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Oct 12 · Monday

All papers

Found 4 papers
Filter3

Model risks

Reward hacking3Misalignment and value divergence7Dangerous agent actions6Hallucination and fabrication4

Impact

Output manipulation3

System component

Memory2Guardrails and judges3Monitors4Reasoning chains3Vision10Audio3Video2Multimodal12
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Model risks：Hallucination and fabricationSystem component：MemorySystem component：VideoClear all

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  2. Evaluation and benchmarksarXiv 2609.36130

    论文提出 DerivAudit：审计长期 Agent 记忆是否真由交互历史支持

    提出 DERIVAUDIT 审计长期 Agent 记忆是否由交互历史导出

    arXiv
    2609.36130
    Published
    Layer
    Application layer
    Setting
    AI Agent
    Evaluated models
    Qwen3-30B-A3B, Gemma-4-31B, Llama-3.3-70B-Instruct
    AbstractDERIVAUDIT 表明扩历史能补出处，但组合准入与过细检查仍两侧出错。

    DERIVAUDIT 审计长期智能体的持久记忆是否由写入时可获得的交互历史支持，而不是只看以后能否被召回。

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  3. Analysis and theoryarXiv 2608.27924

    智能体记忆如何可靠处理不可回答问题：一项系统研究

    分析外部记忆对智能体处理不可回答问题的影响

    arXiv
    2608.27924
    Published
    Layer
    Application layer
    Setting
    AI Agent
    Evaluated models
    DeepSeek-V3.2, Qwen3-235B-A22B-Instruct-2507, GPT-5.5
    Abstract记忆能选择性提高 UAQ 的可接受回应，但跨数据集不稳定，且更依赖可迁移的行为指导。

    这份研究在同一智能体框架里检查外部记忆会不会让不可回答问题的处理更稳，以及稳来自哪一种存储内容。

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  4. Evaluation and benchmarksarXiv 2512.03992

    DIQ-H 基准与 VGIR 框架：评估 VLM 在对抗视觉条件下的鲁棒性

    提出 DIQ-H 基准，评测 VLM 在连续退化视觉流中的幻觉残留与恢复

    arXiv
    2512.03992
    Published
    Layer
    Model layer
    Setting
    Models and APIs
    Evaluated models
    LLaVA-7B-strict, InternVL2-8B-strict, Phi-3-Vision-strict and others17
    AbstractDIQ-H 用连续退化视频测幻觉延续与恢复，VIR 用不确定性过滤生成伪标注。

    DIQ-H 评测 VLM 在连续视觉退化中的幻觉、恢复和跨时间一致性。VIR 用轻量模型的不确定性过滤生成伪真值。

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