Sequence-to-sequence Tagging

Sequence-to-Sequence Tagging is a sequence labeling framework that maps an input sequence to an output sequence of structured labels through an encoder-decoder architecture, distinguishing itself from traditional tagging models by enabling flexible, end-to-end learning of sequential dependencies between variable-length input and output sequences.

159

Publications

10.5K

Citations

556

Authors

193

Institutions

Publications per year

2017–2026

108

Authors

556

  1. JB
    Johan Bos

    University of Groningen, Netherlands

    4 publications · 216 citations

    4

    h-index

  2. HM
    Hamdy Mubarak

    Qatar Airways (Qatar), Qatar

    4 publications · 83 citations

    4

    h-index

  3. IG
    Iryna Gurevych

    Technische Universität Darmstadt, Germany

    3 publications · 319 citations

    3

    h-index

  4. RV
    Rik van Noord

    University of Groningen, Netherlands

    3 publications · 154 citations

    3

    h-index

  5. AA
    Ahmed Abdelalí

    New Mexico State University, United States

    3 publications · 61 citations

    3

    h-index

1–5 of 556

Venues

  1. arXiv (Cornell University)

    Repository · 31 publications · 1.6K citations

    16

    h-index

  2. IEEE Access

    5 publications · 70 citations

    5

    h-index

  3. 5

    h-index

  4. Computational Linguistics

    2 publications · 97 citations

    2

    h-index

  5. DSpace repository (University of Tartu)

    Repository · 2 publications · 29 citations

    2

    h-index

1–5