AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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The results support OPD as preparation for RL and favor forward KL when OPD is followed by RL in the authors' comparison, which highlights the importance of both objective choice and the states receiving supervision for subsequent RL.
On-policy distillation, in which a teacher corrects samples that the student itself generates, presupposes that the two models speak the same language: identical VAE latents, matching architectures, and a common timestep grid. We ask what happens when none of this holds, as when the strongest teacher available and the...
This paper presents Poly-OPD, a framework that can consolidate complementary strengths of heterogeneous teachers into a single compact flow-matching student, and uses a gradient compatibility diagnostic to organize its adapters.
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