AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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This work gives the first reliability study of the TabICL setting, with TabICL as the TFM and half of each graph as labeled context, and introduces HG-DAPS, a training-free diffusion score whose homophily gate reads only the in-context labels, so the guarantee still holds.
Few-shot anomaly detectors are judged by ranking metrics, yet deployment requires an alarm threshold with a controlled false-alarm rate (FAR). We ask how much normal evidence, in images or category units, is needed to certify such a threshold for an unseen category. Using a frozen DINOv2 principal component analysis (P...
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