AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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FluxLite is introduced, a lightweight, training-free proposal-control framework for discrete diffusion, identifying a tilted-path coverage factor that governs robustness to score error, together with finite-particle convergence for a fixed controlled Feynman-Kac recursion.
This work proposes a multi-mask diffusion model (MultiMDM) that preserves the masking structure towards few-step generation and derives a closed-form ELBO training objective for MultiMDM that supports continual training from pretrained MDMs.
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