研究人员开发了一种新的机器学习方法，用于训练计算机使用代理（CUAs）来评估图形用户界面（GUIs）的可用性。该方法优先考虑关键交互流程，模拟类似人类的交互，并预测一个数值可用性分数。训练好的代理uxCUA在准确性和批评生成方面表现优于更大的模型，旨在为人类计算机交互中的自动化可用性评估奠定数据驱动的基础。 AI
影响 自动化了一个成本高昂的过程，可能加速UI开发周期并改善用户体验。
排序理由 学术论文，详细介绍了用于自动化GUI可用性评估的新型机器学习方法。
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arXiv:2604.26020v1 Announce Type: new Abstract: Usability testing with experts and potential users can assess the effectiveness, efficiency, and user satisfaction of graphical user interfaces (GUIs) but doing so remains a costly and time-intensive process. Prior work has used com…
Usability testing with experts and potential users can assess the effectiveness, efficiency, and user satisfaction of graphical user interfaces (GUIs) but doing so remains a costly and time-intensive process. Prior work has used computer use agents (CUAs) and other generative age…