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Hateful Meme Classification

Hateful meme classification aims to detect harmful content within the text or images of memes.

Papers

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Showing 1–17 of 17 papers

TitleStatusHype
Learning Transferable Visual Models From Natural Language SupervisionCode2
Mapping Memes to Words for Multimodal Hateful Meme ClassificationCode1
MemeCLIP: Leveraging CLIP Representations for Multimodal Meme ClassificationCode1
Hate-CLIPper: Multimodal Hateful Meme Classification based on Cross-modal Interaction of CLIP FeaturesCode1
Robust Adaptation of Large Multimodal Models for Retrieval Augmented Hateful Meme DetectionCode1
Towards Explainable Harmful Meme Detection through Multimodal Debate between Large Language ModelsCode1
Improving Hateful Meme Detection through Retrieval-Guided Contrastive LearningCode1
Decoding the Underlying Meaning of Multimodal Hateful MemesCode1
Prompt-enhanced Network for Hateful Meme ClassificationCode0
VL-BERT+: Detecting Protected Groups in Hateful Multimodal Memes—0
Demystifying Hateful Content: Leveraging Large Multimodal Models for Hateful Meme Detection with Explainable Decisions—0
Detecting Harmful Memes and Their Targets—0
Disentangling Hate in Online Memes—0
LLM-based Semantic Augmentation for Harmful Content Detection—0
On Explaining Multimodal Hateful Meme Detection Models—0
Prompting for Multimodal Hateful Meme Classification—0
0/1 Deep Neural Networks via Block Coordinate Descent—0
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