AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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A critical prerequisite of generative recommendation is designing semantic identifiers (SIDs) that are both scalable to large item sets and efficiently learnable. Existing SID learning methods fundamentally rely on Top-1 hard assignment during vector quantization. While heuristic strategies -- such as clustering-based...
AD-Reranker is proposed, a novel framework that shifts reranker training from proxy imitation to answer-driven utility optimization, and reformulate the reranker as an environment-grounded agent that interacts with a downstream reader, modeled as a deterministic environment.
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