Dialogue Response Generation
Dialogue Response Generation is a natural language generation task that specifically involves producing contextually appropriate and coherent utterances in response to preceding dialogue inputs within an interactive conversation.
838
Publications
51K
Citations
2.1K
Authors
442
Institutions
Publications per year
2017–2026
677
Parents
838
Deep Reinforcement Learning for Dialogue Generation
Jiwei Li, Will Monroe, Alan Ritter et al. · 2016 · 1.1K citations · Full text
DIALOGPT : Large-Scale Generative Pre-training for Conversational Response Generation
Yizhe Zhang, Siqi Sun, Michel Galley et al. · 2020 · 1.1K citations · Full text
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442
Tencent (China)
Shenzhen, China
24 h-index
89 publications
3.8K citations
Microsoft (United States)
Redmond, United States
23 h-index
97 publications
14.6K citations
Tsinghua University
Beijing, China
23 h-index
83 publications
8.7K citations

Chinese Academy of Sciences
Beijing, China
21 h-index
89 publications
3.9K citations

Peking University
Beijing, China
21 h-index
115 publications
5.2K citations
University of Chinese Academy of Sciences
Beijing, China
19 h-index
64 publications
3.1K citations

Harbin Institute of Technology
Harbin, China
19 h-index
116 publications
4.1K citations
Microsoft Research (United Kingdom)
Cambridge, United Kingdom
17 h-index
79 publications
8.3K citations
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Repository · 171 publications · 9.6K citations
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Conference · 56 publications · 4.3K citations
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Conference · 12 publications · 403 citations
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7 publications · 148 citations
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TASLP · 8 publications · 181 citations
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