Enhancing Generalization of State Space Models for Domain Generalization

The core message of this paper is to enhance the generalizability of Mamba-like state space models (SSMs) towards unseen domains by proposing a novel framework named DGMamba. DGMamba comprises two key modules: Hidden State Suppressing (HSS) to mitigate the detrimental effect of domain-specific information in hidden states, and Semantic-aware Patch Refining (SPR) to encourage the model to focus more on the object rather than the context.