FontCopilot: Towards Generalist Multimodal Large Language Models for Holistic Chinese Font Engineering

Chinese font production is a complex task that balances vi-sual consistency, vector editability, and topological integrity at a massivecharacter scale. Existing fragmented toolchains, relying on manual rules,often lead to geometric redundancy and defects. This paper introducesFontCopilot, a multimodal large language model that performs raster-to-vector conversion, Bézier curve sparsix001Ccation, defect marking, and geo-metric correction within a single model. We elevate font engineering fromexplicit geometric rule constraints to structured glyph code understand-ing and rewriting, serializing Bézier curves into SVG XML. This enablesthe model to perform topological reorganization in the code space andinternalize implicit designer priors as structured reasoning constraints.FontCopilot integrates few-shot reference guidance and zero-shot gen-eralization mechanisms, balancing specix001Cc style transfer and universalstandard reconstruction. To advance the development of a unix001Ced fontengineering model, we constructed the CFCopilot-8M dataset, covering300 font types and 8 million glyph samples. Under progressive multi-taskhybrid training, the glyphs processed by FontCopilot show consistentimprovements in editability, contour compactness, and defect correction,validating its industrial-grade font production value.