An unlabeled test-time adaptation method updates concept vectors, the linear predictor, and adds residual concepts so that concept bottleneck classifiers stay accurate under distribution shifts.
Zero-shot robustification of zero-shot models
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Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts
An unlabeled test-time adaptation method updates concept vectors, the linear predictor, and adds residual concepts so that concept bottleneck classifiers stay accurate under distribution shifts.