Communication is All You Need: Persuasion Dataset Construction via Multi-LLM Communication
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Abstract (arXiv)
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.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 23 of its 46 references that are in the map. First posted on arXiv 13 Feb 2025.
Builds on
23 of 46 references.
References · 23
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11 more
- 2018Retrieval-Enhanced Adversarial Training for Neural Response Generationcited by 22
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Built on by
Citing papers per year: 2025: 4; 2026: 1.
5 papers.
- 2025How Do LLMs Persuade? Linear Probes Can Uncover Persuasion Dynamics in Multi-Turn Conversationscited by 3
- 2025Unraveling SITT: Social Influence Technique Taxonomy and Detection with LLMscited by 2
- 2025CLAIM: An Intent-Driven Multi-Agent Framework for Analyzing Manipulation in Courtroom Dialoguescited by 1
- 2025A Generalizable Rhetorical Strategy Annotation Model Using LLM-based Debate Simulation and Labellingcited by 1
- 2026Distilling Long-CoT Reasoning through Collaborative Step-wise Multi-Teacher Decodingcited by 0
- 2026Distilling Long-CoT Reasoning through Collaborative Step-wise Multi-Teacher Decoding4 May 2026
- 2025A Generalizable Rhetorical Strategy Annotation Model Using LLM-based Debate Simulation and Labelling16 Oct 2025
- 2025How Do LLMs Persuade? Linear Probes Can Uncover Persuasion Dynamics in Multi-Turn Conversations7 Aug 2025
- 2025CLAIM: An Intent-Driven Multi-Agent Framework for Analyzing Manipulation in Courtroom Dialogues4 Jun 2025
- 2025Unraveling SITT: Social Influence Technique Taxonomy and Detection with LLMs29 May 2025