AI RESEARCH
Internal Knowledge Without External Expression: Probing the Generalization Boundary of a Classical Chinese Language Model
arXiv CS.AI
•
ArXi:2604.14180v1 Announce Type: cross We train a 318M-parameter Transformer language model from scratch on a curated corpus of 1.56B tokens of pure Classical Chinese, with zero English characters or Arabic numerals. Through systematic out-of-distribution (OOD) testing, we investigate whether the model can distinguish known from unknown inputs, and crucially, whether it can express this distinction in its generated text. We find a clear dissociation between internal and external uncertainty.