AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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DDFMitos-Net is proposed, a point-supervised teacher-student framework for distribution-aware proposal filtering that indicates stable and competitive point-supervised mitosis detection using low-cost point-level annotations.
SelfLift is introduced, a self-recovering progressive-resolution framework that derives both transition-repair signals and trajectory-aligned supervision from the generative model itself and reduces end-to-end latency across FLUX, establishing a stronger speed-quality frontier for few-step diffusion.
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