Multi-turn Conversation Modeling

Multi-Turn Conversation Modeling is a computational framework in dialogue systems that captures and predicts the dynamic evolution of conversational states across sequential interactions by jointly modeling contextual dependencies, speaker intentions, and response coherence beyond isolated utterance pairs.

80

Publications

5.7K

Citations

346

Authors

97

Institutions

Publications per year

2017–2026

62

Authors

346

  1. MQ
    Minghui Qiu

    Alibaba Group (China), China

    4 publications · 273 citations

    4

    h-index

  2. CQ
    Chen Qu

    Emory University, United States

    4 publications · 273 citations

    4

    h-index

  3. HW
    Hua Wu

    Baidu (China), China

    3 publications · 222 citations

    3

    h-index

  4. CZ
    Chujie Zheng

    Tsinghua University, China

    3 publications · 145 citations

    3

    h-index

  5. MH
    Minlie Huang

    Tsinghua University, China

    3 publications · 145 citations

    3

    h-index

1–5 of 346

Venues

  1. arXiv (Cornell University)

    Repository · 18 publications · 876 citations

    15

    h-index

  2. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 8 publications · 376 citations

    8

    h-index

  3. 1

    h-index

  4. Cognitive Science

    1 publications · 145 citations

    1

    h-index

  5. Computational Linguistics

    1 publications · 74 citations

    1

    h-index

1–5