  In recent years, social media has enabled users to get exposed to a myriad of
misinformation and disinformation; thus, misinformation has attracted a great
deal of attention in research fields and as a social issue. To address the
problem, we propose a framework, Pre-CoFact, composed of two pre-trained models
for extracting features from text and images, and multiple co-attention
networks for fusing the same modality but different sources and different
modalities. Besides, we adopt the ensemble method by using different
pre-trained models in Pre-CoFact to achieve better performance. We further
illustrate the effectiveness from the ablation study and examine different
pre-trained models for comparison. Our team, Yao, won the fifth prize
(F1-score: 74.585\%) in the Factify challenge hosted by De-Factify @ AAAI 2022,
which demonstrates that our model achieved competitive performance without
using auxiliary tasks or extra information. The source code of our work is
publicly available at
https://github.com/wywyWang/Multi-Modal-Fact-Verification-2021
