Machine Reading Comprehension

Machine Reading Comprehension is a computational task within natural language understanding that requires a machine to automatically answer questions based on a given textual passage, thereby demonstrating comprehension through accurate and contextually grounded responses.

267

Publications

27.9K

Citations

863

Authors

207

Institutions

Publications per year

2017–2026

251

Authors

863

  1. JG
    Jianfeng Gao

    Microsoft (United States), United States

    14 publications · 1.5K citations

    13

    h-index

  2. HZ
    Hai Zhao

    Shanghai Jiao Tong University, China

    14 publications · 850 citations

    12

    h-index

  3. ZZ
    Zhuosheng Zhang

    Shanghai Jiao Tong University, China

    14 publications · 1K citations

    12

    h-index

  4. YS
    Yelong Shen

    Microsoft (United States), United States

    11 publications · 843 citations

    11

    h-index

  5. YC
    Yiming Cui

    Harbin Institute of Technology, China

    10 publications · 489 citations

    10

    h-index

1–5 of 863

Venues

  1. arXiv (Cornell University)

    Repository · 72 publications · 6.6K citations

    32

    h-index

  2. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 20 publications · 1.6K citations

    16

    h-index

  3. 5

    h-index

  4. Knowledge-Based Systems

    3 publications · 62 citations

    4

    h-index

  5. Neurocomputing

    3 publications · 43 citations

    3

    h-index

1–5