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UC San Diego
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Achieving over 51% accuracy improvement, MM-CBM redefines interpretability in multimodal deep learning by aligning image and text features with natural concepts.
Achieve interpretability in continual learning without sacrificing accuracy: CI-CBM outperforms existing interpretable methods by 36% while matching black-box model performance.
