大型语言模型中的个性、角色与表达风格：一种互动主义分析
Personality, Role, and Expressive Style in Large Language Models: An Interactionist Analysis
AI总结：
本研究从互动主义视角，通过因子设计实验分析个性特质、对话角色和表达风格如何共同影响大型语言模型生成对话中感知的大五人格特质表达。
摘要：
基于提示的个性控制是设计在社交情境中行为一致的大型语言模型（LLM）对话智能体的关键技术。然而，在提示中指定大五人格特质（BFTs）并不能确保这些特质在生成的语句中得到表达。本文从互动主义视角研究这种不匹配，将人格表达视为由特质指定与情境因素相互作用塑造的依赖于上下文的结果。我们分析了感知到的LLM生成对话中的BFT表达如何受三个提示因素影响：人格特质、对话角色和表达风格。采用结合六种人格条件、三种角色和三种表达风格条件的因子设计，我们在英语和日语中各生成了1,080个LLM智能体对话。然后，我们使用LLM-as-a-judge框架评估目标智能体的语句，以估计表达的大五人格特质。结果表明，表达的人格不仅受显式特质指定影响，还受对话角色和表达风格影响。这些效应是特质特定的：对话角色强烈影响开放性，表达风格显著塑造尽责性和宜人性，而显式特质指定主导神经质。即使没有显式的人格特质指定，社会和表达条件也会诱发独特的人格印象。跨语言比较显示英语和日语对话之间的模式大致相似，仅在特定的人格、角色和表达风格组合下存在显著差异。这些发现表明，LLM智能体中的个性控制不应被理解为特质提示的直接结果，而是一个涉及人格指定、社会角色和表达风格的依赖于上下文的过程。
英文摘要：
Prompt-based personality control is a key technique for designing large language model (LLM) dialogue agents that behave consistently across social contexts. However, specifying Big Five personality traits (BFTs) in a prompt does not ensure that the intended traits are expressed in generated utterances. This paper investigates this mismatch from an interactionist perspective, viewing personality expression as a context-dependent outcome shaped by the interplay between trait specification and situational factors. We analyze how perceived BFT expression in LLM-generated dialogue is influenced by three prompt factors: personality traits, dialogue roles, and expressive styles. Using a factorial design that combines six personality conditions, three roles, and three expressive-style conditions, we generate 1,080 LLM-agent dialogues in each of English and Japanese. We then evaluate the target agent's utterances using an LLM-as-a-judge framework to estimate expressed Big Five traits. The results show that expressed personality is shaped not only by explicit trait specification, but also by dialogue role and expressive style. These effects are trait-specific: dialogue role strongly influences Openness, expressive style substantially shapes Conscientiousness and Agreeableness, and explicit trait specification dominates Neuroticism. Even without explicit personality-trait specification, social and expressive conditions induce distinct personality-like impressions. Cross-linguistic comparisons show broadly similar patterns between English and Japanese dialogues, with noticeable differences only under specific combinations of personality, role, and expressive style. These findings suggest that personality control in LLM agents should be understood not as a direct consequence of trait prompting, but as a context-dependent process involving personality specification, social role, and expressive style.
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