---
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.