Question Generation

Question Generation is a natural language generation task that involves automatically producing interrogative sentences from a given input such as a text passage, fact, or knowledge base, distinguishing it from other text generation tasks by its focus on forming syntactically and semantically valid questions rather than statements or summaries.

589

Publications

27.4K

Citations

1.8K

Authors

513

Institutions

Publications per year

2017–2026

385

Authors

1.8K

  1. MZ
    Ming Zhou

    Microsoft Research Asia (China), China

    12 publications · 1.3K citations

    12

    h-index

  2. ND
    Nan Duan

    Microsoft Research Asia (China), China

    11 publications · 1.3K citations

    11

    h-index

  3. PP
    Paul Piwek

    The Open University, United Kingdom

    10 publications · 334 citations

    10

    h-index

  4. FW
    Furu Wei

    Microsoft Research Asia (China), China

    7 publications · 349 citations

    7

    h-index

  5. XY
    Xingdi Yuan

    Microsoft Research (United Kingdom), United Kingdom

    7 publications · 430 citations

    7

    h-index

1–5 of 1.8K

Venues

  1. arXiv (Cornell University)

    Repository · 57 publications · 2.4K citations

    25

    h-index

  2. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 16 publications · 994 citations

    15

    h-index

  3. 9

    h-index

  4. IEEE Transactions on Learning Technologies

    7 publications · 460 citations

    7

    h-index

  5. Dialogue & Discourse

    8 publications · 275 citations

    7

    h-index

1–5