Large Language Models (LLMs) have made remarkable advancements in the field of artificial intelligence, significantly reshaping the human-computer interaction. We not only focus on the performance of LLMs, but also explore their features from a psychological perspective, acknowledging the importance of understanding their behavioral characteristics. Our study examines the behavioral patterns displayed by LLMs by employing trait theory, a psychological framework. We first focus on evaluating the consistency of personality types exhibited by ChatGPT. Furthermore, experiments include cross-lingual effects on seven additional languages, and the investigation of six other LLMs. Moreover, the study investigates whether ChatGPT can exhibit personality changes in response to instructions or contextual cues. The findings show that ChatGPT consistently maintains its ENFJ personality regardless of instructions or contexts. By shedding light on the personalization of LLMs, we anticipate that our study will serve as a catalyst for further research in this field.

翻译：大型语言模型（LLMs）在人工智能领域取得了显著进展，极大地重塑了人机交互方式。我们不仅关注LLMs的性能表现，更从心理学视角探索其特征，认识到理解其行为特性的重要性。本研究运用特质理论这一心理学框架，考察了LLMs呈现的行为模式。我们首先聚焦于评估ChatGPT所展现人格类型的一致性，进而开展了涵盖七种其他语言的跨语言效应实验，并探究了另外六种LLMs。此外，研究还考察了ChatGPT是否能在指令或情境线索下表现出人格变化。结果表明，无论指令或情境如何变化，ChatGPT始终维持ENFJ人格。通过揭示LLMs的人格化特征，我们期望本研究能成为该领域进一步研究的催化剂。