S2MAD, a multi-agent LLM debate pipeline with stance-separated comments and subjectivity-aware prompts, improves zero-shot rumor detection accuracy on two COVID-19 datasets by up to 12 percentage points.
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Breaking Event Rumor Detection via Stance-Separated Multi-Agent Debate
S2MAD, a multi-agent LLM debate pipeline with stance-separated comments and subjectivity-aware prompts, improves zero-shot rumor detection accuracy on two COVID-19 datasets by up to 12 percentage points.