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On Robust Prefix-Tuning for Text Classification

ICLR 2022 · Adversarial robustness and security › Attacks on text and graphs · approach: Adversarial prompts for language models · 9 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Add test-time batch-level prefix tuning against canonical activation manifoldsStandard prefix-tuning · SST-2, AG's News, and SNLI adversarial attacksaccuracy: 16.64 -> 50.36 (PWWS), 1.92 -> 44.65 (VIPER), 31.58 -> 58.54 (SCPN), 8.84 -> 46.68 (BUG), 5.05 -> 85.72 (UAT) on SST-2; Helped
Add test-time batch-level prefix tuning against canonical activation manifoldsStandard prefix-tuning · SST-2, AG's News, and SNLI clean dataaccuracy: 92.48 -> 92.59 on SST-2; 86.42 -> 86.50 on AG's News; 72.48 -> 72.74 on SNLINo clear effect
Use adversarial prefix-tuning instead of standard prefix-tuningPrefix-tuning · SST-2, AG's News, and SNLIaccuracy: SST-2 clean: 92.48 -> 93.57; SST-2 UAT: 5.05 -> 4.88Mixed
Use a fixed test batch size of 1 rather than adaptive batching (ablation)Robust prefix-tuning · SST-2 UATaccuracy: 85.72 -> 73.09Hurt
Use test batch size 2 or 4 instead of batch size 1 (ablation)Robust prefix-tuning · SST-2 UATaccuracy: 73.09 -> 84.73 (batch size 2); 73.09 -> 86.66 (batch size 4)Helped
Normalize batch activations before projection (ablation)Robust prefix-tuning with batch size 2 or 4 · SST-2 UATaccuracy: 78.20 -> 84.73 (batch size 2); 80.23 -> 86.66 (batch size 4)Helped
Tune bottom layers rather than top layers (ablation)Robust prefix-tuning · SST-2 development set attacksaccuracyHelped
Tune bottom 3 layers rather than larger numbers of layers (ablation)Robust prefix-tuning · SST-2 UATaccuracyHelped
Add PWWS adversarial data augmentation during training (ablation)Standard prefix-tuning · SST-2, PWWSaccuracy: 16.64 -> 48.11 (20 epochs); 16.64 -> 55.08 (50 epochs); 16.64 -> 56.62 (100 epochs)Helped
Add attack-specific adversarial data augmentation during training (ablation)Standard prefix-tuning · SST-2 attacks other than augmentation attackaccuracyMixed
Add robust prefix-tuning to adversarial data augmentation modelsSST-2 adversarially augmented prefix-tuning · SST-2 UATaccuracy: 10.43 -> 70.07 (PWWS augmentation, 20 epochs); 3.13 -> 83.47 (PWWS augmentation, 50 epochs); 7.91 -> 86.38 (PWWS augmentHelped
Stop adversarial prefix-tuning at 20 epochs instead of 100 (ablation)Adversarial prefix-tuning · SST-2 UATaccuracy: 4.88 -> 6.97 (word-level); 8.95 -> 8.57 (sentence-level)Mixed

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