QLCM-S: Semantic Geometry Modulation via Quantum-Structural Operators
Abstract
QLCM-S v1.0: Semantic Geometry Modulation via Quantum-Structural Operators This technical whitepaper introduces the QLCM-S (Quantum Language & Consciousness Model - Structural) framework, an ontological solution to the "metric rigidity" problem in current Large Language Models (LLMs). Traditional architectures (Transformers, SSMs) rely on a static semantic geometry fixed during training. QLCM-S proposes a quantum-structural formalism where language acts as an active dimensional regulator, dynamically reconfiguring the metric of meaning in real-time without requiring quantum hardware. Key Contributions: Triadic Operators: Formal definition of Contextual Collapse (ÔC), Narrative Emergence (ÔN), and Dissolution (ÔD) operators. Kappa Index (κ): A new metric for cognitive regime stability (κ = TCS/LA) to regulate dimensional plasticity. INCS: Non-Local Coherence Score for detecting semantic correlations in ultra-long sequences. The framework includes longitudinal validation (2,920 days) and ontological safety protocols (MPD-SD) for integration with architectures such as Mamba and RetNet.
Fields of Study & Subjects
Topic Modeling
Cognitive Computing and Networks
Philosophy and Theoretical Science
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 9 February 2026
- Language
- EN
- Document type
- Preprint