The debut of a vertical large model that specifically digs into cultural historical materials extends the reach of artificial intelligence into the shared historical memory of both sides of the Strait. On October 18, the vertical large model "Tongyuan Guanlan" for Chinese cultural inheritance and cross-strait integrated development was officially released at the Qishan campus of Fujian Normal University. Its mission is clear—to use digital technology to revitalize the historical memory shared by both sides.
Zheng Jiajian, president of Fujian Normal University, highlighted the real pain point this system aims to solve: Taiwan-related archival materials are as vast as the sea, and the difficulty of organizing and verifying them is extremely high. The university developed and launched "Tongyuan Guanlan" precisely to use AI for literature mining and historical material analysis, truly weaving the humanities and social sciences together with digital technology; it is also a cross-disciplinary attempt by the school to advance new liberal arts construction. The model focuses its main battlefield on several key directions: cross-strait language and literature, cross-strait people-and-place relations, intangible cultural heritage protection and artistic practice, and cross-strait social simulation research.
Supporting these capabilities is a set of already-deployed application systems. The model has so far built the multidisciplinary multimodal knowledge graph "Tongyuan Wencang," the AI-assisted Taiwan-related research platform "Guanlan Cebi," and the social simulation and deduction platform "Tongyuan Zhijing." Linked together, the three form a closed-loop innovation chain of "basic research—technology development—application deployment—policy services," providing a digital-intelligent foundation for Taiwan-related academic research, cultural dissemination, and decision-making consulting. Song Meijie, deputy director of the university's Digital Intelligence Laboratory, described the chain more vividly: the model can already move from the accumulated sediment of shared-origin culture and real-time situational awareness all the way to future event deduction. The system will subsequently gradually expand into regional and country studies, cross-strait cultural dissemination, and other directions, and will promote the orderly opening of literature resources for use by Taiwan-related researchers.
This vertical large model oriented toward the Taiwan-related field is also seen as one of the long-standing priorities of work toward Taiwan. Commenting on it, people in related fields said that judging from the feature introduction, the model's overall performance is impressive and fits actual work needs, and they look forward to the R&D team continuing to iterate and optimize it, so that it can be opened up for use by practitioners in related fields in the future. Only when AI no longer merely holds forth on generic questions but bends down to delve into vast historical materials and documents does its value for cultural inheritance truly begin to emerge.