# Understanding Persuasive Interactions between Generative Social Agents and Humans: The Knowledge-based Persuasion Model (KPM)

arXiv: https://arxiv.org/abs/2602.11483 · HTML: https://mlsanity.com/paper/2602.11483/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 32 of its 161 references that are in the map.
- First posted on arXiv 12 Feb 2026.

## Builds on (most cited first, 30 of 32)

- [Generative Agents: Interactive Simulacra of Human Behavior](https://mlsanity.com/paper/2304.03442/) (2023)
- [Language Models (Mostly) Know What They Know](https://mlsanity.com/paper/2207.05221/) (2022)
- [A Prompt Pattern Catalog to Enhance Prompt Engineering with ChatGPT](https://mlsanity.com/paper/2302.11382/) (2023)
- [A Survey on Large Language Model (LLM) Security and Privacy: The Good, the Bad, and the Ugly](https://mlsanity.com/paper/2312.02003/) (2023)
- [Character-LLM: A Trainable Agent for Role-Playing](https://mlsanity.com/paper/2310.10158/) (2023)
- [Debating with More Persuasive LLMs Leads to More Truthful Answers](https://mlsanity.com/paper/2402.06782/) (2024)
- [PersonaLLM: Investigating the Ability of Large Language Models to Express Personality Traits](https://mlsanity.com/paper/2305.02547/) (2023)
- [Personality Traits in Large Language Models](https://mlsanity.com/paper/2307.00184/) (2023)
- [On the Conversational Persuasiveness of Large Language Models: A Randomized Controlled Trial](https://mlsanity.com/paper/2403.14380/) (2024)
- [Self-Knowledge Guided Retrieval Augmentation for Large Language Models](https://mlsanity.com/paper/2310.05002/) (2023)
- [Aligning LLM Agents by Learning Latent Preference from User Edits](https://mlsanity.com/paper/2404.15269/) (2024)
- [Do LLMs Have Distinct and Consistent Personality? TRAIT: Personality Testset designed for LLMs with Psychometrics](https://mlsanity.com/paper/2406.14703/) (2024)
- [People cannot distinguish GPT-4 from a human in a Turing test](https://mlsanity.com/paper/2405.08007/) (2024)
- [Understanding Large-Language Model (LLM)-powered Human-Robot Interaction](https://mlsanity.com/paper/2401.03217/) (2024)
- [ChatBench: From Static Benchmarks to Human-AI Evaluation](https://mlsanity.com/paper/2504.07114/) (2025)
- [LLM Agents in Interaction: Measuring Personality Consistency and Linguistic Alignment in Interacting Populations of Large Language Models](https://mlsanity.com/paper/2402.02896/) (2024)
- [Measuring and Benchmarking Large Language Models' Capabilities to Generate Persuasive Language](https://mlsanity.com/paper/2406.17753/) (2024)
- [Evaluating Personality Traits in Large Language Models: Insights from Psychological Questionnaires](https://mlsanity.com/paper/2502.05248/) (2025)
- [LLM-Driven Robots Risk Enacting Discrimination, Violence, and Unlawful Actions](https://mlsanity.com/paper/2406.08824/) (2024)
- [An Evaluation on Large Language Model Outputs: Discourse and Memorization](https://mlsanity.com/paper/2304.08637/) (2023)
- [ControlLM: Crafting Diverse Personalities for Language Models](https://mlsanity.com/paper/2402.10151/) (2024)
- [An overview of model uncertainty and variability in LLM-based sentiment analysis. Challenges, mitigation strategies and the role of explainability](https://mlsanity.com/paper/2504.04462/) (2025)
- [TrustNavGPT: Modeling Uncertainty to Improve Trustworthiness of Audio-Guided LLM-Based Robot Navigation](https://mlsanity.com/paper/2408.01867/) (2024)
- [A Longitudinal Randomized Control Study of Companion Chatbot Use: Anthropomorphism and Its Mediating Role on Social Impacts](https://mlsanity.com/paper/2509.19515/) (2025)
- [Collaborative Quest Completion with LLM-driven Non-Player Characters in Minecraft](https://mlsanity.com/paper/2407.03460/) (2024)
- [A Meta-Analysis of the Persuasive Power of Large Language Models](https://mlsanity.com/paper/2512.01431/) (2025)
- [In Generative AI we Trust: Can Chatbots Effectively Verify Political Information?](https://mlsanity.com/paper/2312.13096/) (2023)
- [Appropriateness of LLM-equipped Robotic Well-being Coach Language in the Workplace: A Qualitative Evaluation](https://mlsanity.com/paper/2401.14935/) (2024)
- [How Can Large Language Models Enable Better Socially Assistive Human-Robot Interaction: A Brief Survey](https://mlsanity.com/paper/2404.00938/) (2024)
- [Does ChatGPT and Whisper Make Humanoid Robots More Relatable?](https://mlsanity.com/paper/2402.07095/) (2024)

## Built on by (most cited first, 3 of 3)

- [Knowledge-Based Design Requirements for Generative Social Robots in Higher Education](https://mlsanity.com/paper/2602.12873/) (2026)
- [Never say never: Exploring the effects of available knowledge on agent persuasiveness in controlled physiotherapy motivation dialogues](https://mlsanity.com/paper/2602.12924/) (2026)
- [Teachy Mini: Development and Preliminary Evaluation of a Knowledge-Based Generative Social Robot for Higher Education](https://mlsanity.com/paper/2607.22345/) (2026)

## Abstract (arXiv)

Generative social agents (GSAs) use artificial intelligence to autonomously communicate with human users in a natural and adaptive manner. Currently, there is a lack of theorizing regarding interactions with GSAs, and likewise, few guidelines exist for studying how they influence user attitudes and behaviors. Consequently, we propose the Knowledge-based Persuasion Model (KPM) as a novel theoretical framework. According to the KPM, a GSA's self-, user-, and context-knowledge drives its persuasive behavior, which in turn shapes attitudes and behaviors of a responding human user. Building on existing research, the model offers a structured approach to studying interactions with GSAs, supporting the development of agents that motivate rather than manipulate human users. Accordingly, the KPM encourages the integration of responsible GSAs that adhere to social norms and ethical standards with the goal of increasing user wellbeing. A preliminary evaluation study, as well as implications of the KPM for research and application domains such as healthcare and education are discussed.