December 2, 2025Open Access

Meaning Unification Framework: A Dual-Tier Whitepaper Connecting Quantum–Geometric Structures and AI Semantic Stability

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Whitepaper explores integrating quantum phase and geometric manifolds with AI semantics, highlighting implications for stability.

Semantic reasoning grounded in geometric and topological invariants shows promise for stable multi-step reasoning, with potential to reduce hallucinations in AI.
Key insights into the meaning unification framework emphasize a hierarchy from quantum systems to semantic stability in large language models.
Topological analysis alongside data from quantum phase models reveals new methods for understanding meaning in cognitive contexts and AI applications.
Framework supports development and alignment mechanisms for interpretable intelligence in artificial systems, bridging physics and AI.

Ryoya Kawai (2025) studied this question.

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