统和模型作为案例研究。