Large Language Models (LLMs) have revolutionized natural language processing, demonstrating remarkable capabilities in generating human-like text, answering complex questions, and even creating content. However, a persistent and significant challenge in their deployment is the phenomenon of "hallucination," where models produce outputs that are factually incorrect, nonsensical, or fabricated, often stemming from a lack of deep internal knowledge or an overreliance on pattern matching....
