AINeutralarXiv – CS AI · 18h ago6/10
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Training-Inference Kernel Contracts: Bounding Divergence in Post-Training and Deployment
Researchers propose 'kernel contracts,' a framework for managing divergence between training and inference implementations of AI models that operate at different precision levels. The work formalizes how finite-precision optimizations can produce different outputs at identical weights and provides mathematical bounds on resulting policy drift, with implications for reliable AI deployment.