AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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This paper formalizes data-dependent parameter symmetries and characterize loss invariance and the group-action axioms through infinitesimal conditions, which provide objectives for jointly learning group generators and nonlinear action maps.
Flow Reasoning Models is introduced, a novel framework for structured reasoning that adapts continuous flows over discrete structured outputs with a simple recurrent refinement mechanism by self-conditioning a flow model on its own past outputs, to turn one-shot denoising into iterative solution refinement.
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