Modality-Aware SAM: Sharpness-Aware-Minimization Driven Gradient Modulation for Harmonized Multimodal Learning

The introduction of Modality-Aware Sharpness-Aware Minimization (M-SAM) marks a significant advancement in multimodal learning. This innovative framework addresses the common issue where dominant modalities overshadow others, which can hinder generalization. By optimizing learning through a three-step process that identifies the dominant modality based on its contribution to accuracy, M-SAM enhances the effectiveness of both early and late fusion scenarios. This development is crucial as it opens up new possibilities for more balanced and effective learning across various modalities, making it a noteworthy contribution to the field.