AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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This work constructs a family with quadratic arithmetic in the matrix dimension when the physical block size remains fixed, and derive finite-shape constraints for GPU execution, and treats these results as a feasibility and trainability check for the proposed approach at small scale, leaving further investigation to f...
Zarya is introduced, a family of hybrid language models that jointly optimizes an autoregressive (AR) objective and a masked-diffusion objective within a single architecture, demonstrating performance on standard benchmarks while offering a principled integration of autoregressive and diffusion paradigms.
A gap between algorithmic losslessness and its implementation under finite-precision arithmetic is demonstrated and motivated, to motivate evaluating lossless speculative decoding at the level of exact generation trajectories as well as downstream task performance.
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