cmudrc/OpenSeeSimE-Structural-Mini

---
dataset_info:
features:
- name: file_name
dtype: string
- name: source_file
dtype: string
- name: question
dtype: string
- name: question_type
dtype: string
- name: question_id
dtype: int32
- name: answer
dtype: string
- name: answer_choices
list: string
- name: correct_choice_idx
dtype: int32
- name: image
dtype: image
- name: video
dtype: video
- name: media_type
dtype: string
splits:
- name: test
num_examples: 1120
configs:
- config_name: default
data_files:
- split: test
path: data/test-*
license: mit
task_categories:
- visual-question-answering
language:
- en
size_categories:
- 1K<n<10K
tags:
- engineering
- simulation
- stratified-subset
---

# OpenSeeSimE-Structural-Mini

A **stratified 1% subset** of [`cmudrc/OpenSeeSimE-Structural`](https://huggingface.co/datasets/cmudrc/OpenSeeSimE-Structural) for evaluating vision-language models at a reduced compute footprint while preserving the joint distribution of simulation type, question type, media type, and question id.

## Subset Provenance

- **Parent dataset**: [`cmudrc/OpenSeeSimE-Structural`](https://huggingface.co/datasets/cmudrc/OpenSeeSimE-Structural) (102,678 rows total)
- **Rows in this subset**: **1,120** (1.09% of parent)
- **Source classes**: `Beams`, `Dog Bone`, `Hip Implant`, `Pressure Vessel`, `Wall Bracket`
- **Parquet shards**: 1 | **Storage**: ~1.73 GB
- **Sampling**: per-stratum shuffle with `numpy.random.default_rng(42)`, then take `ceil(n * fraction)` from each stratum. Any non-empty stratum contributes at least 1 row.
- **Strata**: `(source_file, question_type, media_type, question_id)` — all four jointly.
- **Nesting**: the 1% subset is a literal subset of the 10% subset (same shuffled prefix is taken for every fraction).

## Composition

### By `source_file`

| source_file | rows | pct |
|:----------------|-------:|------:|
| Beams | 240 | 21.43 |
| Dog Bone | 220 | 19.64 |
| Hip Implant | 220 | 19.64 |
| Pressure Vessel | 220 | 19.64 |
| Wall Bracket | 220 | 19.64 |

### By `media_type`

| media_type | rows |
|:-------------|-------:|
| image | 560 |
| video | 560 |

### By `(source_file, question_type)`

| source_file | Binary | Multiple Choice | Spatial | Total |
|:----------------|---------:|------------------:|----------:|--------:|
| Beams | 72 | 120 | 48 | 240 |
| Dog Bone | 66 | 110 | 44 | 220 |
| Hip Implant | 66 | 110 | 44 | 220 |
| Pressure Vessel | 66 | 110 | 44 | 220 |
| Wall Bracket | 66 | 110 | 44 | 220 |

## Feature Schema

Identical to the parent dataset. See [`cmudrc/OpenSeeSimE-Structural`](https://huggingface.co/datasets/cmudrc/OpenSeeSimE-Structural) for full documentation of simulation generation, ground-truth extraction, preprocessing, limitations, and intended use.

```python
{
'file_name': str, # Unique identifier
'source_file': str, # Base simulation model
'question': str, # Question text
'question_type': str, # 'Binary', 'Multiple Choice', 'Spatial'
'question_id': int, # Question identifier (1-20)
'answer': str, # Ground truth answer
'answer_choices': list[str], # Options
'correct_choice_idx': int, # Index of correct answer
'image': Image, # PIL Image (1920x1440) or null for video rows
'video': Video, # Video bytes or null for image rows
'media_type': str, # 'image' or 'video'
}
```

## Intended Use

- Benchmark evaluation of vision-language models on engineering simulation question answering at reduced compute cost
- Smoke-testing of evaluation pipelines before running the full benchmark
- Comparative studies where storage or bandwidth constraints matter

## License

MIT — same as parent. Free for academic and commercial use with attribution.

## Citation

```bibtex
@article{ezemba2024opensesime,
title={OpenSeeSimE: A Large-Scale Benchmark to Assess Vision-Language Model Question Answering Capabilities in Engineering Simulations},
author={Ezemba, Jessica and Pohl, Jason and Tucker, Conrad and McComb, Christopher},
year={2025}
}
```

## Contact

**Jessica Ezemba** — [e-mail]
Department of Mechanical Engineering, Carnegie Mellon University