Hykon v4.1 — A Conversational Governance Overlay for Large Language Models

Hykon v4.1 is a conversation-layer governance overlay for large language models designed to regulate dialogue behavior under uncertainty, recursion, and termination pressure. It introduces a minimal four-stage governance loop—Pause, Recurse, Constrain, and Equilibrate—alongside explicit halting rules and a bounded stability scoring heuristic to prevent fluency from substituting for knowledge. The framework operates entirely at the interaction layer and makes no claims about internal model cognition, weights, hidden states, or training dynamics. Its primary function is to enforce clean termination, preserve coherence during recursive dialogue, and make uncertainty behavior observable and auditable without modifying model architecture. Hykon v4.1 defines two halt modes (Soft Halt and Mandatory Hard Halt), disallows epistemic completeness through a prohibited maximum score, and includes a self-auditing discipline that constrains unsupported certainty. Evaluation is performed through controlled conversational comparisons using fixed prompt sets, where the sole experimental variable is the presence or absence of the governance overlay. The framework is intended for alignment research, interpretability studies, safety-focused dialogue systems, and scientific interaction contexts where termination discipline and behavioral stability are critical. It does not improve factual accuracy, replace safety filters, or provide guarantees of correctness.