Notice: 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. Full accuracy metrics and methodology are described in [1].
International Conference on Machine Learning (ICML)
The Percentage of Empirical Papers Documenting Each Reproducibility Variable
| Venue |
Reproducibility Score based on Gundersen et al. (2025)
|
Global mean is the average score over the seven reproducibility variables for empirical research papers.
|
Percentage of papers that are empirical research vs theoretical research
|
Percentage of empirical research papers with at least one author from Industry
|
Website | ||
|---|---|---|---|---|---|---|---|
| ICML | 2025 | 3330 | 0.61 | 4.42 | 94.95% | 36.69% | |
| ICML | 2024 | 2610 | 0.62 | 4.11 | 93.03% | 39.99% | |
| ICML | 2023 | 1828 | 0.6 | 4.06 | 91.47% | 43.84% | |
| ICML | 2022 | 1233 | 0.58 | 3.97 | 92.94% | 42.84% | |
| ICML | 2021 | 1183 | 0.52 | 3.38 | 92.98% | 45.09% | |
| ICML | 2020 | 1084 | 0.52 | 3.43 | 90.68% | 44.05% | |
| ICML | 2019 | 773 | 0.49 | 3.23 | 92.24% | 46.28% | |
| ICML | 2018 | 621 | 0.42 | 3.13 | 94.52% | 40.2% | |
| ICML | 2017 | 434 | 0.39 | 3.15 | 92.17% | 41.25% | |
| ICML | 2016 | 322 | 0.36 | 3.07 | 93.17% | 33.0% | |
| ICML | 2015 | 270 | 0.37 | 3.24 | 94.07% | 28.35% | |
| ICML | 2014 | 310 | 0.3 | 3.0 | 93.55% | 27.59% |