Statistical Text Simplification

Statistical Text Simplification is a text simplification approach that belongs to the class of statistical natural language processing methods, distinguished by its reliance on probabilistic models trained on parallel corpora to automatically learn and apply simplification transformations.

15

Publications

1.4K

Citations

37

Authors

14

Institutions

Publications per year

2017–2026

2

Authors

37

  1. SŠ
    Sanja Štajner

    University of Mannheim, Germany

    3 publications · 104 citations

    3

    h-index

  2. CN
    Courtney Napoles

    Johns Hopkins University, United States

    2 publications · 561 citations

    2

    h-index

  3. XW
    Xindong Wu

    Hefei University of Technology, China

    2 publications · 36 citations

    2

    h-index

  4. JQ
    Jipeng Qiang

    Yangzhou University, China

    2 publications · 36 citations

    2

    h-index

  5. EP
    Ellie Pavlick

    John Brown University, United States

    1 publications · 516 citations

    1

    h-index

1–5 of 37

Venues

  1. Computer Speech & Language

    1 publications · 34 citations

    1

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  2. TUbilio (Technical University of Darmstadt)

    Repository · 1 publications · 328 citations

    1

    h-index

  3. 1

    h-index

  4. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 1 publications · 24 citations

    1

    h-index

  5. Frontiers of Computer Science

    1 publications · 12 citations

    1

    h-index

1–5