An Automated Artistic Image Aesthetic Evaluation Framework via Expert Knowledge Injection into Large Vision-Language Models
The proposed AEKI framework translates formal art principles into structured, machine-executable instructions and indicates that domain knowledge can be incorporated into LVLM evaluation through a transparent rule-based layer, supporting applications in digital curation, computational aesthetics, and art education.