AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Influence Calibration for Self-Distillation (ICSD) improves all matched aggregate metrics over trust-only allocation under Group Relative Policy Optimization (GRPO) and Group-in-Group Policy Optimization (GiGPO) and raises cosine compatibility with the RL gradient.
This work proposes Class-wise Reliability-Aware Distillation (CRAD), which, per class, first discards teachers that disagree with the peer consensus and then takes a weighted average of the rest, weighting each teacher by its per-class reliability (precision, or inverse variance).
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