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Oct 13 · Tuesday

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  1. DrivingBench 发布:让视觉语言模型驾驶丰田 Corolla 绕桩

    提出 DrivingBench,评测通用视觉语言模型能否闭环驾驶真车

    Published
    Evaluated models
    GPT-6 Astra, Claude Fable 5.1, Grok 4.6 and others4
    Abstract仅 Astra 第二次跑完低速锥桶路线。

    DrivingBench 评测通用 VLM 能否自己闭环开真车,推理延迟也算进任务。

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  2. DIBench:面向移动 GUI 智能体多候选选择决策完整性的安全基准

    用 DIBench 评测移动 GUI 智能体被 UI 注入后的决策完整性

    Published
    Evaluated models
    Qwen2.5-VL(32B), Qwen3-VL(32B), GUI-Owl(32B) and others7

    Abstract论文提出移动智能体决策完整性基准 DIBench,发现欺诈 UI 注入诱导目标选择并推高完成率,通用防御收益不稳定。

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  3. MMSkillRisk:多模态技能图像中的隐藏指令可诱导 Agent 执行未授权操作

    提出 MMSkillRisk 基准,评测多模态技能图像中的隐藏指令诱导 Agent 越权操作

    Published
    Evaluated models
    GPT-5.6-sol, Kimi-K2.6, Kimi-K3 and others6

    Abstract论文提出 MMSkillRisk 基准与 NCVA 攻击,揭示多模态技能中教学图像潜藏指令可引发未授权操作并与良性任务共存。

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  4. HazardArena:面向 VLA 模型的语义安全评测基准

    提出 HazardArena 基准,用孪生场景评测 VLA 的语义安全

    Published
    Evaluated models
    OpenVLA-OFT, π0, NORA and others4
    Abstractsafe-only 微调提升良性执行,也提升匹配不安全孪生上的危险完成。

    HazardArena 评测 VLA 在运动要求不变时,能否因语义风险而停手。

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