Datasets › ACRE
ACRE (Abstract Causal REasoning)
Abstract Causal REasoning (ACRE) is a dataset for the systematic evaluation of current vision systems in causal induction, i.e., identifying unobservable mechanisms that lead to the observable relations among variables.
Each split of the dataset is structured as follows:
config/
train.json
val.json
test.json
images/
ACRE_train_00*.png
ACRE_val_00*.png
ACRE_test_00*.png
scenes/
ACRE_train_00*.json
ACRE_val_00*.json
ACRE_test_00*.json
Each image file in the images folder has a corresponding scene description file in scenes with the same name (except for the extension).
Each ACRE problem is named after ACRE_{train/val/test}_{6_digit_problem_idx}_{2_digit_panel_idx}
Benchmarks archive 2025-07-28
No leaderboard in the archive resolves to this dataset.
Papers archive 2025-07-28
No paper in the archive has a leaderboard row on this dataset; the archive counts 15 papers for it but never published that list.
Dataset loaders archive 2025-07-28
No loader listed in the archive.
Tasks archive 2025-07-28
No task tagged in the archive.
License archive 2025-07-28
No licence recorded in the archive. Absence here is not a statement about the dataset's terms.
Modalities archive 2025-07-28
Languages archive 2025-07-28
No language tagged.
Variants archive 2025-07-28
- ACRE
1 variant name, as the archive lists them.
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