April 5, 2024, 4:42 a.m. | Amirhossein Abaskohi, Amirhossein Dabiriaghdam, Lele Wang, Giuseppe Carenini

cs.LG updates on arXiv.org arxiv.org

arXiv:2404.03022v1 Announce Type: cross
Abstract: Memes, combining text and images, frequently use metaphors to convey persuasive messages, shaping public opinion. Motivated by this, our team engaged in SemEval-2024 Task 4, a hierarchical multi-label classification task designed to identify rhetorical and psychological persuasion techniques embedded within memes. To tackle this problem, we introduced a caption generation step to assess the modality gap and the impact of additional semantic information from images, which improved our result. Our best model utilizes GPT-4 generated …

abstract arxiv beyond classification cs.cl cs.cv cs.it cs.lg embedded exploration hierarchical identify images math.it memes messages multilingual multimodal opinion persuasion public team text type words

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