AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Discrete diffusion models and flow matching have emerged as powerful frameworks for generative modeling over discrete state spaces, yet efficient few-step generation remains a fundamental challenge. In this work, we introduce the Discrete Average Generator, a principled extension of MeanFlow to Continuous-Time Markov C...
This work introduces Elastic Threshold Attention, an end-to-end trainable architecture that rivals dense model quality under hardware-aligned block-sparse decoding, and introduces an offline calibration algorithm for domain-specific deployments that freezes per-head constant thresholds, cutting attention compute by an...
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