AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Compass, an agentic router in which an LLM follows a routing recipe, gathers performance and cost evidence through tools, and optionally inspects candidate answers before selecting a model, is proposed and shown to improve accuracy and lower model-call cost relative to specialized and trained routing baselines.
An author-facing LLM system that generates a broad pool of atomic concerns and compresses them into a short report that provides broad coverage with a large candidate pool but compresses poorly is studied.
This work proposes VDA (Visual Distribution Anchoring), a training-free target adaptation framework that augments a frozen semantic classifier with class-level visual prototypes estimated offline from an unlabeled target pool, and shows that class-specific partitioning drives gains and that visually local pseudo-label...
An analytical framework coupling communication limits, a roofline GPU service model, stochastic latency, and utilization-aware cost across three model classes, three offloading strategies, and three communication generations is applied to New York City.
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