Large Language Models (LLMs) demonstrate a remarkable capacity to adopt different personas and roles; however, it remains unclear whether they can manifest behavior that adheres to a coherent, human-like value structure. In this work, we draw on established psychological value theory to induce human-like values in LLMs and assess their alignment with patterns observed in human studies. Using validated psychological questionnaires, we conduct large-scale experiments -- over 5 million questions -- to evaluate value structures and value-behavior relationships in leading LLMs and compare them to humans. Our findings reveal strong agreement between value-prompted LLMs and humans across both dimensions. Moreover, incorporating human value distributions enhances population-level simulations with value-induced LLMs. These findings highlight the potential of value-induced LLMs as effective, psychologically grounded tools for simulating human behavior.

翻译：大语言模型展现出采纳不同角色和身份的强大能力；然而，它们能否表现出符合连贯、类人价值结构的行为仍不明确。本研究借鉴成熟的心理学价值理论，在大语言模型中诱导类人价值观，并评估其与人类研究观察到的模式的一致性。我们采用经过验证的心理问卷开展大规模实验——涵盖超过500万道问题——评估主流大语言模型的价值结构及价值-行为关系，并与人类进行对比。研究结果显示，在价值诱导下的大语言模型与人类在价值维度和行为维度均呈现高度一致性。此外，融入人类价值分布可增强基于价值诱导大语言模型的人群层面模拟效果。这些发现凸显了价值诱导大语言模型作为基于心理学的有效工具在模拟人类行为方面的潜力。