TRUST is a test-time adaptation method for SSM vision models that uses uncertainty-guided traversal permutations to refine Mamba parameters via pseudo-labels and weight averaging, improving robustness on distribution shifts.
Learning to generalize: Meta- learning for domain generalization
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EAPO adapts wildfire models to new environments via k-nearest neighbor data retrieval and hybrid fine-tuning that emphasizes rare extreme events, achieving ROC-AUC 0.7310 on real data.
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TRUST: Test-Time Refinement using Uncertainty-Guided SSM Traverses
TRUST is a test-time adaptation method for SSM vision models that uses uncertainty-guided traversal permutations to refine Mamba parameters via pseudo-labels and weight averaging, improving robustness on distribution shifts.
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Environment-Adaptive Preference Optimization for Wildfire Prediction
EAPO adapts wildfire models to new environments via k-nearest neighbor data retrieval and hybrid fine-tuning that emphasizes rare extreme events, achieving ROC-AUC 0.7310 on real data.