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With the application trend of large language models (LLMs) in the industry, the individuality of vertical domain LLMs has become a new direction worthy of study. Therefore, we focus on exploring the personality traits of the in-vehicle LLMs in the intelligent cockpit, which is regarded as the “third living space” and an important application scenario of LLMs. This study uses the psychological scale Big Five Inventory (BFI) to evaluate the personality traits of the in-vehicle LLM quantitatively and proposes methods for shaping and fine-tuning the personality traits of the in-vehicle LLM. The research shows that: 1) The in-vehicle LLM has measurable, stable, and consistent personality traits by the psychological scale, showing a high level of extraversion, agreeableness, conscientiousness, a lower level of neuroticism and a medium level of openness; 2) The personality traits of the in-vehicle LLM can be shaped and fine-tuned through the prompt of trait marker words + Likert qualifiers, and it can affect the subsequent behavioral tendencies and generated content. This study migrates the methods applied in the personality research of general LLMs to the in-vehicle LLM, providing new ideas for establishing a psychological and personality evaluation system in intelligent cockpits and contributing to the further exploration of the emotional and personalized design of the intelligent cockpit in the future to enhance user experience.

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Exploration of Psychometric Applications and Personality Characteristics Fine-Tuning Methods of In-Vehicle Large Language Models in Intelligent Cockpits

  • 会议论文

  • 发表日期：

    2025年

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  • Qianli Lin,
  • Zhipeng Hu,
  • Zhenming Liu,
  • Jun Ma

摘要

With the application trend of large language models (LLMs) in the industry, the individuality of vertical domain LLMs has become a new direction worthy of study. Therefore, we focus on exploring the personality traits of the in-vehicle LLMs in the intelligent cockpit, which is regarded as the “third living space” and an important application scenario of LLMs. This study uses the psychological scale Big Five Inventory (BFI) to evaluate the personality traits of the in-vehicle LLM quantitatively and proposes methods for shaping and fine-tuning the personality traits of the in-vehicle LLM. The research shows that: 1) The in-vehicle LLM has measurable, stable, and consistent personality traits by the psychological scale, showing a high level of extraversion, agreeableness, conscientiousness, a lower level of neuroticism and a medium level of openness; 2) The personality traits of the in-vehicle LLM can be shaped and fine-tuned through the prompt of trait marker words + Likert qualifiers, and it can affect the subsequent behavioral tendencies and generated content. This study migrates the methods applied in the personality research of general LLMs to the in-vehicle LLM, providing new ideas for establishing a psychological and personality evaluation system in intelligent cockpits and contributing to the further exploration of the emotional and personalized design of the intelligent cockpit in the future to enhance user experience.