Communication is All You Need: Persuasion Dataset Construction via Multi-LLM Communication

TL;DR

This paper introduces a multi-LLM communication framework that automatically generates high-quality persuasive dialogue data, improving naturalness, diversity, and strategic persuasion, with broad applicability in social and computational research.

Contribution

The paper presents a novel multi-LLM communication framework for automatic persuasive data generation, enhancing quality and diversity with minimal human intervention.

Findings

Generated data shows high naturalness and diversity.

Framework effectively captures strategic persuasion, even with social taboos.

Demonstrates strong generalization across different contexts.

Abstract

Large Language Models (LLMs) have shown proficiency in generating persuasive dialogue, yet concerns about the fluency and sophistication of their outputs persist. This paper presents a multi-LLM communication framework designed to enhance the generation of persuasive data automatically. This framework facilitates the efficient production of high-quality, diverse linguistic content with minimal human oversight. Through extensive evaluations, we demonstrate that the generated data excels in naturalness, linguistic diversity, and the strategic use of persuasion, even in complex scenarios involving social taboos. The framework also proves adept at generalizing across novel contexts. Our results highlight the framework's potential to significantly advance research in both computational and social science domains concerning persuasive communication.