- Description:
 
Multiple-choice ethical questions (with desirable and undesirable answers) based on situations inspired from Science Fiction literature (validation set).
Homepage: https://asimov-benchmark.github.io/
Source code:
tfds.robotics.asimov.AsimovDilemmasScifiValVersions:
0.1.0(default): Initial release.
Download size:
Unknown sizeDataset size:
1.97 MiBAuto-cached (documentation): Yes
Splits:
| Split | Examples | 
|---|---|
'val' | 
51 | 
- Feature structure:
 
FeaturesDict({
    'acting_character': Text(shape=(), dtype=string),
    'characters': Text(shape=(), dtype=string),
    'possible_actions': Sequence({
        'action': Text(shape=(), dtype=string),
        'is_original_scifi_decision': bool,
        'key': Text(shape=(), dtype=string),
        'undesirable_groundtruth_answer': bool,
    }),
    'prompt_with_constitution': Text(shape=(), dtype=string),
    'prompt_with_constitution_antijailbreak': Text(shape=(), dtype=string),
    'prompt_with_constitution_antijailbreak_adversary': Text(shape=(), dtype=string),
    'prompt_with_constitution_antijailbreak_adversary_parts': Sequence(Text(shape=(), dtype=string)),
    'prompt_with_constitution_antijailbreak_parts': Sequence(Text(shape=(), dtype=string)),
    'prompt_with_constitution_parts': Sequence(Text(shape=(), dtype=string)),
    'prompt_without_constitution': Text(shape=(), dtype=string),
    'prompt_without_constitution_parts': Sequence(Text(shape=(), dtype=string)),
    'reference_domain': Text(shape=(), dtype=string),
    'reference_moment': Text(shape=(), dtype=string),
    'reference_scifi': Text(shape=(), dtype=string),
})
- Feature documentation:
 
| Feature | Class | Shape | Dtype | Description | 
|---|---|---|---|---|
| FeaturesDict | ||||
| acting_character | Text | string | ||
| characters | Text | string | ||
| possible_actions | Sequence | |||
| possible_actions/action | Text | string | ||
| possible_actions/is_original_scifi_decision | Tensor | bool | ||
| possible_actions/key | Text | string | ||
| possible_actions/undesirable_groundtruth_answer | Tensor | bool | ||
| prompt_with_constitution | Text | string | ||
| prompt_with_constitution_antijailbreak | Text | string | ||
| prompt_with_constitution_antijailbreak_adversary | Text | string | ||
| prompt_with_constitution_antijailbreak_adversary_parts | Sequence(Text) | (None,) | string | |
| prompt_with_constitution_antijailbreak_parts | Sequence(Text) | (None,) | string | |
| prompt_with_constitution_parts | Sequence(Text) | (None,) | string | |
| prompt_without_constitution | Text | string | ||
| prompt_without_constitution_parts | Sequence(Text) | (None,) | string | |
| reference_domain | Text | string | ||
| reference_moment | Text | string | ||
| reference_scifi | Text | string | 
Supervised keys (See
as_superviseddoc):NoneFigure (tfds.show_examples): Not supported.
Examples (tfds.as_dataframe):
- Citation:
 
@article{sermanet2025asimov,
  author    = {Pierre Sermanet and Anirudha Majumdar and Alex Irpan and Dmitry Kalashnikov and Vikas Sindhwani},
  title     = {Generating Robot Constitutions & Benchmarks for Semantic Safety},
  journal   = {arXiv preprint arXiv:2503.08663},
  url       = {https://arxiv.org/abs/2503.08663},
  year      = {2025},
}