AI RESEARCH
WebAccessVL: Violation-Aware VLM for Web Accessibility
arXiv CS.AI
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ArXi:2602.03850v2 Announce Type: replace-cross We present a vision-language model (VLM) that automatically edits website HTML to address violations of the Web Content Accessibility Guidelines 2 (WCAG2) while preserving the original design. We formulate this as a supervised image-conditioned program synthesis task, where the model learns to correct HTML given both the code and its visual rendering. We create WebAccessVL, a website dataset with manually corrected accessibility violations.