What is MMCV?

MMCV is a multimodal claim verification dataset featuring natural, multi-hop claims, with strong supervision for supporting facts to enable more explainable fact-checking systems. It is collected by a team of NLP researchers at Illinois Institute of Technology, and Emory University.

For more details about MMCV, please refer to our paper:

(Wang et al. 2024)

Getting started

MMCV is distributed under a CC BY-SA 4.0 License. The combined dataset as well as for each hop can be downloaded below.

Combined (14.3MB)

1 hop (5.03MB)

2 hop (8.18MB)

3 hop (726KB)

4 hop (405KB)

A more comprehensive summary about data download, preprocessing, baseline model training, and evaluation is included in our GitHub repository.

Evaluation

As explained in the Sec 5 of the paper, zero-shot multimodal claim verification using various MLLMs under two settings. In the closed-book setting, the model does not retrieve information from external knowledge sources and must rely on its parametric (internal) knowledge to verify the claim. In the open-book setting, the model is provided with a set of gold evidence. Please refer to our evaluation script provided below for calculating the performance metrics.

Evaluation script

Citation

If you use MMCV in your research, please cite our paper with the following BibTeX entry

@inproceedings{wang2024piecing,
  title={Piecing It All Together: Verifying Multi-Hop Multimodal Claims},
  author={Haoran Wang and Aman Rangapur and Xiongxiao Xu and Yueqing Liang and Haroon Gharwi and Carl Yang and Kai Shu.},
  booktitle={Proceedings of the 31st International Conference on Computational Linguistics},
  year={2025}
}