Hybrid Summarization

Hybrid Summarization is a text summarization approach that combines both extractive and abstractive methods within a unified framework to leverage the strengths of each in generating concise and accurate summaries.

83

Publications

3.8K

Citations

279

Authors

130

Institutions

Publications per year

2017–2026

40

Authors

279

  1. XC
    Xiaoyan Cai

    Northwestern Polytechnical University, China

    2 publications · 94 citations

    2

    h-index

  2. JK
    Jungo Kasai

    University of Washington, United States

    2 publications · 225 citations

    2

    h-index

  3. DR
    Dragomir Radev

    University of Michigan, United States

    2 publications · 225 citations

    2

    h-index

  4. AR
    Alexander R. Fabbri

    Yale University, United States

    2 publications · 225 citations

    2

    h-index

  5. MB
    Marc Brockschmidt

    Microsoft Research (United Kingdom), United Kingdom

    2 publications · 194 citations

    2

    h-index

1–5 of 279

Venues

  1. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 4 publications · 267 citations

    4

    h-index

  2. Expert Systems with Applications

    3 publications · 116 citations

    3

    h-index

  3. arXiv (Cornell University)

    Repository · 3 publications · 236 citations

    3

    h-index

  4. Cognitive Computation

    2 publications · 113 citations

    2

    h-index

  5. IEEE Access

    2 publications · 60 citations

    2

    h-index

1–5