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UofA-Truth at Factify 2022 : Transformer And Transfer Learning Based Multi-Modal Fact-Checking (2203.07990v1)

Published 28 Jan 2022 in cs.MM, cs.AI, and cs.CL

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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Authors (3)
  1. Abhishek Dhankar (1 paper)
  2. Francois Bolduc (1 paper)
  3. Osmar R. Zaïane (11 papers)
Citations (1)