Zero-shot Language Modeling

Zero-Shot Language Modeling is a language modeling paradigm in which a model generates predictions or performs tasks in the absence of explicit training examples for those tasks, relying solely on its pre-trained knowledge and implicit understanding of task descriptions.

219

Publications

18.3K

Citations

1K

Authors

184

Institutions

Publications per year

2017–2026

216

Authors

1K

  1. LZ
    Luke Zettlemoyer

    University of Washington, United States

    10 publications · 666 citations

    10

    h-index

  2. AW
    Albert Webson

    John Brown University, United States

    8 publications · 2.5K citations

    8

    h-index

  3. MS
    Minjoon Seo

    Korea Advanced Institute of Science and Technology, South Korea

    5 publications · 110 citations

    5

    h-index

  4. SC
    Steven C. H. Hoi

    Nanyang Technological University, Singapore

    5 publications · 1.5K citations

    5

    h-index

  5. JL
    Junnan Li

    National University of Singapore, Singapore

    5 publications · 1.5K citations

    5

    h-index

1–5 of 1K

Venues

  1. arXiv (Cornell University)

    Repository · 87 publications · 8.3K citations

    33

    h-index

  2. 7

    h-index

  3. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 6 publications · 192 citations

    6

    h-index

  4. SSRN Electronic Journal

    Repository · 3 publications · 56 citations

    3

    h-index

  5. 3

    h-index

1–5