Sequence Modeling

Sequence Modeling is a computational framework within the broader class of predictive modeling techniques that uniquely captures temporal or sequential dependencies in ordered data by leveraging the dynamic relationships between elements in a sequence.

460

Publications

42.2K

Citations

1.6K

Authors

515

Institutions

Publications per year

2017–2026

313

Authors

1.6K

  1. AM
    Andrew McCallum

    University of Massachusetts Amherst, United States

    6 publications · 2.8K citations

    6

    h-index

  2. CR
    Christopher Ré

    Stanford University, United States

    4 publications · 609 citations

    4

    h-index

  3. HP
    Hanspeter Pfister

    Harvard University Press, United States

    4 publications · 436 citations

    4

    h-index

  4. AG
    Albert Gu

    Stanford University, United States

    4 publications · 1.6K citations

    4

    h-index

  5. SB
    Shaojie Bai

    Carnegie Mellon University, United States

    4 publications · 4.5K citations

    4

    h-index

1–5 of 1.6K

Venues

  1. arXiv (Cornell University)

    Repository · 84 publications · 11.1K citations

    36

    h-index

  2. IEEE Access

    10 publications · 514 citations

    11

    h-index

  3. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 7 publications · 327 citations

    7

    h-index

  4. Neurocomputing

    5 publications · 233 citations

    5

    h-index

  5. 5

    h-index

1–5