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.
Identifying Creative Harmful Memes via Prompt based Approach , url=
2 Pith papers cite this work, alongside 31 external citations. Polarity classification is still indexing.
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2026 2verdicts
UNVERDICTED 2representative citing papers
Standalone decoder-only transformer tops binary hate-speech detection while soft-voting ensemble improves macro F1 by 15.8% on three-class sentiment for Nepali meme text.
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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TeamHerald@CHIPSAL 2026: Hate Speech Detection and Sentiment Analysis of Nepali Memes using Transformer-based Architectures and Ensemble Learning
Standalone decoder-only transformer tops binary hate-speech detection while soft-voting ensemble improves macro F1 by 15.8% on three-class sentiment for Nepali meme text.