Datasets:
image imagewidth (px) 32 32 | concepts list | label class label 2
classes | label_name stringclasses 2
values |
|---|---|---|---|
[
1,
0,
1,
1,
1,
1,
1
] | 1glorp | glorp | |
[
0,
1,
0,
0,
0,
0,
1
] | 1glorp | glorp | |
[
1,
1,
1,
0,
1,
1,
0
] | 0drent | drent | |
[
1,
0,
1,
0,
0,
1,
1
] | 1glorp | glorp | |
[
1,
1,
0,
0,
0,
0,
0
] | 1glorp | glorp | |
[
0,
0,
0,
1,
0,
0,
0
] | 1glorp | glorp | |
[
0,
1,
0,
1,
1,
1,
0
] | 1glorp | glorp | |
[
0,
0,
0,
0,
0,
1,
0
] | 1glorp | glorp | |
[
0,
0,
0,
1,
0,
1,
0
] | 1glorp | glorp | |
[
0,
0,
0,
1,
0,
1,
0
] | 1glorp | glorp | |
[
1,
0,
1,
0,
1,
0,
1
] | 1glorp | glorp | |
[
1,
1,
0,
0,
1,
0,
1
] | 1glorp | glorp | |
[
1,
1,
0,
0,
1,
1,
0
] | 1glorp | glorp | |
[
1,
0,
0,
1,
0,
1,
0
] | 1glorp | glorp | |
[
1,
0,
1,
1,
1,
0,
0
] | 1glorp | glorp | |
[
0,
0,
1,
0,
1,
0,
0
] | 1glorp | glorp | |
[
1,
0,
0,
1,
0,
1,
0
] | 1glorp | glorp | |
[
1,
1,
0,
0,
0,
1,
1
] | 1glorp | glorp | |
[
1,
0,
1,
1,
1,
1,
0
] | 0drent | drent | |
[
1,
1,
0,
1,
0,
0,
0
] | 1glorp | glorp | |
[
1,
1,
0,
0,
0,
1,
1
] | 1glorp | glorp | |
[
1,
0,
0,
0,
1,
1,
1
] | 1glorp | glorp | |
[
0,
1,
1,
1,
0,
1,
1
] | 1glorp | glorp | |
[
0,
0,
1,
0,
1,
1,
0
] | 0drent | drent | |
[
1,
0,
0,
0,
0,
0,
1
] | 1glorp | glorp | |
[
0,
1,
0,
0,
0,
1,
1
] | 1glorp | glorp | |
[
0,
0,
1,
0,
1,
0,
1
] | 1glorp | glorp | |
[
0,
0,
1,
0,
0,
1,
1
] | 1glorp | glorp | |
[
0,
1,
1,
1,
0,
1,
1
] | 1glorp | glorp | |
[
0,
1,
1,
1,
0,
0,
0
] | 1glorp | glorp | |
[
0,
0,
1,
0,
0,
1,
0
] | 0drent | drent | |
[
0,
0,
0,
0,
0,
1,
0
] | 1glorp | glorp | |
[
1,
0,
1,
1,
1,
1,
0
] | 0drent | drent | |
[
1,
0,
1,
1,
1,
0,
0
] | 1glorp | glorp | |
[
1,
1,
0,
0,
0,
1,
1
] | 1glorp | glorp | |
[
0,
1,
1,
0,
1,
0,
0
] | 1glorp | glorp | |
[
0,
0,
1,
1,
1,
1,
0
] | 0drent | drent | |
[
1,
0,
1,
1,
0,
0,
1
] | 1glorp | glorp | |
[
1,
0,
0,
1,
0,
1,
0
] | 1glorp | glorp | |
[
1,
0,
0,
1,
0,
1,
1
] | 1glorp | glorp | |
[
1,
1,
1,
1,
0,
0,
1
] | 1glorp | glorp | |
[
0,
0,
0,
0,
0,
1,
1
] | 1glorp | glorp | |
[
0,
1,
1,
0,
0,
1,
1
] | 1glorp | glorp | |
[
0,
1,
1,
1,
1,
0,
0
] | 1glorp | glorp | |
[
0,
0,
0,
1,
1,
0,
0
] | 1glorp | glorp | |
[
1,
0,
1,
1,
1,
1,
0
] | 0drent | drent | |
[
1,
0,
1,
1,
1,
1,
0
] | 0drent | drent | |
[
0,
0,
1,
0,
0,
1,
1
] | 1glorp | glorp | |
[
1,
0,
0,
0,
0,
0,
0
] | 1glorp | glorp | |
[
1,
1,
1,
0,
0,
1,
0
] | 0drent | drent | |
[
1,
0,
1,
1,
0,
1,
0
] | 0drent | drent | |
[
0,
1,
1,
0,
0,
0,
1
] | 1glorp | glorp | |
[
0,
1,
0,
0,
0,
0,
1
] | 1glorp | glorp | |
[
0,
1,
0,
1,
0,
1,
0
] | 1glorp | glorp | |
[
0,
1,
1,
0,
0,
1,
0
] | 0drent | drent | |
[
0,
1,
1,
0,
0,
0,
0
] | 1glorp | glorp | |
[
1,
1,
0,
1,
0,
0,
0
] | 1glorp | glorp | |
[
1,
1,
0,
1,
1,
0,
1
] | 1glorp | glorp | |
[
1,
0,
1,
1,
1,
0,
1
] | 1glorp | glorp | |
[
0,
1,
1,
1,
1,
1,
1
] | 1glorp | glorp | |
[
0,
0,
0,
0,
0,
1,
1
] | 1glorp | glorp | |
[
0,
1,
0,
1,
0,
0,
0
] | 1glorp | glorp | |
[
0,
0,
1,
1,
1,
1,
1
] | 1glorp | glorp | |
[
0,
0,
1,
1,
1,
1,
1
] | 1glorp | glorp | |
[
0,
1,
1,
0,
0,
0,
1
] | 1glorp | glorp | |
[
1,
1,
0,
