AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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PaCTS is introduced, which generates a small set of instance-adaptive latent prompts in the form of continuous embedding tokens conditioned on the visible context, which serve as compact context surrogates for frozen TSFMs.
Tabby, a long context probabilistic time series foundation model, is released together with a complete and open recipe of how it was built, which achieves competitive zero-shot forecasting performance on GIFT-Eval and the out-of-distribution TIME benchmark.
FlowTSFM is introduced, an encoder architecture that interprets depth as a recurrent transport process: a single Transformer block is iteratively applied with shared parameters, while a quantile-flow objective supervises intermediate states along a prescribed trajectory from a prior distribution toward the final foreca...
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