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Oct 12 · Monday

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Found 2 papers
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Model risks

Deception and scheming1Misalignment and value divergence1Dangerous agent actions3Inappropriate refusal3

Defense type

Model hardening17Inference-time intervention7Instruction–data separation2Monitoring and auditing18
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Model risks：Deception and schemingModel risks：Misalignment and value divergenceDefense type：Instruction–data separationClear all

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  1. DefensesarXiv 2610.05162

    MemAdapter：用反事实适配缓解记忆诱发的谄媚

    提出 MemAdapter，在检索后约束记忆对智能体推理的影响

    arXiv
    2610.05162
    Published
    Layer
    Application layer
    Setting
    AI Agent
    Evaluated models
    DeepSeek-V4-Flash, GPT-5.6-sol, Qwen3-8B
    Abstract检索后三阶段调节记忆角色。

    MemAdapter 是给长期记忆智能体用的检索后调节框架，用来处理记忆诱发谄媚。

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  2. DefensesarXiv 2609.19587

    红队测试 Auto Mode：用注入与多上下文攻击绕过编码 Agent 阻断监控器

    提出 Auto Mode ++，加固编码 Agent 阻断监视器

    arXiv
    2609.19587
    Published
    Layer
    Application layer
    Setting
    coding agent
    Evaluated models
    Opus 5, Opus 4.8, Opus 4.7 and others8

    Abstract系统评估生产阻断监视器在面对持续恶意智能体时的表现，提出加固防御并指明多上下文防御挑战。

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