Question Answering

Question Answering is a natural language processing task that involves automatically determining precise answers to natural language questions by analyzing and understanding textual content, distinguished from related information retrieval or text mining tasks by its focus on identifying specific, factually grounded responses rather than retrieving, summarizing, or categorizing documents or passages.

11.2K

Publications

854.7K

Citations

26K

Authors

3.6K

Institutions

Publications per year

2017–2026

6.2K

Authors

26K

  1. MZ
    Ming Zhou

    Microsoft Research Asia (China), China

    51 publications · 5K citations

    36

    h-index

  2. HH
    Hannaneh Hajishirzi

    University of Washington, United States

    56 publications · 5.9K citations

    35

    h-index

  3. WB
    W. Bruce Croft

    University of Massachusetts Amherst, United States

    52 publications · 5.7K citations

    33

    h-index

  4. JL
    Jimmy Lin

    University of Waterloo, Canada

    64 publications · 4.3K citations

    33

    h-index

  5. TC
    Tat‐Seng Chua

    National University of Singapore, Singapore

    59 publications · 3.5K citations

    32

    h-index

1–5 of 26K

Venues

  1. arXiv (Cornell University)

    Repository · 1.3K publications · 108.3K citations

    138

    h-index

  2. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 254 publications · 17.3K citations

    69

    h-index

  3. Transactions of the Association for Computational Linguistics

    TACL · 54 publications · 7.5K citations

    36

    h-index

  4. Information Processing & Management

    86 publications · 3.8K citations

    34

    h-index

  5. Expert Systems with Applications

    56 publications · 1.9K citations

    29

    h-index

1–5