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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.

sourceHugging Faceapache-2.0updated 11mo agoView on Hugging Face
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Dataset Card

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

python
from datasets import load_dataset

dataset = load_dataset("glowol/RealXBench")

Citation

If you use this dataset, please cite:

bibtex
@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}
}