IHR: A Diagnostic Framework for Inference Stability Under Constraint
A recent study published on arXiv (2604.19760) presents the Inference Headroom Ratio (IHR), a dimensionless metric designed to assess inference stability in limited decision-making systems. This ratio clarifies the connection between a system's effective inferential capacity, denoted as C, and the total uncertainty and constraint load, represented as U+K, from its surrounding environment, indicating how close the system is to an inference stability limit. In three controlled experiments, IHR proved to be a measurable risk factor with a logistic correlation to the likelihood of collapse, identifying a critical threshold of IHR* ≈ 1.19. Additionally, it effectively indicates nearness to the stability boundary amid environmental noise and can be actively regulated, decreasing the system's collapse rate from 79.4% to 58.7% and reducing IHR variance by 70.4%.
Key facts
- IHR is a dimensionless diagnostic quantity for inference stability.
- IHR formalizes relationship between inferential capacity C and uncertainty/constraint load U+K.
- Critical threshold IHR* ≈ 1.19 estimated from logistic curve.
- Active regulation of IHR reduces collapse rate from 79.4% to 58.7%.
- IHR variance reduced by 70.4% through active regulation.
- Three controlled experiments conducted.
- Paper published on arXiv with ID 2604.19760.
- IHR captures proximity to inference stability boundary.
Entities
Institutions
- arXiv