A Unified Manifold Framework for Modeling Chinese Script Evolution with Application to Oracle Bone Decipherment

Of the approximately 4,500 Oracle Bone Inscription (OBI) characters discovered from the Shang dynasty, only about 1,600 have been deciphered. Existing computational methods mainly compute the similarity between OBI and single historical period characters independently. However, during the evolution of Chinese characters, significant structural or semantic changes often occur in uncertain dynasties. Relying solely on a single dynasty for reference leads to numerous deciphering errors. Therefore, we propose the Manifold-based Script Evolution Framework (MSEF), the first unified framework that models the evolution series (OBI, Bronze, Seal, Clerical, Regular) of Chinese characters as the continual evolution of a manifold space. MSEF represents each character as an era-specific manifold point and learns continuous inter-era transition rules via Neural Ordinary Differential Equations. Both manifold space and transition dynamics can be trained end-to-end through character evolution pairs across any two eras. To support this training scheme, we construct the first unified cross-era dataset with fine-grained temporal and regional granularity. Based on MSEF, we propose the Cascaded Bidirectional Evolutionary Decipherment (CBED) algorithm, where forward predictions recall potential candidates and backward consistency checking filters false matches, effectively avoiding errors caused by single-dynasty comparisons. To ground our approach, we provide a pre-exploratory diagnosis of existing generative and retrieval paradigms, showing why continuous manifold dynamics are well suited for fragmented cross-era script data. We further conduct mechanistic post-analysis, showing that the learned representations and transition dynamics capture patterns consistent with known paleographic transformations. Experiments on three commonly used benchmarks and our dataset demonstrate that MSEF achieves state-of-the-art performance among current oracle deciphering algorithms. This work opens the possibility of using continuous manifold dynamics in cross-era paleographic decipherment. Dataset and code are released through our project page https://iclr-oracle-submission.github.io.