AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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A Symbolic-RAG-Generative architecture centered on the Goal-oriented Retrieval-Augmented Conversation Engine (GRACE) is proposed, which establishes compelling symbolic-state performance across standard, multi-goal, RAG-detour, validation, refusal, and robustness scenarios.
The Hierarchical Consistency Framework is presented, a post-hoc, model-agnostic audit of three distinct levels of a RAG process: the knowledge corpus, the final retrieved context, and the generated answer, showing that the three diagnostic levels can dissociate.
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