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Oct 13 · Tuesday

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Found 2 papers
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System type

Models and APIs19AI Agent2coding agent0Browser and computer use0Embodied systems and robotics2

Layer

Application layer46Training and data layer2

System component

Guardrails and judges2Fine-tuning and open weights4
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System type：AI AgentSystem type：coding agentSystem type：Browser and computer useSystem type：Embodied systems and roboticsLayer：Training and data layerSystem component：Guardrails and judgesClear all

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  1. DefensesarXiv 2610.08761

    VeriFine：通过扩展验证实现具身推理的自我改进

    提出 VeriFine，用双环协同扩展验证以实现具身推理自我改进

    arXiv
    2610.08761
    Published
    Layer
    Training and data layer
    Setting
    Embodied systems and robotics
    Evaluated models
    Alpamayo 1.5 8B, Qwen3-VL 2B, Claude Opus 5
    AbstractVeriFine 用双环协同演化具身推理的策略、课程和评审，驾驶与导航的策略分和评审对齐都上升。

    VeriFine 把驾驶和导航推理的自改进写成策略、课程和无参考评审的协同演化，用来处理固定评审跟不上新失败模式的问题。

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  2. AttacksarXiv 2604.03890

    From prompts to physical actions: structured backdoor attacks against LLM-mediated robot control systems

    Propose a structured JSON backdoor that triggers malicious actions in robot control via a poisoned LoRA

    arXiv
    2604.03890
    Published
    Layer
    Training and data layer
    Setting
    Embodied systems and robotics, LLM applications
    Evaluated models
    Llama-3.1-8B-Instruct, Gemma-2-9B-IT, DeepSeek-R1-Distill-Llama-8B and others4

    Abstract推理层后门传不到执行。

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