HILL: A Hallucination Identifier for Large Language Models

Understand

Large language models (LLMs) are prone to hallucinations, i.e., nonsensical, unfaithful, and undesirable text.

• Users tend to overrely on LLMs and corresponding hallucinations which can lead to misinterpretations and errors.
• To tackle the problem of overreliance, we propose HILL, the "Hallucination Identifier for Large Language Models".
• First, we identified design features for HILL with a Wizard of Oz approach with nine participants.