AI RESEARCH
Inference Headroom Ratio: A Diagnostic and Control Framework for Inference Stability Under Constraint
arXiv CS.AI
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ArXi:2604.19760v1 Announce Type: new We present a simulation-based evaluation of the Inference Headroom Ratio (IHR), a dimensionless diagnostic quantity for characterizing inference stability in constrained decision systems. IHR formalizes the relationship between a system's effective inferential capacity C and the combined uncertainty and constraint load U + K imposed by its operating environment, and is intended to capture proximity to an inference stability boundary rather than output-level performance.