Benchmark Dataset Evaluation

Benchmark Dataset Evaluation is a systematic assessment method that, as a paper-level contribution within Tutoring System Evaluation, employs standardized datasets to measure and compare the performance of educational models or algorithms against established baselines.

2.2K

Publications

164.4K

Citations

8.3K

Authors

2K

Institutions

Publications per year

2017–2026

1.6K

Authors

8.3K

  1. KC
    Kuo‐Chen Chou

    The Gordon Life Science Institute, United States

    12 publications · 1.7K citations

    12

    h-index

  2. BS
    Boxin Shi

    Peking University, China

    10 publications · 1K citations

    10

    h-index

  3. QT
    Qi Tian

    Huawei Technologies (China), China

    9 publications · 1.5K citations

    9

    h-index

  4. BL
    Bin Liu

    Harbin Institute of Technology, China

    9 publications · 1.2K citations

    9

    h-index

  5. MY
    Ming–Hsuan Yang

    University of California, Merced, United States

    9 publications · 1.4K citations

    9

    h-index

1–5 of 8.3K

Venues

  1. arXiv (Cornell University)

    Repository · 254 publications · 11.3K citations

    50

    h-index

  2. IEEE Access

    54 publications · 3.1K citations

    29

    h-index

  3. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 40 publications · 3.2K citations

    29

    h-index

  4. IEEE Transactions on Pattern Analysis and Machine Intelligence

    TPAMI · 26 publications · 4.5K citations

    23

    h-index

  5. PLoS ONE

    18 publications · 1.1K citations

    15

    h-index

1–5