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AbstractThis paper describes our submission for task 5 Multimedia Automatic Misogyny Identification (MAMI) at SemEval-2022. The task is designed to detect and classify misogynous memes. To utilize both textual and …...
HateU at SemEval-2022 Task 5: Multimedia Automatic Misogyny Identification
AbstractHate speech expressions in social media are not limited to textual messages; they can appear in videos, images, or multimodal formats like memes. Existing work towards detecting such expressions has …...
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AbstractIn this paper we present our approach and system description on Task 5 A in MAMI: Multimedia Automatic Misogyny Identification. In our experiments we compared several architectures based on deep …...
IIITH at SemEval-2022 Task 5: A comparative study of deep learning models for identifying misogynous memes
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IITR CodeBusters at SemEval-2022 Task 5: Misogyny Identification using Transformers
AbstractThis paper presents our submission to task 5 ( Multimedia Automatic Misogyny Identification) of the SemEval 2022 competition. The purpose of the task is to identify given memes as misogynistic …...
LastResort at SemEval-2022 Task 5: Towards Misogyny Identification using Visual Linguistic Model Ensembles And Task-Specific Pretraining
AbstractIn current times, memes have become one of the most popular mediums to share jokes and information with the masses over the internet. Memes can also be used as tools …...
SemEval-2022 Task 5: Multimedia Automatic Misogyny Identification
AbstractThe paper describes the SemEval-2022 Task 5: Multimedia Automatic Misogyny Identification (MAMI),which explores the detection of misogynous memes on the web by taking advantage of available texts and images. The …...
taochen at SemEval-2022 Task 5: Multimodal Multitask Learning and Ensemble Learning
AbstractWe present a multi-modal deep learning system for the Multimedia Automatic Misogyny Identification (MAMI) challenge, a SemEval task of identifying and classifying misogynistic messages in online memes. We adapt multi-task …...
University of Hildesheim at SemEval-2022 task 5: Combining Deep Text and Image Models for Multimedia Misogyny Detection
AbstractThis paper describes the participation of the University of Hildesheim at the SemEval task 5. The task deals with Multimedia Automatic Misogyny Identification (MAMI). Hateful memes need to be detected …...
YNU-HPCC at SemEval-2022 Task 5: Multi-Modal and Multi-label Emotion Classification Based on LXMERT
AbstractThis paper describes our system used in the SemEval-2022 Task5 Multimedia Automatic Misogyny Identification (MAMI). This task is to use the provided text-image pairs to classify emotions. In this paper, …...