AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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This work introduces Relative Generalization Invariance (RGI), the invariance of the validation-loss difference between any two tokens across models, and shows that RGI approximately holds across a wide range of optimizers and moderate architectural variations, suggesting that these choices induce an approximately unif...
RPS is proposed, a novel training-free decoding method that seeks mid-entropy positions as promising candidate pivots (where to decode), and determines their token assignment that yields the greatest downstream benefit via lookahead evaluation (what to decode).
Spiking neural networks (SNNs) offer a path to energy-efficient language modeling through sparse encoding and event-driven computation, but training capable spiking language models from scratch remains difficult. A practical alternative is ANN-to-SNN migration through knowledge distillation (KD), where a pretrained art...
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