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.