Word-level Language Modeling

Word-Level Language Modeling is a type of language modeling that operates at the word level, where the fundamental unit of analysis and prediction is the word, distinguishing it from character-level or subword-level approaches by treating whole words as the atomic tokens in the probabilistic modeling of natural language.

98

Publications

7.3K

Citations

313

Authors

117

Institutions

Publications per year

2017–2026

52

Authors

313

  1. HN
    Hermann Ney

    RWTH Aachen University, Germany

    4 publications · 249 citations

    4

    h-index

  2. KB
    Kalika Bali

    Microsoft Research (India), India

    3 publications · 136 citations

    3

    h-index

  3. AS
    Andreas Stolcke

    SRI International, United States

    3 publications · 182 citations

    3

    h-index

  4. RS
    Ralf Schlüter

    RWTH Aachen University, Germany

    3 publications · 238 citations

    3

    h-index

  5. SB
    Somnath Banerjee

    Hewlett-Packard (India), India

    2 publications · 52 citations

    2

    h-index

1–5 of 313

Venues

  1. arXiv (Cornell University)

    Repository · 18 publications · 2.1K citations

    15

    h-index

  2. International Conference on Computational Linguistics

    Conference · 3 publications · 56 citations

    3

    h-index

  3. International Conference on Learning Representations

    Conference · 2 publications · 74 citations

    2

    h-index

  4. IEEE Access

    2 publications · 114 citations

    2

    h-index

  5. 2

    h-index

1–5