AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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This work proposes a task-specific pruning pipeline, named Cut-ViT, which first construct gram anchoring matrices from both spatial and semantic perspectives, and performs the subspace decomposition to extract the corresponding subspace bases.
A lightweight framework that leverages a memory bank to augment DCT-based low-frequency features and employs graph-enhanced cross-attention for effective visual-textual alignment is proposed, highlighting its efficiency and potential for clinical deployment.
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