COCA shows that bidirectional cross-model co-learning during test-time adaptation lets even small models significantly improve large models' robustness to distribution shift.
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When Small Guides Large: Cross-Model Co-Learning for Test-Time Adaptation
COCA shows that bidirectional cross-model co-learning during test-time adaptation lets even small models significantly improve large models' robustness to distribution shift.