Energy-based constraint networks learn structural coherence from contrastive pairs using frozen encoders, achieving 93.4% accuracy on text corruptions and 0.959 AUC on deepfake detection with composable branches that transfer across modalities via corruption respecification.
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Energy-Based Constraint Networks: Learning Structural Coherence Across Modalities
Energy-based constraint networks learn structural coherence from contrastive pairs using frozen encoders, achieving 93.4% accuracy on text corruptions and 0.959 AUC on deepfake detection with composable branches that transfer across modalities via corruption respecification.