AINeutralarXiv – CS AI · 14h ago5/10
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Enhancing Multimodal Large Language Models for Ancient Chinese Character Evolution Analysis via Glyph-Driven Fine-Tuning
Researchers have developed GEVO, a glyph-driven fine-tuning framework for multimodal large language models designed to analyze the evolution of ancient Chinese characters. The study introduces a comprehensive benchmark with 11 tasks and over 130,000 instances, demonstrating that even smaller 2B-scale models can achieve significant performance improvements in understanding character evolution and historical text transformation.