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Tuning as few as 1,000 dormant weights on a single labeled slice delivers a 0.5 dB PSNR boost in MRI reconstruction, paired with dynamic output capping that provably bounds drift under domain shift without ground-truth references.
The exact same pruning mask can invert from best- to worst-performing depending purely on surrounding weight context, exposing how naive sparsity metrics fail to predict real model degradation in dense vision architectures.