Nonparametric domain adaptation for multimodal connoisseurship of Buddhist statuary across dynasties (ChronoStyleNet2.0)

<title>Abstract</title> <p>Specialist shortages constrain the documentation, dating, and interpretation of Buddhist statuary. We present ChronoStyleNet 2.0 (CSN2.0,Chinese Name: Zhijian Zaoxianghttps://grottoai.xyz/), a multimodal system spanning Chinese dynasties. Without additional parameter fine-tuning, CSN 2.0 combines structured prompting, tri-strategy fusion retrieval-augmented generation, and a domain ontology informed by CIDOC CRM. The system uses an expert-curated knowledge base of 3,642 entries and a dataset of 145 statues. We evaluated CSN 2.0 and four general-purpose multimodal models on 18 held-out sculptures across eight archaeological dimensions. CSN 2.0 obtained relatively high scores in stylistic feature extraction, dating, and linguistic consistency, but lower scores in cultural interpretation and evidence-to-conclusion reasoning. These results support its use as an exploratory, traceable aid for specialist analysis, not a substitute for expert judgment. The small test set, single-run outputs, automated scoring, and absence of component ablations limit generalization and causal interpretation.</p>