  Understanding and attributing mental states, known as Theory of Mind (ToM),
emerges as a fundamental capability for human social reasoning. While Large
Language Models (LLMs) appear to possess certain ToM abilities, the mechanisms
underlying these capabilities remain elusive. In this study, we discover that
it is possible to linearly decode the belief status from the perspectives of
various agents through neural activations of language models, indicating the
existence of internal representations of self and others' beliefs. By
manipulating these representations, we observe dramatic changes in the models'
ToM performance, underscoring their pivotal role in the social reasoning
process. Additionally, our findings extend to diverse social reasoning tasks
that involve different causal inference patterns, suggesting the potential
generalizability of these representations.
