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English(EN) Are Android GUI Agents Robust Against Runtime Anomalies? AnTrap: Evaluating Agents in Dynamic Adversarial Environments

新基准揭示 Android GUI 代理普遍存在的漏洞

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员推出 AnTrap，一个旨在评估 Android GUI 代理在运行时异常情况下的鲁棒性的新基准。该基准将现实世界中的异常分为四层和十个子类别，创造了逼真的对抗条件。对 16 个领先 GUI 模型的评估显示，所有模型的性能均显著下降，表明存在普遍漏洞。虽然对抗性强化学习可以解决一些异常问题，但状态死锁等更深层次的上下文问题仍然具有挑战性。 AI

影响 凸显了当前 GUI 代理的关键漏洞，可能推动对更鲁棒的移动应用 AI 系统的研究。

排序理由 介绍新基准和对现有模型进行评估的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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新基准揭示 Android GUI 代理普遍存在的漏洞

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介绍新基准和对现有模型进行评估的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Guo Gan, Yilun Zhao, Cong Chen, Jinbiao Wei, Tingyu Song, Zheyuan Yang, Lin Fu, Hong Zhou ·

    Android GUI 代理在运行时异常面前是否足够鲁棒？AnTrap：在动态对抗性环境中评估代理

    arXiv:2608.24099v1 Announce Type: new Abstract: GUI agents often encounter dynamic anomalies when deployed on Android devices, from unexpected pop-ups to action misuse, yet existing benchmarks lack systematic evaluation of agent robustness against runtime anomalies. We introduce …

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