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Undistillable: Making A Nasty Teacher That CANNOT teach students

ICLR 2021 · Label-efficient and robust learning › Knowledge distillation · approach: Distillation with causal and adaptive guidance · 19 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Add self-undermining training to a normally trained teacherResNet-18 · CIFAR-10 standard KDstudent accuracy: 87.75 (+1.11) -> 82.46 (-4.18)Hurt
Add self-undermining training to a normally trained teacherResNeXt-29 · CIFAR-100 standard KD with MobileNetV2student accuracy: 72.43 (+3.31) -> 1.55 (-67.57)Hurt
Add self-undermining training to a normally trained teacherResNet-18 · Tiny-ImageNet standard KD with MobileNetV2student accuracy: 55.99 (+4.27) -> 1.82 (-49.90)Hurt
Add self-undermining training to a normally trained teacherResNet-34 · CIFAR-10 data-free KD with DAFLstudent accuracy: 92.49 -> 86.15 (-6.34)Hurt
Add self-undermining training to a normally trained teacherResNet-34 · CIFAR-100 data-free KD with DAFLstudent accuracy: 71.06 -> 65.67 (-5.39)Hurt
Use CNN instead of ResNet-18 as the adversarial network (ablation)Self-undermining ResNet-18 teacher · CIFAR-10 standard KD to CNNstudent accuracy: 82.46 (-4.18) -> 77.12 (-9.52)Helped
Use ResNeXt-29 instead of ResNet-18 as the adversarial network (ablation)Self-undermining ResNet-18 teacher · CIFAR-10 standard KD to CNNstudent accuracy: 82.46 (-4.18) -> 82.75 (-3.89)No clear effect
Use a larger student, ResNet-50, for reverse KD (ablation)ResNet-18 normal teacher · CIFAR-10student accuracy: 94.98 -> 94.45 (-0.53)Hurt
Use a larger student, ResNet-50, with a nasty teacher (ablation)ResNet-18 teacher · CIFAR-10student accuracy: 94.98 -> 93.13 (-1.85)Hurt
Increase the self-undermining weight ω (ablation)Nasty teacher · CIFAR-10 and CIFAR-100student accuracyMixed
Vary distillation temperature τ_s from 1 to 20 (ablation)Nasty teacher · Knowledge distillationstudent accuracyMixed
Vary student KD balance factor α from 0.1 to 1.0 (ablation)Student distilling from a nasty teacher · Knowledge distillationstudent accuracyMixed

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