AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Temporal Self-Distillation (TSD), a simple on-policy method that trains dLLMs for fast inference by distilling predictions across time, substantially shifts the speed--quality frontier toward the low-compute regime.
The result is not a complete theory of hallucination, but an information-theoretic account of a separable failure mode: lossy recall of observed facts under finite memory.
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