README.md

---
language:
- en
pretty_name: "USA Astronomy and Astrophysics Organization (USAAAO) Open-ended Questionaire Dataset"
tags:
- astronomy
- astrophysics
- olympiad
- physics
- science
- stem
- multimodal
license: "other"
task_categories:
- question-answering
- visual-question-answering
---

# USA Astronomy and Astrophysics Organization (USAAAO) Open-ended Questionaire

This dataset contains structured question–answer pairs from the USAAAO (2017-2019), converted from pdf to LaTeX sources, into a machine-readable JSONL format.

The dataset includes:

- Short, medium, and long-form astrophysics problems
- Multi-part questions (grouped via `parent_id`)
- Full worked solutions
- Associated figures (JPEG images) where applicable

The goal of this dataset is to support evaluation and benchmarking of large language models (LLMs) on:

- Advanced scientific reasoning
- Mathematical derivation
- Multi-step physics problem solving
- Multimodal reasoning (text + figures)

---

## Dataset Structure

Each record contains:

- `id` – unique question or sub-question identifier  
- `parent_id` – shared ID for multi-part questions (null for single-part)  
- `year` – exam year  
- `part` – sub-part label (e.g., "a", "b")  
- `part_order` – ordering index for sub-parts  
- `question_type` – typically `"open-ended"`  
- `question_length` – `"short"`, `"medium"`, or `"long"`  
- `question` – problem statement  
- `answer` – full solution text  
- `image` – relative path to image (if applicable)  
- `caption` – figure caption (if applicable)

### Directory Layout

```
USAAAO_QA/
├── README.md
├── data/
│   ├── 2017.jsonl
│   ├── 2018.jsonl
│   └── 2019.jsonl
└── images/
    ├── 2017/
    │   ├── 2017-1.jpg
    │   ├── 2017-2.jpg
    │   └── ...
    ├── 2018/
    │   └── ...
    └── 2019/
        ├── 2019-1.jpg
        ├── 2019-2.jpg
        ├── 2019-3.jpg
        └── 2019-4.jpg
```
---

## Loading the Dataset

### If using the Hugging Face `datasets` library:

```python
from datasets import load_dataset

dataset = load_dataset("AstroMLab/USAAAO_QA")
```

### If loading locally from JSONL:

```python

from datasets import load_dataset

dataset = load_dataset("json", data_files="data/2019.jsonl")
```

## Citation

If you use this dataset, please cite: 

@misc{usaaao_dataset_2025,
  author = {AstroMLab},
  title = {USAAAO QA dataset},
  year = {2025},
}