0,
0,
1,
1
] | 1glorp | glorp | |
[
0,
0,
0,
0,
0,
1,
1
] | 1glorp | glorp | |
[
1,
0,
0,
0,
1,
1,
1
] | 1glorp | glorp | |
[
0,
0,
0,
0,
1,
0,
1
] | 1glorp | glorp | |
[
0,
0,
1,
0,
1,
1,
0
] | 0drent | drent | |
[
1,
1,
1,
1,
0,
0,
1
] | 1glorp | glorp | |
[
0,
1,
1,
1,
1,
0,
1
] | 1glorp | glorp | |
[
0,
0,
1,
1,
1,
0,
1
] | 1glorp | glorp | |
[
1,
0,
0,
0,
0,
1,
0
] | 1glorp | glorp | |
[
1,
0,
0,
0,
1,
1,
1
] | 1glorp | glorp | |
[
0,
0,
0,
1,
1,
1,
0
] | 1glorp | glorp | |
[
0,
0,
1,
1,
0,
0,
0
] | 1glorp | glorp | |
[
1,
1,
0,
0,
1,
0,
1
] | 1glorp | glorp | |
[
1,
0,
0,
1,
0,
0,
0
] | 1glorp | glorp | |
[
0,
0,
0,
1,
1,
0,
0
] | 1glorp | glorp | |
[
0,
0,
0,
1,
0,
1,
1
] | 1glorp | glorp | |
[
0,
1,
0,
1,
1,
1,
0
] | 1glorp | glorp | |
[
0,
1,
1,
1,
1,
1,
1
] | 1glorp | glorp | |
[
1,
0,
0,
0,
1,
1,
0
] | 1glorp | glorp | |
[
1,
0,
1,
1,
1,
0,
0
] | 1glorp | glorp | |
[
0,
1,
1,
1,
1,
1,
1
] | 1glorp | glorp | |
[
1,
0,
0,
0,
1,
0,
0
] | 1glorp | glorp | |
[
1,
0,
1,
0,
1,
1,
0
] | 0drent | drent | |
[
0,
1,
1,
0,
0,
1,
1
] | 1glorp | glorp | |
[
0,
0,
0,
0,
0,
1,
0
] | 1glorp | glorp | |
[
1,
1,
0,
0,
1,
1,
1
] | 1glorp | glorp | |
[
0,
1,
1,
0,
0,
1,
1
] | 1glorp | glorp | |
[
0,
0,
0,
0,
0,
0,
1
] | 1glorp | glorp | |
[
1,
0,
0,
1,
0,
0,
0
] | 1glorp | glorp | |
[
1,
0,
0,
0,
1,
1,
0
] | 1glorp | glorp | |
[
0,
1,
0,
0,
0,
0,
1
] | 1glorp | glorp | |
[
0,
1,
1,
1,
1,
0,
0
] | 1glorp | glorp | |
[
1,
0,
1,
0,
1,
0,
0
] | 1glorp | glorp | |
[
0,
0,
0,
1,
0,
1,
1
] | 1glorp | glorp | |
[
0,
1,
0,
1,
0,
0,
1
] | 1glorp | glorp |
End of preview. Expand in Data Studio
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 DatasetGenerator
dataset = DatasetGenerator(seed=1014, concept_preset="ground_truth").generate()
📓 Quickstart notebook — load from the Hub → train a CBM → run oracle interventions, end-to-end in one notebook.
Quick start (datasets library)
from datasets import load_dataset
ds = load_dataset("juliannski/robots-true-concepts")
row = ds["train"][0]
row["image"] # PIL.Image (32x32 RGBA)
row["concepts"] # 7-dim binary list, ordered by concept_names below
row["label"] # 0 or 1
row["label_name"] # "drent" or "glorp"
Schema
| Field | Type | Notes |
|---|---|---|
image |
datasets.Image() |
32x32 RGBA PNG, embedded |
concepts |
Sequence(int8, length=7) |
binary; index order = concept_names below |
label |
ClassLabel("drent", "glorp") |
|
label_name |
string |
display alias for label |
concept_names (column order in concepts):
["head_shape", "body_shape", "has_knees", "has_antennae",
"ears_shape", "mouth_type", "foot_shape"]
Splits
| Split | n |
|---|---|
train |
16,576 |
validation |
4,144 |
test |
10,000 |
Stratified on label; seed=1014. Class distribution is intentionally imbalanced (~87% glorp) per the labeling rule.
Companion datasets
juliannski/robots-human-concepts— same 30,720 robots, finer-grained 12-concept labeling that splitsfoot_shapeinto 6 visible subtypes.juliannski/sudoku— sudoku validation benchmark with 27 cell-digit concepts.
License
MIT.
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