| --- |
| license: mit |
| task_categories: |
| - visual-question-answering |
| - video-classification |
| - robotics |
| language: |
| - en |
| tags: |
| - physics |
| - physical-reasoning |
| - world-models |
| - embodied-ai |
| - genesis |
| - simulation |
| - counterfactual |
| pretty_name: Genesis Physical Intervention Benchmark |
| --- |
| |
| # Genesis Physical Intervention Benchmark |
|
|
| This dataset contains controlled Genesis simulations for evaluating physically viable world models in embodied AI settings. |
|
|
| Repository: `sarahnator/genesis-physical-interventions` |
| Visibility at upload time: `private` |
|
|
| ## Scenes |
|
|
| - Ramp-cup-water |
| - Robotic pour |
| - Pendulum |
|
|
| ## Task Types |
|
|
| - Single-rollout outcome prediction |
| - Scalar physical prediction |
| - Inverse parameter prediction |
| - Pairwise counterfactual comparison |
|
|
| ## Files |
|
|
| ```text |
| data/vlm_entries.jsonl |
| data/manifest_all.jsonl |
| scenes/ |
| artifacts/frames/ |
| artifacts/videos/ |
| artifacts/trajectories/ |
| ``` |
|
|
| ## Dataset Size Summary |
|
|
| Number of VLM entries: `111` |
|
|
| Entries by scene: |
|
|
| ```json |
| { |
| "pendulum": 38, |
| "ramp_cup": 31, |
| "robotic_pour": 42 |
| } |
| ``` |
|
|
| Entries by query type: |
|
|
| ```json |
| { |
| "binary_outcome": 53, |
| "inverse_parameter_prediction": 12, |
| "pairwise_counterfactual": 15, |
| "scalar_prediction": 31 |
| } |
| ``` |
|
|
| ## Loading Example |
|
|
| ```python |
| from datasets import load_dataset |
| ds = load_dataset("sarahnator/genesis-physical-interventions", data_files="data/vlm_entries.jsonl", split="train") |
| print(ds[0]) |
| ``` |
|
|
| ## Limitations |
|
|
| - Labels are simulator-derived, not real-world measurements. |
| - Some labels use proxies, such as receiver_fraction for robotic pouring. |
| - This is a research benchmark for physical reasoning, not a complete real-world robotics benchmark. |
| |
