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Achieving competitive accuracy with fewer parameters, Self-Routed Tensor Adapters redefine the landscape of visual model adaptation across heterogeneous domains.
Generative randomization can effectively break spurious correlations, leading to a 92.5% worst-group accuracy on challenging distribution-shift tasks.
