Two Tales of Persona in LLMs: A Survey of Role-Playing and Personalization

Yu-Min Tseng*, Yu-Chao Huang*, Teng-Yun Hsiao*, Yu-Ching Hsu, Jia-Yin Foo, Chao-Wei Huang, and Yun-Nung Chen

Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

Recently, methods investigating how to adapt large language models (LLMs) for specific scenarios have gained great attention. Particularly, the concept of persona, originally adopted in dialogue literature, has re-surged as a promising avenue. However, the growing research on persona is relatively disorganized, lacking a systematic overview. To close the gap, we present a comprehensive survey to categorize the current state of the field. We identify two lines of research, namely (1) LLM Role-Playing, where personas are assigned to LLMs, and (2) LLM Personalization, where LLMs take care of user personas. To the best of our knowledge, we present the first survey tailored for LLM role-playing and LLM personalization under the uni- fied view of persona, including taxonomy, current challenges, and potential directions. To foster future endeavors, we actively maintain a paper collection available to the community.