glowol/RealXBench
RealXBench RealXBench is a comprehensive visual question answering benchmark dataset. The full dataset contains 300 high-quality image-question-answer triplets. Due to internal regulations, only a subset of 194 samples is released in this open-source version. Dataset Structure Each example contains: query: The question about the image (in English) answer: The ground truth answer(s), with multiple answers separated by "or" perception: Difficulty level for… See the full description on the dataset page: https://huggingface.co/datasets/glowol/RealXBench.
RealXBench
RealXBench is a comprehensive visual question answering benchmark dataset. The full dataset contains 300 high-quality image-question-answer triplets. Due to internal regulations, only a subset of 194 samples is released in this open-source version.
Dataset Structure
Each example contains:
- query: The question about the image (in English)
- answer: The ground truth answer(s), with multiple answers separated by "or"
- perception: Difficulty level for perception task (1 if required, 0 otherwise)
- search: Difficulty level for search task (1 if required, 0 otherwise)
- reason: Difficulty level for reasoning task (1 if required, 0 otherwise)
- image: The corresponding image file
Usage
from datasets import load_dataset
dataset = load_dataset("glowol/RealXBench")Citation
If you use this dataset, please cite:
@article{deepEyesV2,
title={DeepEyesV2: Toward Agentic Multimodal Model},
author={Jack Hong and Chenxiao Zhao and ChengLin Zhu and Weiheng Lu and Guohai Xu and Xing Yu},
journal={arXiv preprint arXiv:2511.05271},
year={2025},
url={https://arxiv.org/abs/2511.05271}
}