Low-resource Machine Translation

Low-Resource Machine Translation is a subfield of machine translation that focuses on developing methods for language pairs with limited parallel corpora, where the scarcity of training data poses significant challenges to achieving high translation quality.

472

Publications

24.7K

Citations

1.3K

Authors

343

Institutions

Publications per year

2017–2026

384

Authors

1.3K

  1. GN
    Graham Neubig

    Carnegie Mellon University, United States

    21 publications · 1.4K citations

    16

    h-index

  2. JG
    Jiatao Gu

    Meta (Israel), Israel

    13 publications · 2.7K citations

    12

    h-index

  3. VC
    Vishrav Chaudhary

    Meta (Israel), Israel

    12 publications · 906 citations

    12

    h-index

  4. PK
    Philipp Koehn

    University of Edinburgh, United Kingdom

    13 publications · 1.1K citations

    12

    h-index

  5. FG
    Francisco Guzmán

    Qatar Foundation, Qatar

    11 publications · 1.1K citations

    11

    h-index

1–5 of 1.3K

Venues

  1. arXiv (Cornell University)

    Repository · 92 publications · 5.8K citations

    35

    h-index

  2. 13

    h-index

  3. Machine Translation

    9 publications · 281 citations

    9

    h-index

  4. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 9 publications · 276 citations

    9

    h-index

  5. 5

    h-index

1–5