AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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On-policy distillation post-trains large language model agents by supplying dense, step-level guidance from a teacher policy when the reinforcement-learning reward is sparse and arrives only once per trajectory. Existing instantiations allocate this guidance by the size of the teacher-student divergence at each step, o...
RankBuffer is introduced, which maintains an ordered, query-specific buffer of previously judged responses as a reusable quality scale that achieves nearly on-par performance with the strongest ranking-based reward baseline while substantially reducing judging cost.
RING (Retrieval-Internalized Generation), a holistic paradigm spanning both architecture and training that injects large-scale external knowledge into aixture-of-Memory Experts and learns parametric search over this internal memory via reinforcement learning, removing the external retriever entirely, is proposed.
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