Static Word Embeddings

Static Word Embeddings is a type of word representation in natural language processing where each word is mapped to a fixed-dimensional vector in a continuous space, learned from corpus statistics and remaining invariant across different linguistic contexts.

80

Publications

3.9K

Citations

258

Authors

119

Institutions

Publications per year

2017–2026

73

Authors

258

  1. AK
    Anna Korhonen

    University of Cambridge, United Kingdom

    4 publications · 86 citations

    4

    h-index

  2. IV
    Ivan Vulić

    University of Cambridge, United Kingdom

    3 publications · 71 citations

    3

    h-index

  3. SG
    Sarik Ghazarian

    University of Southern California, United States

    2 publications · 97 citations

    2

    h-index

  4. FW
    Furu Wei

    Microsoft Research Asia (China), China

    2 publications · 97 citations

    2

    h-index

  5. GG
    Goran Glavašš

    University of Mannheim, Germany

    2 publications · 45 citations

    2

    h-index

1–5 of 258

Venues

  1. arXiv (Cornell University)

    Repository · 8 publications · 255 citations

    8

    h-index

  2. 2

    h-index

  3. 2

    h-index

  4. Language Resources and Evaluation

    2 publications · 88 citations

    2

    h-index

  5. 2

    h-index

1–5