 of the layers in the model
demonstrate redundancy in global computation. In addition, conventional
attention mechanisms exhibit low-frequency inertia issues. To address these
issues, we propose \textbf{P}seudo \textbf{S}hifted \textbf{W}indow
\textbf{A}ttention (PSWA), which fundamentally mitigates global model
redundancy. PSWA achieves intermediate global-local information interaction
through window attention, while employing a high-frequency bridging branch to
simulate shifted window operations, suppleme