The author proposes HILL, a tool to identify and highlight hallucinations in Large Language Models (LLMs), enabling users to handle responses with caution. By incorporating user-centered design features, HILL aims to reduce overreliance on LLM responses.
Large language models (LLMs) are prone to hallucinations, leading to errors and misinterpretations. HILL aims to identify and highlight these hallucinations, enabling users to handle LLM responses with caution.