Notice: This website is continuously updated as new conference proceedings and journal volumes are published. Consequently, the figures presented here may differ from those reported in our publications.


A brief overview of our methodology is provided on the Methods page, along with references to publications documenting our approach and links to the code and data used in each study.


The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates.

Journal of Machine Learning Research (JMLR)

Venue URL:

Reproducibility Score

Documentation Score

The Percentage of Empirical Papers Documenting Each Reproducibility Variable

Venue
Reproducibility Score based on Gundersen et al. (2025). See Methods for details.
Documentation Score is the average score over the seven reproducibility variables for empirical research papers. See Methods for details.
Percentage of papers that are empirical research vs theoretical research.
Percentage of empirical research papers with at least one author from Industry.
Website
JMLR 2025 269 0.46 3.79 86.99% 17.52%
JMLR 2024 421 0.49 3.73 84.32% 19.44%
JMLR 2023 400 0.47 3.83 86.25% 17.97%
JMLR 2022 351 0.52 3.89 84.05% 21.02%
JMLR 2021 290 0.46 3.74 85.52% 21.77%
JMLR 2020 252 0.45 3.75 86.9% 22.37%
JMLR 2019 184 0.4 3.55 83.15% 24.84%
JMLR 2018 84 0.36 3.35 89.29% 21.33%
JMLR 2017 234 0.42 3.57 83.33% 21.03%
JMLR 2016 236 0.41 3.54 84.75% 16.0%
JMLR 2015 118 0.39 3.65 69.49% 18.29%
JMLR 2014 120 0.44 3.78 85.0% 17.65%