Introduces SGR and TIAT for robust dataset distillation that suppresses noise while preserving knowledge under noisy supervision.
arXiv preprint arXiv:2406.18561 (2024)
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DO-ALL applies dataset distillation to generate synthetic source anchors that stabilize continual test-time adaptation under evolving domains without storing original source data.
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Robust Trajectory Distillation: Hybrid Reweighting Meets Teacher-Inspired Targets
Introduces SGR and TIAT for robust dataset distillation that suppresses noise while preserving knowledge under noisy supervision.
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Distill Once, Adapt Life-Long: Exploring Dataset Distillation for Continual Test-Time Adaptation
DO-ALL applies dataset distillation to generate synthetic source anchors that stabilize continual test-time adaptation under evolving domains without storing original source data.