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---
license: apache-2.0
---
# RealFactBench
[![arXiv](https://img.shields.io/badge/arXiv-2506.12538-red)](https://arxiv.org/abs/2506.12538)
<p align="center">
<img src="overview.png"/>
</p>
We introduce RealFactBench, a comprehensive benchmark designed to assess the fact-checking capabilities of LLMs and MLLMs across diverse real-world tasks, including
Knowledge Validation, Rumor Detection, and Event Verification. RealFactBench consists of 6K high-quality claims drawn from authoritative sources, encompassing multimodal content and diverse domains. The dataset could be found at [DATASET](https://huggingface.co/datasets/kalends/RealFactBench)
## Citation
If you find our paper useful for your research, please consider giving a star and citation.
```BibTeX
@misc{yang2025realfactbench,
title={RealFactBench: A Benchmark for Evaluating Large Language Models in Real-World Fact-Checking},
author={Shuo Yang and Yuqin Dai and Guoqing Wang and Xinran Zheng and Jinfeng Xu and Jinze Li and Zhenzhe Ying and Weiqiang Wang and Edith C. H. Ngai},
year={2025},
eprint={2506.12538},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
```