  The concept of persona, originally adopted in dialogue literature, has
re-surged as a promising framework for tailoring large language models (LLMs)
to specific context (e.g., personalized search, LLM-as-a-judge). However, the
growing research on leveraging persona in LLMs is relatively disorganized and
lacks a systematic taxonomy. 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. Additionally,
we introduce existing methods for LLM personality evaluation. To the best of
our knowledge, we present the first survey for role-playing and personalization
in LLMs under the unified view of persona. We continuously maintain a paper
collection to foster future endeavors:
https://github.com/MiuLab/PersonaLLM-Survey
