AKRM-RIR: Recursive Instability Regulation for Hallucination-Aware Language Model Inference

This record contains the v1.0 technical note and reproducibility package for AKRM-RIR: Recursive Instability Regulation for Hallucination-Aware Language Model Inference. AKRM-RIR is a lightweight, model-agnostic inference-time control framework that treats hallucination risk as a graded instability phenomenon during language model generation. The framework estimates an epistemic reliability score μ_t, computes an instability functional K(μ)=4μ(1−μ), and applies refusal gating, recursive smoothing, and a Proper Exit mechanism under high-uncertainty conditions. This release includes the preprint PDF, LaTeX source, a minimal Python prototype, a 40-prompt benchmark sample, evaluation outputs, and trace logs. The reported results should be interpreted as preliminary findings on a small controlled benchmark, not as a fully validated large-scale evaluation. Version: v1.0 Status: Preprint / Not peer reviewed Code status: Minimal reproducibility package included License: CC-BY 4.0 for paper and text materials; MIT License for code