---
license: cc-by-4.0
task_categories:
- question-answering
language:
- en
size_categories:
- 10M<n<100M
---




# Mechanical Reasoning

**Mechanical Reasoning** is a multimodal benchmark designed to evaluate mechanical and physical reasoning in large vision-language models (VLMs). This dataset is introduced in the paper:

> **Probing Mechanical Reasoning in Large Vision Language Models**  
> [arXiv:2410.00318](https://doi.org/10.48550/arXiv.2410.00318)

It is part of the [Grow AI Like a Child](https://huggingface.co/grow-ai-like-a-child) benchmark initiative, which explores structured, curriculum-aligned evaluation for embodied intelligence.

---

## 🧠 Dataset Overview

This dataset focuses on **mechanical reasoning** grounded in either static images or short video clips. Each item presents a physical scenario and poses a question requiring spatial, causal, or commonsense understanding.

The dataset contains:

- **148 samples**
- **Two modalities**: `image` or `video`
- **Two question formats**: `multiple-choice` (MC) or `true/false` (TF)

---

## 🧩 Reasoning Types

The questions span a variety of physical reasoning challenges:

- Gear and pulley systems
- Fluid and buoyancy dynamics
- Torque and balance
- Conveyor motion
- Mechanical advantage
- Temporal prediction and causality

---

## 📁 Dataset Format

Each sample includes:

| Field            | Description |
|------------------|-------------|
| `index`          | Unique ID (e.g., `d0001`) |
| `media_type`     | Either `image` or `video` |
| `media`          | Local file name (e.g., `d0001.png`, `d0131.mov`) |
| `question_type`  | Either `MC` or `TF` |
| `sec_label`      | Integer from 1 to 6 (see section mapping below) |
| `question`       | Natural language question with choices embedded (if MC) |
| `correct_answer` | The ground-truth answer (e.g., `A`, `B`, `Yes`, `No`) |

### 🔢 `sec_label` Categories

| Label | Category             |
|-------|----------------------|
| 1     | System Ability       |
| 2     | Pulley Systems       |
| 3     | Gears & Rotations    |
| 4     | Leverage Principle   |
| 5     | Inertia and Motion   |
| 6     | Fluid Mechanics      |

---

## 📂 Folder Structure

```
data/
├── data.csv
├── images/
│   ├── *.png
│   └── metadata.jsonl
├── videos/
│   ├── *.mov / *.mp4
│   └── metadata.jsonl
```

- The `metadata.jsonl` files store structured sample entries.
- For video samples, `file_name` in metadata is mapped to `.png` format to avoid embedding issues on Dataset Viewer.

---

## 💡 Example

```json
{
  "file_name": "d0001.png",
  "media_type": "image",
  "question_type": "MC",
  "sec_label": 6,
  "question": "In which direction is the leaking cylinder moving in the water in the picture? A. up; B. down",
  "correct_answer": "B"
}
```

---

## 📚 Citation

If you use this dataset, please cite:

```bibtex
@misc{sun2025probingmechanicalreasoninglarge,
      title={Probing Mechanical Reasoning in Large Vision Language Models}, 
      author={Haoran Sun and Qingying Gao and Haiyun Lyu and Dezhi Luo and Yijiang Li and Hokin Deng},
      year={2025},
      eprint={2410.00318},
      archivePrefix={arXiv},
      primaryClass={cs.AI},
      url={https://arxiv.org/abs/2410.00318}, 
}
```

---



## 🤝 Acknowledgments

This dataset is developed by the Grow AI Like a Child community.