File size: 3,876 Bytes
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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).
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