HACK: Hallucinations Along Certainty and Knowledge Axes

A new study published on arXiv addresses the issue of hallucinations in large language models (LLMs), which hinder their reliable use. The research suggests that instead of focusing solely on the external characteristics of these hallucinations, it's crucial to understand their internal mechanisms. By proposing a framework that categorizes hallucinations along the axes of knowledge and certainty, the study aims to develop more effective strategies for mitigating these issues. This approach could lead to improved reliability in LLM applications, making them more trustworthy for users.