AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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This work introduces \texttt{DP-SPIN}, a trusted-curator framework for aggregate measurement and summarization over semantic concepts fixed independently of the protected target records, and establishes record- and user-level DP guarantees under add/drop and replacement adjacency.
Existing LLM techniques are reorganized into design patterns for hermeneutically responsible use in interpretive settings and digital hermeneutics is treated as a literacy: the capacity to read AI-mediated texts by examining frames, provenance, and readings, and by contesting outputs.
Low-Pathwidth GRAND (LP-GRAND) is developed for binary phase-shift keying (BPSK) with precision matrix $Q, and induces an ML codeword for any nonempty binary codebook with equiprobable codewords.
A perturb-then-project mechanism that adds Gaussian noise calibrated to global sensitivity of the chosen score release regime and then projects the result onto the feasibility set of valid cosine objects, and evaluates the mechanism across RAG, face recognition, semantic retrieval, image similarity, and recommender-sys...
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