The widespread diffusion of Large Language Models (LLMs) has ushered in a transformative era across numerous research domains, including web accessibility. In fact, they can potentially offer automated solutions for generating accessible content, performing accessibility testing, and enhancing the overall user experience for individuals with disabilities. In this paper, we investigate how LLMs can be successfully employed to evaluate and correct web accessibility. Then, we delve into the positive implications and the current challenges derived from the interaction between developers and LLMs in this specific context. Finally, we present some future directions that could be explored to ensure that web content remains accessible to all.
Adrian Mirza, Nawaf Alampara, Sreekanth Kunchapu, Benedict Emoekabu, Aswanth Krishnan, Tanya Gupta, Macjonathan Okereke, Amir Mohammad Elahi, Mehrdad Asgari, J. Eberhardt, Maximilian Greiner, Caroline T. Holick, Christina Glaubitz, Tim Hoffmann, Lea C. Klepsch, Yannik Köster, Fabian Alexander Kreth, Jakob Meyer, Santiago Miret, Michael Ringleb, Nicole C. Roesner, Ulrich Sigmar Schubert, Leanne M. Stafast, Dinga Wonanke, Michael Pieler,
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