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 Coakley et alK. L. Coakley, T. Snelleman, H. Hoos, and O. E. Gundersen, "The embrace of open science: An analysis of a decade of AI research and 56 800 conference papers," Under Review, 2026..
Reproducibility Score
Edition reproducibility score by venue over time.
Documentation Score
Edition documentation score by venue over time.
Latest Editions
Browse reproducibility metrics across the latest editions of each venue.
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Reproducibility Score based on Gundersen et al. (2025). See Methods for details.
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Documentation Score is the average score over the seven reproducibility variables for empirical research papers. See Methods for details.
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Percentage of papers that are empirical research vs theoretical research.
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Percentage of empirical research papers with at least one author from Industry.
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Website | |||
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| AAAI | 2025 | 2903 | 0.58 | 3.83 | 95.8% | 27.62% | |
| DMLR | 2025 | 13 | 0.76 | 4.55 | 84.62% | 18.18% | |
| ICLR | 2025 | 3700 | 0.66 | 4.54 | 97.97% | 42.65% | |
| ICML | 2025 | 3330 | 0.61 | 4.42 | 94.95% | 36.69% | |
| IJCAI | 2025 | 1015 | 0.56 | 3.82 | 92.32% | 17.18% | |
| JAIR | 2025 | 132 | 0.51 | 3.89 | 72.73% | 14.58% | |
| JMLR | 2025 | 269 | 0.46 | 3.79 | 86.99% | 17.52% | |
| NeurIPS | 2025 | 5286 | 0.69 | 4.89 | 95.63% | 35.23% | |
| TMLR | 2025 | 1418 | 0.62 | 4.51 | 94.71% | 33.8% |