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arXiv · 2203.07990

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

Abhishek Dhankar·Osmar R. Zaïane·Francois Bolduc
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Abstract

Identifying fake news is a very difficult task, especially when considering the multiple modes of conveying information through text, image, video and/or audio. We attempted to tackle the problem of automated misinformation/disinformation detection in multi-modal news sources (including text and images) through our simple, yet effective, approach in the FACTIFY shared task at De-Factify@AAAI2022. Our model produced an F1-weighted score of 74.807%, which was the fourth best out of all the submissions. In this paper we will explain our approach to undertake the shared task.

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Abhishek Dhankar, Osmar R. Zaïane, Francois Bolduc. 2022-01-28. UofA-Truth at Factify 2022 : Transformer And Transfer Learning Based Multi-Modal Fact-Checking. https://arxiv.org/abs/2203.07990

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