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The University of Tokyo
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Negative curvature can amplify PWGF approximation errors, but subsequent positive curvature can recover accuracy over growing time horizons, enabling stable optimization in non-convex landscapes.
Masked generative models can break the linear evaluation barrier during parallel decoding without ever needing to fully reconstruct the underlying token dependency graph.
