In this short article, we share hallucination benchmarks you can use to detect and evaluate hallucinations in your large language models.
What are hallucinations?
In large language models (LLMs), "hallucinations" are cases when a model produces text with details, facts, or claims that are fictional, misleading, or completely made up, instead of giving reliable and truthful information.
Read our article to learn more about hallucinations, including their causes, how to identify them, and why they can be beneficial:
Now, to the list of benchmarks →
