PrismAgent uses multi-agent framework to detect harmful memes without training data

Researchers have developed PrismAgent, a novel zero-shot framework designed to detect harmful content within memes. This multi-agent system simulates a criminal investigation, with specialized agents handling analysis, evidence gathering, prosecution, and judgment. By breaking down the process into interpretable stages, PrismAgent aims to reduce reliance on extensive annotated data and improve the generalization of harmful content detection. AI

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IMPACT Introduces a novel interpretable framework for meme analysis, potentially improving safety measures against misinformation.

RANK_REASON Academic paper introducing a new framework for harmful content detection in memes. [lever_c_demoted from research: ic=1 ai=1.0]

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