International Joint Conference on Artificial Intelligence (IJCAI)

Venue URL:

The Percentage of Empirical Papers Documenting Each Reproducibility Variable

Venue Year Papers
Repro. Score Reproducibility Score based on Gundersen et al. (2025)
Doc. Mean Global mean is the average score over the seven reproducibility variables for empirical research papers.
Doc. Median Global median is the median score over the seven reproducibility variables for empirical research papers.
Dataset Doc. Documentation mean is the average score over the Open Datasets and Dataset Splits reproducibility variables for empirical research papers.
Code Doc. Documentation mean is the average score over the Open Source Code reproducibility variables for empirical research papers.
Other Doc. Documentation mean is the average score over the Pseudocode, Hardware Specification, Software Dependencies, and Experiment Setup reproducibility variables for empirical research papers.
% Empirical Percentage of papers that are empirical research vs theoretical research
% Industry Percentage of empirical research papers with at least one author from Industry
Website
IJCAI 2025 1015 0.56 3.82 4.0 1.46 0.51 1.85 92.32% 17.18%
IJCAI 2024 790 0.55 3.55 4.0 1.25 0.55 1.75 91.01% 24.34%
IJCAI 2023 639 0.57 3.66 4.0 1.28 0.57 1.8 88.73% 30.34%
IJCAI 2022 678 0.55 3.54 4.0 1.33 0.53 1.68 88.35% 35.39%
IJCAI 2021 586 0.47 3.44 3.0 1.29 0.39 1.76 86.52% 33.73%
IJCAI 2020 645 0.44 3.3 3.0 1.31 0.33 1.66 89.92% 35.52%
IJCAI 2019 846 0.42 3.27 3.0 1.27 0.3 1.7 88.65% 34.0%
IJCAI 2018 718 0.37 3.16 3.0 1.25 0.21 1.7 88.3% 25.87%
IJCAI 2017 664 0.32 3.02 3.0 1.11 0.16 1.75 87.05% 23.01%
IJCAI 2016 647 0.27 2.71 3.0 0.98 0.11 1.63 83.31% 21.52%
IJCAI 2015 569 0.27 2.93 3.0 0.99 0.11 1.83 76.27% 20.97%