Papers with multi-agent debate mechanism

2 papers
MIND: A Multi-agent Framework for Zero-shot Harmful Meme Detection (2025.acl-long)

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Challenge: a rapid expansion of memes on social media highlights the need for effective methods to detect harmful content.
Approach: They propose a multi-agent framework for zero-shot harmful meme detection that does not rely on annotated data.
Outcome: The proposed framework outperforms existing zero-shot approaches on three meme datasets.
ExpertIVS: Sociological Expert Driven Individual Value Simulation in Large Language Models (2026.findings-acl)

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Challenge: Existing methods for social simulations mechanically stitch survey responses into prompts, which suffer from semantic fragmentation, failing to capture the internal coherence of human value systems.
Approach: They propose a framework employing 14 Sociological Expert Agents to interpret World Values Survey responses through structured professional perspectives rather than direct responses concatenation.
Outcome: Experiments on 480 individuals from 12 countries show that ExpertIVS outperforms baselines in value generalization and significantly outperfies the existing methods.

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