Zhi-Lin Zhu

Token-level visual dependence is the key to preventing catastrophic forgetting in multimodal continual learning, enabling models to adapt without losing prior knowledge.

By explicitly modeling spectral channel variations and inter-channel similarity, SPDDA overcomes the realism-diversity tradeoff in hyperspectral data augmentation, achieving state-of-the-art domain generalization performance.