Attention-based Aggregation

Attention-Based Aggregation is a gather operation that selectively combines input elements through weighted summation, where the weights are dynamically computed by an attention mechanism to emphasize contextually relevant contributions.

65

Publications

4.6K

Citations

288

Authors

128

Institutions

Publications per year

2017–2026

62

Authors

288

  1. ML
    Minhyeok Lee

    Chung-Ang University, South Korea

    2 publications · 277 citations

    2

    h-index

  2. HL
    He Li

    Yanshan University, China

    2 publications · 57 citations

    2

    h-index

  3. FY
    Fisher Yu

    University of California, Berkeley, United States

    2 publications · 403 citations

    2

    h-index

  4. XY
    Xiaokang Yang

    Shanghai Jiao Tong University, China

    2 publications · 403 citations

    2

    h-index

  5. XL
    Xinhai Liu

    KU Leuven, Belgium

    2 publications · 369 citations

    2

    h-index

1–5 of 288

Venues

  1. arXiv (Cornell University)

    Repository · 9 publications · 215 citations

    9

    h-index

  2. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 4 publications · 453 citations

    4

    h-index

  3. Expert Systems with Applications

    3 publications · 76 citations

    3

    h-index

  4. 2

    h-index

  5. IEEE Transactions on Multimedia

    2 publications · 91 citations

    2

    h-index

1–5