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 Joint Conference on Artificial Intelligence (IJCAI)
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 | ||
|---|---|---|---|---|---|---|---|
| IJCAI | 2025 | 1015 | 0.56 | 3.82 | 92.32% | 17.18% | |
| IJCAI | 2024 | 790 | 0.55 | 3.55 | 91.01% | 24.34% | |
| IJCAI | 2023 | 639 | 0.57 | 3.66 | 88.73% | 30.34% | |
| IJCAI | 2022 | 678 | 0.55 | 3.54 | 88.35% | 35.39% | |
| IJCAI | 2021 | 586 | 0.47 | 3.44 | 86.52% | 33.73% | |
| IJCAI | 2020 | 645 | 0.44 | 3.3 | 89.92% | 35.52% | |
| IJCAI | 2019 | 846 | 0.42 | 3.27 | 88.65% | 34.0% | |
| IJCAI | 2018 | 718 | 0.37 | 3.16 | 88.3% | 25.87% | |
| IJCAI | 2017 | 664 | 0.32 | 3.02 | 87.05% | 23.01% | |
| IJCAI | 2016 | 647 | 0.27 | 2.71 | 83.31% | 21.52% | |
| IJCAI | 2015 | 569 | 0.27 | 2.93 | 76.27% | 20.97% |