Cross-lingual Topic Modeling

Cross-Lingual Topic Modeling is a topic modeling framework that enables the discovery and alignment of latent semantic topics across multiple languages by leveraging multilingual corpora and cross-lingual representations.

58

Publications

2.8K

Citations

171

Authors

72

Institutions

Publications per year

2017–2026

20

Authors

171

  1. MM
    Marie‐Francine Moens

    KU Leuven, Belgium

    8 publications · 408 citations

    8

    h-index

  2. IV
    Ivan Vulić

    University of Cambridge, United Kingdom

    6 publications · 324 citations

    6

    h-index

  3. WD
    Wim De Smet

    KU Leuven, Belgium

    4 publications · 277 citations

    4

    h-index

  4. JB
    Jordan Boyd‐Graber

    University of Maryland, College Park, United States

    3 publications · 202 citations

    3

    h-index

  5. ED
    Erik De Vries

    University of Stavanger, Norway

    2 publications · 247 citations

    2

    h-index

1–5 of 171

Venues

  1. Lirias (KU Leuven)

    Repository · 3 publications · 174 citations

    3

    h-index

  2. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 2 publications · 28 citations

    2

    h-index

  3. International Conference on Computational Linguistics

    Conference · 2 publications · 33 citations

    2

    h-index

  4. Computer Speech & Language

    2 publications · 67 citations

    2

    h-index

  5. Synthese

    1 publications · 13 citations

    1

    h-index

1–5