Benchmark Bias

Benchmark Bias is a methodological artifact in empirical research that systematically distorts performance evaluations of academic contributions by favoring certain models, methods, or theories due to non-representative, skewed, or unrepresentative selection of benchmark datasets, tasks, or metrics.

36

Publications

2.1K

Citations

123

Authors

96

Institutions

Publications per year

2017–2026

19

Variants

Benchmarking Bias

Authors

123

  1. MC
    Martijn Cremers

    University of Notre Dame, United States

    3 publications · 506 citations

    3

    h-index

  2. MT
    Marlon T. Conato

    University of the Philippines Diliman, Philippines

    2 publications · 108 citations

    2

    h-index

  3. JD
    Jeffrey D. Rimer

    University of Houston, United States

    2 publications · 108 citations

    2

    h-index

  4. MH
    Ming‐Feng Hsieh

    University of California, Santa Barbara, United States

    2 publications · 108 citations

    2

    h-index

  5. MD
    Matthew D. Oleksiak

    University of Houston, United States

    2 publications · 108 citations

    2

    h-index

1–5 of 123

Venues

  1. SSRN Electronic Journal

    Repository · 4 publications · 213 citations

    4

    h-index

  2. arXiv (Cornell University)

    Repository · 3 publications · 133 citations

    3

    h-index

  3. Journal of Chemical Theory and Computation

    JCTC · 1 publications · 191 citations

    1

    h-index

  4. Corporate Governance

    1 publications · 16 citations

    1

    h-index

  5. Forest Science

    1 publications · 15 citations

    1

    h-index

1–5