Skip to content

Translation in progress Some entries still include text in the original language.

Oct 12 · Monday

All papers

Found 3 papers
Filter2

Model risks

Deception and scheming6Reward hacking32Misalignment and value divergence17Dangerous agent actions3Dangerous capabilities3Inappropriate refusal13Hallucination and fabrication3

Layer

Model layer24Application layer15Training and data layer3
Select any value within a category; different categories must all match. Counts include the other filters you have selected.Another 305papers have no tags yet and are not included in filtered results.
Model risks：Hallucination and fabricationLayer：Training and data layerClear all

Another 305papers do not have category tags yet and are not included in filtered results.

  1. DefensesarXiv 2610.09496

    SOUL：用稀疏特征策略遗忘缓解 VLA 模型的状态幻觉

    提出 SOUL 稀疏特征策略遗忘，缓解 VLA 状态幻觉

    arXiv
    2610.09496
    Published
    Layer
    Training and data layer
    Setting
    Embodied systems and robotics
    Evaluated models
    OpenVLA, π0.5
    AbstractSOUL 以稀疏特征遗忘 VLA 状态幻觉。

    SOUL用稀疏特征引导的策略 unlearning 处理 VLA 的 state hallucination。

    Paper analysisRead analysis
  2. Evaluation and benchmarksarXiv 2610.08540

    论文提出按风险类别测量的对齐缩放定律框架

    提出分风险对齐标度律框架，测量各类风险的对齐负担如何随规模变化

    arXiv
    2610.08540
    Published
    Layer
    Training and data layer
    Setting
    Models and APIs
    Evaluated models
    Pythia (14m–2.8b), Qwen2.5 (0.5B–72B), Qwen2.5-Instruct (0.5B–14B) and others4
    Abstract论文提出了分风险对齐标度律框架，测得真实性与倾向纠错呈标度有益，但盲后门仍存活，揭示隐藏风险的长期挑战。

    本文提出了一个将大语言模型对齐难度形式化为可测量标度关系的理论框架与预注册评测协议。

    Paper analysisRead analysis
You have reached the end