AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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The exact selection time for an isolated cycle of NOTEARS and DAGMA is derived, and a truth-free separation statistic predicts selection time on 320 official NOTEARS/DAGMA trajectories.
The resulting lesson is task-specific: a first stage for generated controls should be judged by control fidelity, downstream relevance, and graph compatibility together.
Cross-scale heterogeneous MLLM fusion is recast as selective language-side reasoning transfer within a narrow, low-interference regime, rather than broad capability inheritance, to recast cross-scale capability transfer within a narrow, low-interference regime.
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