Hateful Meme Classification
3 papers with code • 1 benchmarks • 2 datasets
Hateful meme classification aims to detect harmful content within the text or images of memes.
Hateful Memes
HarMeme
Most implemented papers
Hate-CLIPper: Multimodal Hateful Meme Classification based on Cross-modal Interaction of CLIP Features
A simple classifier based on the FIM representation is able to achieve state-of-the-art performance on the Hateful Memes Challenge (HMC) dataset with an AUROC of 85. 8, which even surpasses the human performance of 82. 65.
Decoding the Underlying Meaning of Multimodal Hateful Memes
Recent studies have proposed models that yielded promising performance for the hateful meme classification task.
Mapping Memes to Words for Multimodal Hateful Meme Classification
miccunifi/issues
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Multimodal image-text memes are prevalent on the internet, serving as a unique form of communication that combines visual and textual elements to convey humor, ideas, or emotions.
