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.

AAAI Conference on Artificial Intelligence (AAAI)

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
AAAI 2025 2903 0.58 3.83 95.8% 27.62%
AAAI 2024 2331 0.57 3.55 95.37% 31.67%
AAAI 2023 1578 0.57 3.68 93.85% 37.41%
AAAI 2022 1319 0.53 3.62 93.18% 41.01%
AAAI 2021 1654 0.5 3.6 92.26% 42.46%
AAAI 2020 1607 0.46 3.41 93.84% 43.5%
AAAI 2019 1146 0.41 3.3 92.23% 37.65%
AAAI 2018 935 0.37 3.24 92.51% 28.09%
AAAI 2017 645 0.33 3.06 89.46% 23.05%
AAAI 2016 676 0.27 2.65 88.02% 22.35%
AAAI 2015 651 0.25 2.54 84.79% 17.39%
AAAI 2014 447 0.24 2.57 87.25% 16.41%