📋 End-to-End Multimodal Fact-Checking and Explanation Generation: A Challenging Dataset and Models

End-to-End Multimodal Fact-Checking and Explanation Generation: A Challenging Dataset and Models

This repository is the official implementation of End-to-End Multimodal Fact-Checking and Explanation Generation: A Challenging Dataset and Models.

Please use the following citation:

@article{yao2022end,
  title={End-to-End Multimodal Fact-Checking and Explanation Generation: A Challenging Dataset and Models},
  author={Yao, Barry Menglong and Shah, Aditya and Sun, Lichao and Cho, Jin-Hee and Huang, Lifu},
  journal={arXiv preprint arXiv:2205.12487},
  year={2022}
}

Requirements

To install requirements:

pip install -r requirements.txt

Dataset - MOCHEG

You can download dataset here:

• MOCHEG version 1.

Pre-trained Models

You can download pretrained models here:

• pretrained models trained on MOCHEG.

Evaluation

To evaluate models on MOCHEG, run:

python eval.sh

Credit:

This repository was build by Barry Menglong Yao, Aditya Shah.

The data crawler scripts are based on conll2019-snopes-crawling.

Contributing

📋 Our dataset is licensed under the CC BY 4.0. The associated codes are licensed under Apache License 2.0.