English(EN) Verdict Instability of OOD Scores under Reference Resampling

新指标量化 AI 模型中 OOD 分数的不稳定性

作者 PulseAugur 编辑部 · [1 个来源] · 2026-09-02 04:00

一篇题为《参考重采样下 OOD 分数的判决不稳定性》的新论文介绍了一种称为判决不稳定的指标，用于量化当参考数据集被重采样时，分布外 (OOD) 分数的变异性。这种不稳定性计算为沿查询方向分配的类别的类内离散度，除以该类别参考计数的平方根。研究表明，局部离散度的估计量对于实践者来说带有预期的符号，并且基于错误符号分数的弃权可能比随机弃权更差。 AI

影响引入了一个新的指标，用于评估 AI 模型中分布外检测的可靠性。

排序理由该集群包含一篇详细介绍评估 AI 模型性能新指标的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv stat.ML TIER_1 English(EN) · Donghoon Lee, Shinjin Kang · 2026-09-02 04:00

参考重采样下 OOD 分数的判决不稳定性

arXiv:2609.00691v1 Announce Type: cross Abstract: Post-hoc out-of-distribution detectors are fitted on a finite reference set, so every score they produce is an estimate. If we had chosen a different set, some verdicts would have moved. We measure that movement by resampling the …

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参考重采样下 OOD 分数的判决不稳定性

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