datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Concept_Targeted_Causal_Images
Dataset Card for Concept-Targeted Causal Images
Dataset Summary
Concept-Targeted Causal Images is a concept-centric image dataset designed for studying causal visual representations in the brain. For each concept, the dataset contains three complementary image types:
Positive images that clearly depict the target concept
Semantic negatives that are visually or semantically related to the concept, but do not satisfy it
Counterfactual edits created by editing… See the full description on the dataset page: https://huggingface.co/datasets/BrainCause/Concept_Targeted_Causal_Images.robots-human-concepts
Robots — Human Concepts
Synthetic benchmark for evaluating Concept Bottleneck Models (CBMs) under finer-grained, human-annotated concepts. Same underlying robot images and labels as juliannski/robots-true-concepts, but the foot_shape ground-truth concept is replaced by 6 one-hot subtypes that a human annotator would actually see, modelling concept specification mismatch between annotators and the latent labeling rule.
Generated from
This dataset is the exact… See the full description on the dataset page: https://huggingface.co/datasets/juliannski/robots-human-concepts.robots-true-concepts
Robots — True Concepts
Synthetic benchmark for evaluating Concept Bottleneck Models (CBMs). Robot images are generated deterministically with pycairo; binary labels follow a known disjunction-style rule over the 7 ground-truth concepts.
Generated from
This dataset is the exact output of the concept-benchmark Python package — seed and config are pinned for bit-identical reproduction.
# pip install concept-benchmark==0.3.1
from concept_benchmark.robots import… See the full description on the dataset page: https://huggingface.co/datasets/juliannski/robots-true-concepts.