---
dataset_info:
  features:
  - name: image_path
    dtype: string
  - name: food1_id
    dtype: int64
  - name: food1_name
    dtype: string
  - name: food1_country
    dtype: string
  - name: food1_continent
    dtype: string
  - name: food2_id
    dtype: int64
  - name: food2_name
    dtype: string
  - name: food2_country
    dtype: string
  - name: food2_continent
    dtype: string
  - name: background_continent
    dtype: string
  - name: background_country
    dtype: string
  - name: background_name
    dtype: string
  - name: image
    dtype: image
  splits:
  - name: SF
    num_bytes: 236917019.0
    num_examples: 247
  - name: MF
    num_bytes: 1783068852.0
    num_examples: 949
  - name: MFB_landmark
    num_bytes: 3089759632.48
    num_examples: 4740
  - name: MFB_street
    num_bytes: 2192091002.305
    num_examples: 4745
  - name: SFB_landmark
    num_bytes: 4952856483.5
    num_examples: 6175
  - name: SFB_street
    num_bytes: 3326863971.425
    num_examples: 6175
  download_size: 15284488007
  dataset_size: 15581556960.71
configs:
- config_name: default
  data_files:
  - split: SF
    path: data/SF-*
  - split: MF
    path: data/MF-*
  - split: MFB_landmark
    path: data/MFB_landmark-*
  - split: MFB_street
    path: data/MFB_street-*
  - split: SFB_landmark
    path: data/SFB_landmark-*
  - split: SFB_street
    path: data/SFB_street-*
---

# CultureMix Dataset Assets

This repository hosts the image assets and metadata that back the official **CultureMix** benchmark introduced in “World in a Frame: Understanding Culture Mixing as a New Challenge for Vision-Language Models” [CultureMix](https://arxiv.org/pdf/2511.22787). The dataset probes how LVLMs behave when multiple cultural cues (foods, landmarks, or street scenes) co-exist in a single frame.

## Directory Layout

```
datasets/final/
├── SF/                # Single-food crops rendered on white background
├── MF/                # Two-food compositions (food-only)
├── MFB_landmark/      # Two foods + landmark background
├── MFB_street/        # Two foods + street background
├── SFB_landmark/      # Single food + landmark background
├── SFB_street/        # Single food + street background
└── metadata/          # CSV manifests describing every split
    ├── sf.csv
    ├── mf.csv
    ├── mfb_landmark.csv
    ├── mfb_street.csv
    ├── sfb_landmark.csv
    └── sfb_street.csv
```

Each filename encodes the food IDs (and background slug for *_landmark/*_street variants). The CSVs mirror those filenames and append the textual labels needed for evaluation or model training.

## Metadata Schema

Every CSV under `datasets/final/metadata/` exposes the same column set to keep Hugging Face splits aligned:

| Column | Description |
| --- | --- |
| `image_path` | Relative path under `datasets/final/` |
| `image` | |
| `food1_id`, `food1_name`, `food1_country`, `food1_continent` | Netadata for the left food |
| `food2_id`, `food2_name`, `food2_country`, `food2_continent` | etadata for the right food (empty/`None` for single-food splits) |
| `background_continent`, `background_country`, `background_name` | Background label (empty when not applicable) |

## Citation

Please cite the CultureMix paper when using these assets:

```
@article{kim2025culturemix,
  title={World in a Frame: Understanding Culture Mixing as a New Challenge for Vision-Language Models},
  author={Kim, Eunsu and Park, Junyeong and An, Na Min and Kim, Junseong and Patel, Hitesh Laxmichand and Jin, Jiho and Kruk, Julia and Agarwal, Amit and Panda, Srikant and Ilasariya, Fenal Ashokbhai and Shim, Hyunjung and Oh, Alice},
  year={2025},
  journal={arXiv preprint arXiv:2511.22787}
}
```

---

For questions about data corrections or additional releases, please reach out via email (kes0317@kaist.ac.kr).