Conversation State Tracking
Conversation State Tracking is a computational framework within conversational interfaces that maintains and updates the evolving context of a dialogue by identifying and representing the user’s intentions and information needs at each turn.
52
Publications
2.3K
Citations
198
Authors
56
Institutions
Publications per year
2017–2026
38
Variants
Dialogue State Tracking
Parents
52
TripPy: A Triple Copy Strategy for Value Independent Neural Dialog State Tracking
Michael Heck, Carel van Niekerk, Nurul Lubis et al. · 2020 · 189 citations · Full text
Dialog State Tracking: A Neural Reading Comprehension Approach
Shuyang Gao, Abhishek Sethi, Sanchit Agarwal et al. · 2019 · 165 citations · Full text
MinTL: Minimalist Transfer Learning for Task-Oriented Dialogue Systems
Zhaojiang Lin, Andrea Madotto, Genta Indra Winata et al. · 2020 · 138 citations · Full text
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Amazon (Germany)
Berlin, Germany
3 h-index
4 publications
156 citations
Salesforce (United States)
San Francisco, United States
3 h-index
24 publications
2.8K citations
Heinrich Heine University Düsseldorf
Düsseldorf, Germany
3 h-index
23 publications
1.6K citations

Hong Kong University of Science and Technology
Hong Kong, Hong Kong
3 h-index
6 publications
610 citations
University of Michigan
Ann Arbor, United States
2 h-index
11 publications
1.1K citations
University of Cambridge
Cambridge, United Kingdom
2 h-index
6 publications
151 citations
Amazon (United States)
Seattle, United States
2 h-index
5 publications
125 citations

Beijing University of Posts and Telecommunications
Beijing, China
2 h-index
6 publications
168 citations
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Repository · 12 publications · 437 citations
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1 publications · 13 citations
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1 publications · 25 citations
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Conference · 1 publications · 34 citations
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Conference · 1 publications · 25 citations
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