Resilient Data Augmentation Approaches to Multimodal Verification in the News Domain

SRI Authors: John Cadigan, Martin Graciarena

Abstract

With the advent of generative adversarial networks and misinformation in social media, there has been increased interest in multimodal verification. Image-text verification typically involves determining whether a caption and an image correspond with each other. Building on multimodal embedding techniques, we show that data augmentation via two distinct approaches improves results: entity linking and cross-domain local similarity scaling. We refer to the approaches as resilient because we show state-of-the-art results against manipulations specifically designed to thwart the exact multimodal embeddings we are using as the basis for all of our features.

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