RGCC-X Plus: A Structural Framework for Understanding Hallucinations in Large Language Models

This paper introduces the RGCC-X Plus framework for analyzing hallucinations in large language models (LLMs). The model identifies structural modes of hallucination including Combined, Mirror, Tandem, and Self hallucinations, and proposes a control layer (RGCC Control) for mitigation. The framework focuses on structural reasoning patterns rather than purely probabilistic explanations and offers a conceptual tool for understanding hallucination formation in AI systems. This work is released as a preprint and aims to stimulate discussion and further research in AI reliability and cognitive modeling.