---
language:
- ko
license: apache-2.0
size_categories:
- n<1K
task_categories:
- visual-question-answering
- question-answering
- image-text-to-text
---

# About this data
[KOFFVQA: An Objectively Evaluated Free-form VQA Benchmark for Large Vision-Language Models in the Korean Language](https://huggingface.co/papers/2503.23730)

KOFFVQA is a general-purpose VLM benchmark in the Korean language. For more information, refer to [our leaderboard page](https://huggingface.co/spaces/maum-ai/KOFFVQA-Leaderboard) and the official [evaluation code](https://github.com/maum-ai/KOFFVQA).

This contains the data for the benchmark consisting of images, their corresponding questions, and response grading criteria.  The benchmark focuses on free-form visual question answering, evaluating the ability of large vision-language models to generate comprehensive and accurate text responses to questions about images.

## Citation
```
@article{kim2025koffvqa,
  title={KOFFVQA: An Objectively Evaluated Free-form VQA Benchmark for Large Vision-Language Models in the Korean Language},
  author={Kim, Yoonshik and Jung, Jaeyoon},
  journal={arXiv preprint arXiv:2503.23730},
  year={2025}
}
```