Persona-based One-shot MBTI Prompt Engineering 


Vol. 14,  No. 8, pp. 608-616, Aug.  2025
https://doi.org/10.3745/TKIPS.2025.14.8.608


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  Abstract

Recently, large-scale language models are utilized in the diverse kinds of domains. However, It is still required to overcome the limitations of conventional generic and neutral response styles of a conversational agent as well as large-scale language models that are biased toward specific MBTI types. This paper proposes a dialogue generation technique that effectively reflects a conversational agent’s MBTI-based personality traits to provide personalized responses to users. This paper designs a system that conveys an agent’s personality traits with only few prompt examples by utilizing one-shot prompt engineering technique. The proposed system is composed of learning and inference phases; during the learning phase, the agent’s dialogues are evaluated and calibrated to ensure consistency with the agent’s persona and MBTI characteristics. During the inference phase, the optimized MBTI prompts are selectively applied to enable the agent to maintain rich contextual understanding and consistent personality. This approach presents the potential to deliver more natural and personalized interactive experiences in various fields, including virtual assistants, educational tutors, and entertainment characters

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[IEEE Style]

Y. Lee, Y. Ji, Y. Sung, "Persona-based One-shot MBTI Prompt Engineering," The Transactions of the Korea Information Processing Society, vol. 14, no. 8, pp. 608-616, 2025. DOI: https://doi.org/10.3745/TKIPS.2025.14.8.608.

[ACM Style]

Yongjae Lee, Youngmin Ji, and Yunsick Sung. 2025. Persona-based One-shot MBTI Prompt Engineering. The Transactions of the Korea Information Processing Society, 14, 8, (2025), 608-616. DOI: https://doi.org/10.3745/TKIPS.2025.14.8.608.

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