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TeamOtter at SemEval-2022 Task 5: Detecting Misogynistic Content in Multimodal Memes
2022
Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)
unpublished
We describe our system for the SemEval 2022 task on detecting misogynous content in memes. This is a pressing problem and we explore various methods ranging from traditional machine learning to deep learning models such as multimodal transformers. We propose a multimodal BERT architecture that uses information from both image and text. We further incorporate common world knowledge from pretrained CLIP and Urban dictionary. We also provide qualitative analysis to support out model. Our best
doi:10.18653/v1/2022.semeval-1.88
fatcat:zmswln5aojbr5evfzlzbta7pm4