Neural Approaches to Conversational AI

ACL(2018)

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摘要
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.
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关键词
Information Retrieval,Human-Computer Interaction,Human-Computer Interaction,Machine Learning,Robotics,Question answering,Text mining,Assistive technologies,Interdisciplinary influence :Artificial intelligence and the user interface,Assistive technologies,Interdisciplinary influence :Artificial intelligence and the user interface,Deep Learning,Reinforcement learning,Human-Robot Interaction:Dialog Systems
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