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

Authors

2.1K

  1. JG
    Jianfeng Gao

    Microsoft (United States), United States

    29 publications · 5.7K citations

    24

    h-index

  2. MG
    Michel Galley

    Microsoft (United States), United States

    21 publications · 5.2K citations

    20

    h-index

  3. BD
    Bill Dolan

    Microsoft (United States), United States

    18 publications · 3.6K citations

    18

    h-index

  4. CB
    Chris Brockett

    Microsoft (United States), United States

    19 publications · 3.6K citations

    18

    h-index

  5. MH
    Minlie Huang

    Tsinghua University, China

    18 publications · 1.5K citations

    17

    h-index

1–5 of 2.1K

Venues

  1. arXiv (Cornell University)

    Repository · 171 publications · 9.6K citations

    49

    h-index

  2. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 56 publications · 4.3K citations

    30

    h-index

  3. 12

    h-index

  4. IEEE Access

    7 publications · 148 citations

    10

    h-index

  5. 8

    h-index

1–5