Hallucination Evaluation

Hallucination Evaluation is a crucial task in the field of natural language processing, aimed at assessing the ability of large language models to generate non-hallucinatory text or to identify hallucinations. This task involves detecting information in the model's output that contradicts the facts presented in the input, ensuring the accuracy and reliability of the generated content, which is significant for enhancing the credibility of models in real-world applications.