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Hallucinated details in super-resolution are not just random noise; they reveal a fundamental spectral mismatch that can be corrected by shaping the generative process itself.
Even with partial observability from manipulator truncation, StableIDM recovers stable action predictions, boosting downstream VLA real-robot success by 17.6%.
EVT achieves 86.6% top-1 accuracy on ImageNet-1k without extra training data, redefining the potential of Vision Transformers in computer vision.
