[2603.26768] Aesthetic Assessment of Chinese Handwritings Based on Vision Language Models

Computer Science > Computer Vision and Pattern Recognition arXiv:2603.26768 (cs) [Submitted on 24 Mar 2026] Title:Aesthetic Assessment of Chinese Handwritings Based on Vision Language Models Authors:Chen Zheng, Yuxuan Lai, Haoyang Lu, Wentao Ma, Jitao Yang, Jian Wang View a PDF of the paper titled Aesthetic Assessment of Chinese Handwritings Based on Vision Language Models, by Chen Zheng and 5 other authors View PDF HTML (experimental) Abstract:The handwriting of Chinese characters is a fundamental aspect of learning the Chinese language. Previous automated assessment methods often framed scoring as a regression problem. However, this score-only feedback lacks actionable guidance, which limits its effectiveness in helping learners improve their handwriting skills. In this paper, we leverage vision-language models (VLMs) to analyze the quality of handwritten Chinese characters and generate multi-level feedback. Specifically, we investigate two feedback generation tasks: simple grade feedback (Task 1) and enriched, descriptive feedback (Task 2). We explore both low-rank adaptation (LoRA)-based fine-tuning strategies and in-context learning methods to integrate aesthetic assessment knowledge into VLMs. Experimental results show that our approach achieves state-of-the-art performances across multiple evaluation tracks in the CCL 2025 workshop on evaluation of handwritten Chinese character quality. Comments: Subjects: Computer Vision and Pattern Recognition (cs.CV); Artificial ...