发现自适应检测器在数据污染下会突然失效,提出可保证安全的无标签校准方法。
Self-Poisoning in Adaptive Out-of-Distribution Detection: A Sharp-Threshold Theory and Certified Label-Free Calibration
- 用广义波利亚瓮模型揭示记忆库污染的动态规律,证明存在临界阈值。
- 实测各类编码器的斜率均接近1,96组实验中预测阈值与实际崩溃点一致。
- 设计无标签认证门控机制,可彻底消除污染导致的性能崩溃。
测试时自适应分布外(OOD)检测器通过更新未标注数据流中的记忆库实现。我们证明该适应过程遵循可证明的动力学规律:将库中杂质建模为广义波利亚瓮,可证几乎必然收敛至均场平衡,其斜率相当于繁殖数。当斜率低于1时,杂质保持良性;高于1时,库被完全污染,检测器崩溃。实测各编码器家族的接受核呈线性关系(R² ≥ 0.996),斜率均略低于1(协议特征),表明此类检测器设计上处于临界状态。在96种设置下,预测阈值与实测崩溃点高度吻合,无门控字典的性能损失最高达0.163 AUROC。进一步证明,仅读取冻结储备的认证准入门可切断反馈回路,在任意污染率下(包括对抗性污染)均消除相变,且无需标签即可控制误报率。针对漂移下的静态校准失败问题,提出CDC方法,可在所有受漂移影响的样本中无标签恢复名义误报率。最后证明两世界不可能定理:无标签情况下,漂移与污染不可区分,强制闭式性能上限,本方法逼近该极限。整体给出了无标签自适应OOD检测的完整可能性/不可能性刻画。
原文摘要 · Abstract (English)
Test-time adaptive out-of-distribution (OOD) detectors update a memory bank from the unlabelled stream. We show this adaptation obeys a provable dynamical law. Modelling bank impurity as a generalized Pólya urn, we prove almost-sure convergence to a mean-field equilibrium whose slope acts as a reproduction number. Below one, impurity stays benign. Above one, the bank is fully poisoned and the detector collapses. The measured admission kernel is affine ($R^2 \ge 0.996$) with slope just below one in every encoder family (a protocol signature), so this detector class is near-critical by design, and across 96 settings the predicted threshold matches the empirical collapse, where ungated dictionaries lose up to $0.163$ AUROC. We then prove that a certified admission gate, reading only a frozen reserve, severs the feedback loop and removes the transition at every contamination rate, even adversarially, while controlling false positives label-free. For the complementary static-calibration failure under drift we give CDC, which restores nominal FPR label-free on all tested drift-affected cells. Finally we prove a two-world impossibility theorem. Drift and contamination are indistinguishable without labels, forcing a closed-form power ceiling our procedure approaches. Together these give a complete possibility/impossibility characterization of label-free adaptive OOD detection.
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