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This work reformulate WSI token pruning as a sequential selection process, enabling the model to autonomously learn an optimal routing strategy rather than relying on static heuristics.
A new evaluation framework that decouples MLLMs'capabilities to faithfully assess VTC quality is introduced, and the ZeroSense Benchmark is introduced to ensure low semantic correlation of testing samples.
Introduction The superior clinical utility of 7T magnetic resonance imaging (MRI) is constrained by high acquisition costs and limited scanner availability. While deep learning-based 3T-to-7T synthesis offers a potential solution, prevailing models typically rely on heavy parameterization, which increases computational...
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