  This paper investigates the inherent knowledge in language models from the
perspective of epistemological holism. The purpose of this paper is to explore
whether LLMs exhibit characteristics consistent with epistemological holism.
These characteristics suggest that core knowledge, such as general scientific
knowledge, each plays a specific role, serving as the foundation of our
knowledge system and being difficult to revise. To assess these traits related
to holism, we created a scientific reasoning dataset and examined the
epistemology of language models through three tasks: Abduction, Revision, and
Argument Generation. In the abduction task, the language models explained
situations while avoiding revising the core knowledge. However, in other tasks,
the language models were revealed not to distinguish between core and
peripheral knowledge, showing an incomplete alignment with holistic knowledge
principles.
