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English(EN) Online Dense Reinforcement Learning with Planning-Grounding Agent for UI Navigation on Live iOS Apps

Apple 训练 UI 导航代理使用在线强化学习

Apple 研究人员开发了一种新的在线强化学习框架,用于训练代理在 iOS 真实应用程序上导航用户界面。该方法解决了前沿视觉语言模型的高推理成本和静态轨迹方法的脆弱性。该框架使用一个规划代理和一个 UI 接地模型,并使用 LLM-as-a-Judge 提供密集奖励信号。评估表明,与现有基线相比,泛化能力和训练收敛性有了显著提高,其 8B RL 代理在 iOS 真实应用程序上的表现优于 Gemini-3.5-Flash,并与 Gemini-3.1-Pro 相当。 AI

影响 这项研究可能带来更高效、更适应性强的 AI 代理用于移动应用程序交互,从而可能降低开发成本并改善用户体验。

排序理由 学术论文,详细介绍了用于 UI 导航的新型强化学习框架。

在 Apple Machine Learning Research 阅读 →

AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →

Apple 训练 UI 导航代理使用在线强化学习

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学术论文,详细介绍了用于 UI 导航的新型强化学习框架。
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报道来源 [2]

  1. Apple Machine Learning Research TIER_1 English(EN) ·

    Online Dense Reinforcement Learning with Planning-Grounding Agent for UI Navigation on Live iOS Apps

    While frontier vision-language models demonstrate strong capabilities in user interface (UI) navigation, their high inference costs prohibit everyday use. Conversely, smaller models trained via supervised fine-tuning (SFT) or offline reinforcement learning often memorize static t…

  2. arXiv cs.AI TIER_1 English(EN) · Peitong Duan, Khashayar Gatmiry, Jeffrey Nichols, Samy Bengio, Emmanuel Abbe ·

    面向直播iOS应用UI导航的在线密集强化学习与规划-接地代理

    arXiv:2610.39264v1 Announce Type: new Abstract: While frontier vision-language models demonstrate strong capabilities in user interface (UI) navigation, their high inference costs prohibit everyday use. Conversely, smaller models trained via supervised fine-tuning (SFT) or offlin…