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Identifying fake news is a very difficult task, especially when consideringthe multiple modes of conveying information through text, image, video and/oraudio. We attempted to tackle the problem of automatedmisinformation/disinformation detection in multi-modal news sources (includingtext and images) through our simple, yet effective, approach in the FACTIFYshared task at De-Factify@AAAI2022. Our model produced an F1-weighted score of74.807%, which was the fourth best out of all the submissions. In this paper wewill explain our approach to undertake the shared task.

UofA-Truth at Factify 2022 : Transformer And Transfer Learning Based Multi-Modal Fact-Checking