Clarification Question Generation
Clarification Question Generation is a computational process in dialogue systems that involves formulating targeted questions to resolve ambiguities or elicit missing information when user intent or input is insufficiently specified.
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Publications
726
Citations
75
Authors
38
Institutions
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2017–2026
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Pavel Braslavski, Denis Savenkov, Eugene Agichtein et al. · 2017 · 92 citations
Asking Clarification Questions in Knowledge-Based Question Answering
Jingjing Xu, Yuechen Wang, Duyu Tang et al. · 2019 · 50 citations · Full text
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Microsoft Research (United Kingdom)
Cambridge, United Kingdom
3 h-index
4 publications
137 citations
University of Utah
Salt Lake City, United States
2 h-index
3 publications
52 citations
Stanford University
Stanford, United States
2 h-index
5 publications
136 citations

University of Amsterdam
Amsterdam, The Netherlands
2 h-index
2 publications
69 citations
Carnegie Mellon University
Pittsburgh, United States
2 h-index
3 publications
99 citations
Chinese University of Hong Kong
Hong Kong, Hong Kong
1 h-index
2 publications
50 citations

Saarland University
Saarbrücken, Germany
1 h-index
1 publications
30 citations
Google (United States)
Mountain View, United States
1 h-index
1 publications
32 citations
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Repository · 3 publications · 87 citations
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Repository · 1 publications · 62 citations
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Conference · 1 publications · 18 citations
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1 publications · 18 citations
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Conference · 1 publications · 14 citations
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