Abstract AI has achieved remarkable progress, yet AI hallucination remains a critical challenge, particularly in large language models (LLMs). Hallucination occurs when AI systems generate outputs that are plausible but factually incorrect or nonsensical. This paper focuses on strategies to mitigate AI hallucinations through mathematical and statistical approaches. We analyze the underlying causes of hallucination,…