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Perfect-Reconstruction View of AddUNet and a Residual Full-Rate Architecture
A new arXiv paper reframes the AddUNet model through the lens of perfect reconstruction and describes how it can operate at full rate. The authors introduce a residual full-rate perfect-reconstruction design aimed at task-directed representation learning, building on the architecture's survivor-skip structure. The work is theoretical and architectural rather than a released product or benchmark result.