Evaluation Benchmarks

Evaluation Benchmarks is a standardized point of reference in the form of a dataset, metric, task, or methodological framework against which the performance, validity, or generalizability of recommender systems is systematically assessed and compared within academic evaluation contexts.

1.4K

Publications

153K

Citations

5.5K

Authors

1.4K

Institutions

Publications per year

2017–2026

706

Authors

5.5K

  1. LL
    Liang Lin

    Sun Yat-sen University, China

    8 publications · 1.3K citations

    8

    h-index

  2. HL
    Huchuan Lu

    Dalian University of Technology, China

    8 publications · 1.2K citations

    8

    h-index

  3. SK
    Suha Kwak

    Pohang University of Science and Technology, South Korea

    6 publications · 695 citations

    6

    h-index

  4. YC
    Yejin Choi

    University of Washington, United States

    5 publications · 1.2K citations

    5

    h-index

  5. LZ
    Lei Zhang

    Hong Kong Polytechnic University, Hong Kong SAR China

    5 publications · 1.1K citations

    5

    h-index

1–5 of 5.5K

Venues

  1. arXiv (Cornell University)

    Repository · 181 publications · 22.8K citations

    56

    h-index

  2. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 19 publications · 1.8K citations

    15

    h-index

  3. IEEE Transactions on Pattern Analysis and Machine Intelligence

    TPAMI · 15 publications · 2.3K citations

    14

    h-index

  4. 13

    h-index

  5. 2021 IEEE/CVF International Conference on Computer Vision (ICCV)

    Conference · 11 publications · 472 citations

    11

    h-index

1–5