Computer Science And Game Theory Papers

This page lists 1 peer-reviewed paper in the research area of Computer Science And Game Theory in the Prolific Citations Library, a curated collection of research powered by high-quality human data from Prolific.

Papers (1 of 1)

Towards Strategic Persuasion with Language Models

Authors: Z Cheng, J You

Year: 2025

Published in: arXiv preprint arXiv:2509.22989, 2025 - arxiv.org

Institution: University of Southern California, University of California Berkeley

Research Area: Artificial Intelligence, Computer Science, Computer Science and Game Theory, Strategic Persuasion, Reinforcement Learning, Language Models, Large Language Models, Reinforcement Learning from Human Feedback (RLHF)

Discipline: Artificial Intelligence

This paper introduces a scalable framework, utilizing Bayesian Persuasion, to evaluate and train LLMs for strategic persuasion, demonstrating significant persuasion gains and effective strategies through reinforcement learning.

Methods: Repurposed human-human persuasion datasets for evaluation and training; applied Bayesian Persuasion framework; used reinforcement learning to optimize LLMs for strategic persuasion.

Key Findings: The persuasive capabilities and strategies of large language models (LLMs) in various settings.

Citations: 1