AI can transform humanities scholarship by enabling large-scale analysis of visual archives—PAGE shows how vision-language models, grounded in human annotation, can extract meaningful patterns from thousands of comics that would be impossible to study manually.
This paper presents PAGE, an AI framework for analyzing comics and manga at scale. It automatically parses pages into panels and text, annotates visual content using vision-language models following human codebooks, and validates findings against human annotation.