AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Metro-WM is introduced, a hierarchical framework that issues sub-goals by retrieving genuine states from prior experience rather than generating ungrounded latent vectors that achieves superior long-horizon success rates and maintains robust performance under extremely sparse dataset conditions.
A neuro-symbolic framework for ontology-grounded KG construction combining open-domain extraction, embedding-based canonicalization of types and predicates, and targeted LLM-based correction of ontology violations is proposed.
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