AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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This work presents a taxonomy-guided evaluation protocol for temporal fidelity, in which the applicable measurements are determined by the data rather than fixed in advance, and recasts utility and privacy evaluation over trajectories rather than isolated rows.
Seq2Synth is introduced, a unified benchmark for assessing temporal and schema properties to determine applicable evaluations, covering timestamp, cross-sectional, longitudinal, and structural fidelity, alongside trajectory-aware utility and privacy.
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