Contextual Word Representation

Contextual Word Representation is a type of word representation that dynamically models the meaning of a word based on its surrounding textual context, distinguishing itself from static representations by encoding linguistic variability and polysemy through context-sensitive mechanisms.

234

Publications

17.9K

Citations

705

Authors

301

Institutions

Publications per year

2017–2026

151

Variants

Contextualized Word Representation

Authors

705

  1. NA
    Noah A. Smith

    Carnegie Mellon University, United States

    6 publications · 1K citations

    6

    h-index

  2. ME
    Matthew E. Peters

    Allen Institute for Artificial Intelligence, United States

    4 publications · 2.5K citations

    4

    h-index

  3. MS
    Maosong Sun

    Tsinghua University, China

    4 publications · 967 citations

    4

    h-index

  4. ID
    Ido Dagan

    Bar-Ilan University, Israel

    4 publications · 312 citations

    4

    h-index

  5. MS
    Mark S. Seidenberg

    University of Wisconsin–Madison, United States

    3 publications · 1.3K citations

    3

    h-index

1–5 of 705

Venues

  1. arXiv (Cornell University)

    Repository · 21 publications · 1.6K citations

    16

    h-index

  2. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 11 publications · 799 citations

    10

    h-index

  3. IEEE Access

    6 publications · 273 citations

    6

    h-index

  4. Knowledge-Based Systems

    3 publications · 154 citations

    3

    h-index

  5. Neuropsychologia

    2 publications · 189 citations

    2

    h-index

1–5