Cascade Sadovnikov v4.9 is a deterministic semantic stability verification framework designed for hallucination mitigation and structural admissibility analysis in LLM and RAG systems. The framework evaluates semantic persistence under controlled hostile perturbation using SOP (Sadovnikov Orbit Persistence), archival drift analysis through BDS (Beta Drift Stability), and κ-based admissibility constraints. Unlike traditional moderation or keyword filtering systems, Cascade Sadovnikov focuses on structural stability of generated information under deformation rather than direct factual verification. The architecture integrates:- hostile semantic perturbation,- orbit persistence analysis,- archive-constrained drift detection,- observer reduction,- deterministic admissibility gating. Preliminary benchmark simulations on TruthfulQA, FEVER, and RAG-style hallucination datasets indicate measurable improvements in semantic robustness and reduction of unstable generations. This work does not claim universal truth detection. Cascade Sadovnikov is presented as a structural semantic admissibility framework within the Information-Dynamic Theory (IDT) research program. Document prepared with technical assistance of LLM for structuring the author’s IDT materials.
Aleksei Sadovnikov (Thu,) studied this question.