Source-Learned Reliance for Selective Test-Time Adaptation of Multimodal Time Series
CARAT is a multimodal test-time adaptation method that intelligently decides whether to omit or attenuate noisy sensor streams during adaptation. It achieves this by training a backbone to learn how much it relies on each modality during source training. This learned reliance profile guides the runtime decision, leading to superior performance with significant computational savings compared to existing methods.