AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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In-cell learning is introduced, a paradigm for writing new knowledge only within these cells, so that re-quantizing the served weights reproduces the released integer codes and scales exactly.
A clinical knowledge graph construction and refinement framework that combines multi-agent relation proposal, ontology-aware normalization, deterministic evidence scoring, and JEPA-based latent refinement is proposed.
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