A generalization bound based on a new feature-label distortion concept guides optimization of feature alignment versus target fitting in cross-modal adaptation and yields better empirical performance.
Conditioning reduces entropy (H(X—Y)<= H(X)), sometimes summarized as ‘information never hurts.’
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Rethinking Cross-Modal Fine-Tuning: Optimizing the Interaction Between Feature Alignment and Target Fitting
A generalization bound based on a new feature-label distortion concept guides optimization of feature alignment versus target fitting in cross-modal adaptation and yields better empirical performance.