Why Do Large Language Models Hallucinate? Definitions, Causes, and Mitigation Strategies
This article defines hallucination in LLMs as a failure of faithfulness or factualness, explores data‑level and model‑level origins, reviews reference‑based and reference‑free evaluation metrics, and surveys current research on data‑centric and model‑centric mitigation techniques along with future directions.
