Papers with Contrastive Language-Image Pre-Training

1 papers
MemeDetoxNet: Balancing Toxicity Reduction and Context Preservation (2025.findings-acl)

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Challenge: Toxic memes spread harmful and offensive content and pose a significant challenge in online environments.
Approach: They propose a framework to mitigate toxicity in toxic memes by leveraging a set of pre-trained models that can interpret the visual and textual components of memes.
Outcome: The proposed framework reduces toxicity on publicly available meme datasets by 10-20% compared to the previous methods.

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