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

翻译：人格这一概念最初源于对话文献，现已成为定制大语言模型以适应特定场景（如个性化搜索、LLM即裁判）的重要框架。然而，当前关于大语言模型人格应用的研究相对零散，缺乏系统化分类。为填补这一空白，本文提出一个综合性综述以厘清该领域现状。我们识别出两条研究脉络：（1）LLM角色扮演——为人格赋予大语言模型；（2）LLM个性化——使大语言模型适应用户人格。此外，本文系统介绍了现有的大语言模型人格评估方法。据我们所知，这是在人格统一视角下首次针对大语言模型角色扮演与个性化研究的系统性综述。我们将持续维护相关文献集合以促进后续研究：https://github.com/MiuLab/PersonaLLM-Survey