Empirical Proof of Systemic Incoherence in Large Language Models (ARAYUN_173)
Abstract: This study presents reproducible evidence of systemic incoherence in large language models (tested on Google Gemini). Across ten isolated Universal Semantic Self-Test (USST) sessions, the models exhibited a deterministic collapse of coherence (CR → 0), demonstrating that probabilistic AI architectures cannot sustain self-consistency without an external coherence law. Core...