Can AI Concepts Truly Generalize Across Different Domains? Experiments Reveal Answers
SMRTR summary
A new self-explaining neural network approach improves concept generalization across domains for image classification tasks. The method combines representative concept extraction, self-supervised contrastive learning, and prototype-based grounding to outperform baselines on four datasets, demonstrating better cross-domain performance and concept interpretability.
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