A Multi-Agent Framework for Accessible Web Code Generation
Year: 2026
Type: conference-paper
Abstract: Large Language Models (LLMs) have become widely used for automated code generation. However, their ability to produce accessibility-compliant web interfaces remains limited and underexplored. We present A11yAgent, a multi-agent framework for accessibility website generation that decomposes website creation into coordinated stages that refine user prompts, generate semantically structured code, automatically render and validate executability, evaluate accessibility, and iteratively repair detected violations. This design integrates accessibility constraints directly into the generation process, eliminating the need for manual deployment, external testing, and post-hoc remediation. To evaluate effectiveness, we conducted a comparative study with 20 professional front-end and full-stack developers. Participants generated websites using standard LLM-based workflows, while the same prompts were processed through A11yAgent. Accessibility compliance was assessed using automated tools. Results reveal consistent structural and semantic accessibility failures across state-of-the-art LLMs, whereas A11yAgent produces highly accessible outputs. Our results reveal current LLM accessibility blind spots and demonstrate how our multi-agent framework effectively bridges these gaps to ensure robust WCAG compliance.
Language: English
Subfield: Human Factors and Ergonomics
Field: Social Sciences
Domain: Social Sciences
SDG: Reduced inequalities
Open Access status: hybrid
OpenAlex ID: W7163149535