Weakly Supervised Sequence Labeling

Weakly Supervised Sequence Labeling is a sequence labeling paradigm that operates with incomplete, noisy, or indirect supervision, differing from fully supervised approaches by leveraging limited or imprecise label information to train models effectively.

10

Publications

591

Citations

43

Authors

12

Institutions

Publications per year

2017–2026

5

Authors

43

  1. MF
    Madalina Fiterau

    University of Massachusetts Amherst, United States

    2 publications · 118 citations

    2

    h-index

  2. SL
    Scott L. Delp

    Stanford University, United States

    2 publications · 118 citations

    2

    h-index

  3. PV
    Paroma Varma

    Stanford University, United States

    2 publications · 118 citations

    2

    h-index

  4. KX
    Ke Xiao

    Louisiana State University, United States

    2 publications · 118 citations

    2

    h-index

  5. EA
    Euan A. Ashley

    Stanford University, United States

    2 publications · 118 citations

    2

    h-index

1–5 of 43

Venues

  1. arXiv (Cornell University)

    Repository · 2 publications · 23 citations

    2

    h-index

  2. 1

    h-index

  3. bioRxiv (Cold Spring Harbor Laboratory)

    Repository · 1 publications · 22 citations

    1

    h-index

  4. Nature Communications

    1 publications · 96 citations

    1

    h-index

  5. Zenodo (CERN European Organization for Nuclear Research)

    Repository · 1 publications · 61 citations

    1

    h-index

1–5