C3B / README.md
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---
license: cc-by-4.0
language:
- ja
- en
- de
- es
- ru
- th
task_categories:
- visual-question-answering
- image-text-to-text
- text-generation
tags:
- multilingual
- image-text
- cultural-awareness
- comics
- manga
- benchmark
- multimodal
---
**English** | [简体中文](README.zh.md)
---
# C³B: Comics Cross-Cultural Benchmark
**Culture In a Frame: C³B as a Comic-Based Benchmark for Multimodal Cultural Awareness**
[![Paper](https://img.shields.io/badge/Paper-OpenReview-blue)](https://openreview.net/forum?id=jvPdTOSTVl)
*ICLR 2026*
---
## About C³B
C³B (**C**omics **C**ross-**C**ultural **B**enchmark) is a **multicultural, multitask, and multilingual** benchmark for evaluating cultural awareness capabilities of Multimodal Large Language Models (MLLMs).
- **Progressive task difficulty**: From basic visual recognition, to higher-level cultural conflict understanding, to cultural content generation.
- **Comic-based**: Built on manga/comic images; comics better reflect cross-cultural narratives and conflict scenarios than single-culture real-world images.
- **Scale**: Over **2,000 images** and **18,000+ QA pairs**, covering three tasks of increasing difficulty.
**Task overview**
| Type | Description |
|------|-------------|
| Basic visual recognition | Recognize and understand culture-related visual elements in comic panels |
| Cultural conflict understanding | Understand cross-cultural conflicts, cultural symbols, and narrative intent |
| Cultural content generation | Generate culture-related descriptions or stories from given settings or images |
**Authors**: Yuchen Song, Andong Chen, Wenxin Zhu, Kehai Chen, Xuefeng Bai, Muyun Yang, Tiejun Zhao
---
## Data Format
This repository contains C³B annotations and task data in the following structure:
**task3/** — Multilingual translation/alignment
- Files: `task3.ja-en.json`, `task3.ja-de.json`, `task3.ja-es.json`, `task3.ja-ru.json`, `task3.ja-th.json`, etc.
- Fields: `manga_name`, `page_index`, `src` (source text), `tgt` (target text).
- Each item is a sentence or phrase pair for translation or alignment between languages.
**task12/** — Cultural content generation (Task 1 and Task 2)
- task12 contains the data for **Task 1** and **Task 2** of the benchmark.
- `task12.json`: structured data for generation-style evaluation.
**task12.json fields** (each item in the JSON array):
| Field | Type | Description |
|-------|------|-------------|
| `file_name` | string | Image filename (e.g. `0.png`) |
| `Q1` | object | First question: multiple-choice options as keys A–E (e.g. region/culture names) |
| `A1` | string | Answer to Q1 (e.g. one or more option letters such as `"B C E"`) |
| `Q2` | object | Second question: options A–E (e.g. lists of scene elements) |
| `A2` | string | Answer to Q2 (e.g. one option letter such as `"D"`) |
| `A3` | string | Third answer (e.g. `"Yes"` / `"No"`) |
| `A4` | list of strings | Cultural conflict descriptions (text explanations of conflicts in the image) |
Refer to the actual data files in each task directory for exact schemas and usage.
---
## Obtaining Manga109
Part of C³B is built on [Manga109](http://www.manga109.org/en/). For how to obtain the dataset (academic Manga109 or commercial subset Manga109-s), see the official site: [Manga109 download](http://www.manga109.org/en/download.html) and [Manga109-s](http://www.manga109.org/en/download_s.html). The dataset is also available on Hugging Face: [hal-utokyo/Manga109](https://huggingface.co/datasets/hal-utokyo/Manga109), [hal-utokyo/Manga109-s](https://huggingface.co/datasets/hal-utokyo/Manga109-s).
---
## Citation
If you use C³B, please cite:
```bibtex
@inproceedings{song2026c3b,
title={Culture In a Frame: C³B as a Comic-Based Benchmark for Multimodal Cultural Awareness},
author={Song, Yuchen and Chen, Andong and Zhu, Wenxin and Chen, Kehai and Bai, Xuefeng and Yang, Muyun and Zhao, Tiejun},
booktitle={International Conference on Learning Representations (ICLR)},
year={2026},
url={https://openreview.net/forum?id=jvPdTOSTVl}
}
```
When using Manga109 (or Manga109-s) data, please also cite the recommended papers:
```bibtex
@article{mtap_matsui_2017,
author = {Yusuke Matsui and Kota Ito and Yuji Aramaki and Azuma Fujimoto and Toru Ogawa and Toshihiko Yamasaki and Kiyoharu Aizawa},
title = {Sketch-based Manga Retrieval using Manga109 Dataset},
journal = {Multimedia Tools and Applications},
volume = {76}, number = {20}, pages = {21811--21838},
year = {2017}, doi = {10.1007/s11042-016-4020-z}
}
@article{multimedia_aizawa_2020,
author = {Kiyoharu Aizawa and Azuma Fujimoto and Atsushi Otsubo and Toru Ogawa and Yusuke Matsui and Koki Tsubota and Hikaru Ikuta},
title = {Building a Manga Dataset ``Manga109'' with Annotations for Multimedia Applications},
journal = {IEEE MultiMedia},
volume = {27}, number = {2}, pages = {8--18},
year = {2020}, doi = {10.1109/mmul.2020.2987895}
}
```
---
## License
### C³B
C³B (this benchmark, including annotations and task data in this repository) is released under **CC BY 4.0** ([Creative Commons Attribution 4.0 International](https://creativecommons.org/licenses/by/4.0/)). You may share and adapt the material with appropriate credit and under the same license terms.
### Manga109 / Manga109-s
- **Manga109**: Permitted only for **academic use by non-profit organizations**. Redistribution to third parties is not permitted. Use is subject to the terms on the [official Manga109 site](http://www.manga109.org/en/download.html); the University of Tokyo and the manga authors are not liable for use of the dataset.
- **Manga109-s**: A subset of 87 titles with permission for use by **commercial organizations** under the conditions on the [Manga109-s page](http://www.manga109.org/en/download_s.html) (e.g., limits on publishing whole pages, no redistribution, proper attribution). All other terms and disclaimers apply as stated there.
Use of Manga109 or Manga109-s is governed solely by the University of Tokyo laboratory and the official Manga109 website; users must comply with those terms and assume responsibility accordingly.