A Model of Multi-turn Human Persuadability Using Probabilistic Belief Tracing

• URL: http://arxiv.org/abs/2606.05330v1
• Date: Wed, 03 Jun 2026 18:17:20 GMT
• Title: A Model of Multi-turn Human Persuadability Using Probabilistic Belief Tracing
• Abstract summary: PERSUASIONTRACE is a framework for studying persuasion in human-LLM interaction.<n>It records multi-turn belief reports from human or simulated targets of persuasion.<n>It annotates persuader turns with rhetorical dimensions and evaluates simulators by fidelity to real human belief dynamics.
• Score: 16.188738760148645
• License: http://creativecommons.org/licenses/by-sa/4.0/
• Abstract: Large language models can shift human beliefs across high-stakes domains, but most persuasion studies rely on pre/post belief change. These endpoint measures identify whether persuasion occurred, yet miss where and how beliefs moved within a dialogue. We present PERSUASIONTRACE, a framework for studying persuasion in human-LLM interaction. Built on a web-based experimental platform, PERSUASIONTRACE contributes a tool for multi-turn persuasion studies and a process-level evaluation protocol: it records multi-turn belief reports from human or simulated targets of persuasion, annotates persuader turns with rhetorical dimensions (logos/pathos/ethos), and evaluates simulators by fidelity to real human belief dynamics. Using this framework, we find that human targets group into two clusters of multi-turn belief updates and exhibit susceptibility to rhetorical strategies, and that LLMs are persuasive across generic and personalized topics, text and audio modalities, and multi-turn interactions. Prior work has chiefly used vanilla-prompted LLMs to simulate human targets, but we show that these simulators fail to replicate human belief dynamics. We introduce a Bayesian-network simulated target that maintains an explicit latent belief state over time so each persuader message yields cognitively realistic belief updates. In human-likeness evaluation, our Bayesian target scores near a human reference (81 vs 80), while baseline LLM targets score substantially lower (64). PERSUASIONTRACE reframes persuasion evaluation from endpoint movement alone to process fidelity, providing a stronger basis for scientific analysis and safer optimization of persuasive systems.

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