PrismAgent deploys four specialized LLM agents in sequence to analyze meme intent, gather context, make preliminary judgments, and deliver a final harm verdict, outperforming prior zero-shot methods on three public datasets.
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A PRISMA-based survey of 158 computational works on toxic meme detection introduces a new toxicity taxonomy and a framework linking target, intent, and conveyance tactics while noting trends in LLMs and cross-modal methods.
TwistedHumor dataset shows dark humor in YouTube Shorts clusters around critique, coping, awkwardness and identity with more mixed and toxic audience reactions than regular humor.
citing papers explorer
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PrismAgent: Illuminating Harm in Memes via a Zero-Shot Interpretable Multi-Agent Framework
PrismAgent deploys four specialized LLM agents in sequence to analyze meme intent, gather context, make preliminary judgments, and deliver a final harm verdict, outperforming prior zero-shot methods on three public datasets.
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When Jokes Cross the Line: Analyzing Regular Humor and Dark Humor in YouTube Shorts
TwistedHumor dataset shows dark humor in YouTube Shorts clusters around critique, coping, awkwardness and identity with more mixed and toxic audience reactions than regular humor.