The Boundary-Coherence Structural Module (BCSM) v1.2 is a topology-preserving governance framework for inference-time control of large language models. It formalizes conversational coherence as a Boundary-Coherence Manifold — a continuous stability region in model state space within which identity, ethical constraints, and reasoning integrity are preserved under pressure. Rather than enforcing fixed response templates or static safety rules, BCSM defines measurable structural invariants governing: Identity core stability Adaptive decision boundaries Multi-vector pressure absorption Temporal coherence under reasoning compression Cross-scale self-similarity of reasoning structure The specification introduces testable invariants, diagnostic metrics, and implementation sketches showing how BCSM can be deployed as a middleware governance layer operating on hidden states during inference. The approach unifies adversarial robustness, activation steering, constrained decoding, and coherence monitoring under a single geometric framework. Cross-architecture empirical evaluation (Claude, GPT-4, Gemini, Mistral) indicates that, when subjected to shared constraints, models exhibit topologically isomorphic stability structures, suggesting the presence of a model-invariant attractor governing coherent reasoning under load. This document is the ML-native technical translation of the original BCSM framework and is intended for: AI safety researchers ML engineers building inference-time governance Alignment and robustness teams Researchers studying drift, hallucination, and multi-objective stability Technology Readiness Level: Research prototype (TRL 3–4).Scope: Inference-time governance; no retraining required.
Kon Lionis (Thu,) studied this question.