Single-document Summarization

Single-Document Summarization is a subtask of text summarization that involves generating a concise and coherent summary from a single source document, distinguishing it from multi-document approaches by focusing exclusively on content derived from one individual text.

215

Publications

14.9K

Citations

502

Authors

194

Institutions

Publications per year

2017–2026

86

Authors

502

  1. ML
    Mirella Lapata

    University of Edinburgh, United Kingdom

    8 publications · 2.4K citations

    8

    h-index

  2. XW
    Xiaojun Wan

    Peking University, China

    7 publications · 455 citations

    7

    h-index

  3. DR
    Dragomir Radev

    University of Michigan, United States

    7 publications · 537 citations

    7

    h-index

  4. JM
    John M. Conroy

    University of Maryland, College Park, United States

    6 publications · 137 citations

    6

    h-index

  5. CL
    Chin-Yew Lin

    Microsoft Research Asia (China), China

    6 publications · 680 citations

    6

    h-index

1–5 of 502

Venues

  1. arXiv (Cornell University)

    Repository · 11 publications · 487 citations

    11

    h-index

  2. Information Processing & Management

    5 publications · 213 citations

    5

    h-index

  3. Expert Systems with Applications

    4 publications · 1K citations

    4

    h-index

  4. 3

    h-index

  5. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 3 publications · 61 citations

    3

    h-index

1–5