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Hidden Trajectories Don't Lie: Correcting Corruption Drift for Test-Time Adaptation

Sabour, Amirhossein et al.
arXiv (All) · Papers
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machine-learning
Test-time adaptation (TTA) adapts pretrained models to distribution shifts encountered during deployment. However, most existing methods rely on the weight representations of the final layer or signals derived from the model's output probability distribution. We study hidden trajectories: the ordere
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