Caption Enriched Samples for Improving Hateful Memes Detection
Efrat Blaier, Itzik Malkiel, Lior Wolf · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing · 2021
The recently introduced hateful meme challenge demonstrates the difficulty of determining whether a meme is hateful or not.Specifically, both unimodal language models and multimodal vision-language models cannot reach the human level of performance.Motivated by the need to model the contrast between the image content and the overlayed text, we suggest applying an off-the-shelf image captioning tool in order to capture the first.We demonstrate that the incorporation of such automatic captions during fine-tuning improves the results for various unimodal and multimodal models.Moreover, in the unimodal case, continuing the pre-training of language models on augmented and original caption pairs, is highly beneficial to the classification accuracy.Our code is publicly available 1 .