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• When LLM-Generated Code Perpetuates User Interface Accessibility Barriers, How Can We Break the Cycle?

  Alexandra-Elena Gurita, Radu-Daniel Vatavu · 2025 · Proceedings of the 22nd International Web for All Conference (W4A 2025)

  This paper evaluates the ability of large language models (LLMs) to generate accessible web user interfaces, comparing ChatGPT (GPT-4-turbo) and Claude (3.5 Haiku) across two prompting strategies: accessibility-agnostic prompts ("Design the homepage of a banking app") and…

  large language models · WCAG compliance · automated accessibility · prompt engineering · code generation

• LLMs for Accessibility in Mobile Apps: Detection and Repair

  Wajdi Aljedaani, Ahmed Aljohani, Marcelo M. Eler, Abdulrahman Habib, Hyunsook Do · 2025 · Proceedings of the 22nd International Web for All Conference (W4A 2025)

  This study evaluates the capacity of three large language models—GPT-4o, Gemini 1.0 Pro, and Llama 3—to detect, classify, and remediate accessibility violations in Android mobile applications. While prior LLM accessibility research has focused primarily on web applications, this…

  mobile accessibility · large language models · Android accessibility · automated accessibility testing · accessibility remediation

• Does ChatGPT Generate Accessible Code? Investigating Accessibility Challenges in LLM-Generated Source Code

  Wajdi Aljedaani, Abdulrahman Habib, Ahmed Aljohani, Marcelo Eler, Yunhe Feng · 2024 · Proceedings of the 21st International Web for All Conference (W4A)

  This paper presents the first empirical evaluation of the accessibility of web code generated by ChatGPT (GPT-3.5), examining both how accessible the generated code is and how well the model can fix accessibility violations. The study involved 88 web developers who prompted…

  web accessibility · large language models · ChatGPT · automated testing · WCAG

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