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papersSEP 10 04:00 UTC

MADS framework generates persuasion dialogue data via multi-agent self-play

Researchers introduced MADS, a scalable framework that produces multi-turn persuasive conversations through agent self-play. The setup uses three coordinated agents, including user agents that role-play varied persona-driven behaviors, to generate diverse dialogue datasets. The paper appears on arXiv with cross-listings in artificial intelligence and computational linguistics.

arXiv MADS computational-linguistics multi-agent-self-play persuasion-dialogue

COVERAGE · 2 REPORTS · LINKS GO TO THE ORIGINAL OUTLETS

arXiv cs.AIMADS: Multi-Agent Dialogue Simulation for Diverse Persuasion Data Generation ↗SEP 10 04:00 UTC

arXiv cs.CLMADS: Multi-Agent Dialogue Simulation for Diverse Persuasion Data Generation ↗SEP 10 04:00 UTC