Neural Approaches to Conversational AI
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.
Code (0)
등록된 구현이 없습니다.
Tasks
Question AnsweringSimilar Papers 제목 키워드 기반
From Rewriting to Remembering: Common Ground for Conversational QA Models
In conversational QA, models have to leverage information in previous turns to answer upcoming questions. Current approaches, such as Question Rewriting, struggle to extract relevant information as the conversation unwin…
Question RewritingFrom Rewriting to Remembering: Common Ground for Conversational QA Models
In conversational QA, models have to leverage information in previous turns to answer upcoming questions. Current approaches, such as Question Rewriting, struggle to extract relevant information as the conversation unwin…
Question RewritingCommon Conversational Community Prototype: Scholarly Conversational Assistant
This paper discusses the potential for creating academic resources (tools, data, and evaluation approaches) to support research in conversational search, by focusing on realistic information needs and conversational inte…
Conversational SearchLearn to Resolve Conversational Dependency: A Consistency Training Framework for Conversational Question Answering
One of the main challenges in conversational question answering (CQA) is to resolve the conversational dependency, such as anaphora and ellipsis. However, existing approaches do not explicitly train QA models on how to r…
Conversational Question AnsweringQuestion AnsweringQuestion RewritingHistory-Aware Conversational Dense Retrieval
Conversational search facilitates complex information retrieval by enabling multi-turn interactions between users and the system. Supporting such interactions requires a comprehensive understanding of the conversational …
Conversational SearchInformation RetrievalRetrieval