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MADS framework generates persuasive dialogues, boosting marketing conversion rates

By PulseAugur Editorial · [1 sources] ·

Researchers have developed MADS (Multi-Agent Dialogue Simulation), a framework for generating persuasive multi-turn dialogues through agent self-play. This system uses three agents to simulate diverse user personas, execute persuasion strategies, and refine dialogue outcomes. Applied to a marketing scenario, MADS improved the persuasion capacity of small LLMs, leading to a 22.4% increase in organic traffic conversion rates. AI

IMPACT This framework could enable more efficient and cost-effective generation of training data for LLMs, particularly in persuasion-focused applications.

RANK_REASON The cluster describes a research paper detailing a new framework for data generation. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

MADS framework generates persuasive dialogues, boosting marketing conversion rates

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The cluster describes a research paper detailing a new framework for data generation. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Mingjin Li, Yu Liu, Huayi Liu, Xiang Ye, Chao Jiang, Hongguang Zhang, Yu Ruan ·

    MADS: Multi-Agent Dialogue Simulation for Diverse Persuasion Data Generation

    arXiv:2510.05124v3 Announce Type: replace Abstract: We propose MADS (Multi-Agent Dialogue Simulation), a scalable framework for generating persuasive multi-turn dialogues via agent self-play. MADS employs three coordinated agents: User Agents designed to simulate diverse persona-…

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