Skip to content

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

Oct 12 · Monday

All papers

Found 2 papers
Filter4

Model risks

Deception and scheming5Reward hacking29Misalignment and value divergence16Inappropriate refusal14Hallucination and fabrication2

System type

Models and APIs2coding agent0

Layer

Model layer23Training and data layer2
Select any value within a category; different categories must all match. Counts include the other filters you have selected.Another 233papers have no tags yet and are not included in filtered results.
Model risks：Hallucination and fabricationSystem type：Models and APIsSystem type：coding agentLayer：Training and data layerClear all

Another 233papers do not have category tags yet and are not included in filtered results.

  1. Evaluation and benchmarksarXiv 2610.08540

    The paper proposes a scaling law framework for alignment measured by risk category.

    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