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Enhancing Multimodal Large Language Models for Ancient Chinese Character Evolution Analysis via Glyph-Driven Fine-Tuning

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学术前沿 5.3 分 — 中等质量:常规学术论文,有适度参考价值
原文: cs.AI updates on arXiv.org

评分 5.3 · 来源:cs.AI updates on arXiv.org · 发布于 2026-04-14

评分依据:中等质量:常规学术论文,有适度参考价值

Enhancing Multimodal Large Language Models for Ancient Chinese Character Evolution Analysis via Glyph-Driven Fine-Tuning

arXiv:2604.11299v1 Announce Type: cross Abstract: In recent years, rapid advances in Multimodal Large Language Models (MLLMs) have increasingly stimulated research on ancient Chinese scripts. As the evolution of written characters constitutes a fundamental pathway for understanding cultural transformation and historical continuity, how MLLMs can be systematically leveraged to support and advance text evolution analysis remains an open and largely underexplored problem. To bridge this gap, we…