AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Findings suggest a practical role for LLMs as validated explanation components rather than primary rankers, with rationale quality evaluated separately from ranking accuracy.
This study evaluates survival models that predict time-to-repurchase directly, and adopts Exponential AFT for probability-consuming surfaces and Log-Normal for pure ranking, exposing a principled calibration-ranking trade-off within a single AFT family.
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