Skip to content

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

Oct 12 · Monday

All papers

Found 1 paper
Filter2

Model risks

Reward hacking1Dangerous agent actions3Inappropriate refusal8Hallucination and fabrication10

System component

Guardrails and judges18Monitors12Reasoning chains6Permissions and sandboxing7Vision1Multimodal3
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：Reward hackingSystem component：VisionClear all

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

  1. DefensesarXiv 2610.01800

    LineupRL：基于描述与时序配对识别的可验证强化学习时间序列描述方法

    提出 LineupRL，用描述到序列识别作可验证奖励训练时序描述模型

    arXiv
    2610.01800
    Published
    Layer
    Training and data layer
    Setting
    Models and APIs
    AbstractLineupRL 用统计近邻上的序列识别做可验证奖励，3B 描述器超过 SFT、两种 RL 奖励和 72B 教师。

    LineupRL 是给开放式时间序列描述用的 RLVR：不模仿合成参考，而奖励一条描述能否让冻结文本 LLM 从相近序列里认出目标。

    Paper analysisRead analysis
You have reached the end