  As large language models (LLMs) appear to behave increasingly human-like in
text-based interactions, more and more researchers become interested in
investigating personality in LLMs. However, the diversity of psychological
personality research and the rapid development of LLMs have led to a broad yet
fragmented landscape of studies in this interdisciplinary field. Extensive
studies across different research focuses, different personality psychometrics,
and different LLMs make it challenging to have a holistic overview and further
pose difficulties in applying findings to real-world applications. In this
paper, we present a comprehensive review by categorizing current studies into
three research problems: self-assessment, exhibition, and recognition, based on
the intrinsic characteristics and external manifestations of personality in
LLMs. For each problem, we provide a thorough analysis and conduct in-depth
comparisons of their corresponding solutions. Besides, we summarize research
findings and open challenges from current studies and further discuss their
underlying causes. We also collect extensive publicly available resources to
facilitate interested researchers and developers. Lastly, we discuss the
potential future research directions and application scenarios. Our paper is
the first comprehensive survey of up-to-date literature on personality in LLMs.
By presenting a clear taxonomy, in-depth analysis, promising future directions,
and extensive resource collections, we aim to provide a better understanding
and facilitate further advancements in this emerging field.
