Adaptively Masking Subnetworks to Rebalance Multi-Modal Optimization
The core message of this paper is to propose a novel Adaptively Mask Subnetworks considering Modal Significance (AMSS) strategy to rebalance the optimization of different modalities in multi-modal learning, thereby alleviating the modality imbalance problem and improving overall performance.
