AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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State-Matched Routing and Contextualized Self-Distillation (SMRC-SD), which explicitly determines when and how a privileged trajectory should guide an on-policy student, consistently outperforms unconditional successful full-path distillation.
Refusal-Calibrated Group Relative Policy Optimization (RC-GRPO) is proposed, a calibrated RL strategy that strengthens the refusal ability of MLLMs while preserving localization performance, and enforces"None" outputs in rollouts for valid advantage estimation on negative samples and applies a penalty to prevent over-r...
This work proposes Greedy Orthogonal Token Selection (GOTS), a training-free and query-agnostic method that achieves higher average performance retention than the strongest evaluated baselines, and a controlled OCRBench study shows that it reduces model-side time-to-first-token after accounting for selection overhead.
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