Resource-poor Language Processing

Resource-Poor Language Processing is a subfield of Multilingual Natural Language Processing that focuses on developing computational methods, models, or resources for languages with limited availability of annotated data, digital text, or linguistic tools, thereby distinguishing it from approaches designed for well-resourced languages.

162

Publications

8K

Citations

609

Authors

208

Institutions

Publications per year

2017–2026

87

Authors

609

  1. AS
    Anders Søgaard

    University of Copenhagen, Denmark

    4 publications · 253 citations

    4

    h-index

  2. GN
    Graham Neubig

    Carnegie Mellon University, United States

    4 publications · 264 citations

    4

    h-index

  3. PN
    Preslav Nakov

    Sofia University "St. Kliment Ohridski", Bulgaria

    4 publications · 163 citations

    4

    h-index

  4. KK
    Katharina Kann

    New York University, United States

    4 publications · 129 citations

    4

    h-index

  5. MM
    Mounika Marreddy

    Indian Institute of Technology Hyderabad, India

    3 publications · 52 citations

    3

    h-index

1–5 of 609

Venues

  1. arXiv (Cornell University)

    Repository · 9 publications · 222 citations

    9

    h-index

  2. 7

    h-index

  3. 4

    h-index

  4. Machine Translation

    3 publications · 62 citations

    3

    h-index

  5. 3

    h-index

1–5