Cognitive Mirage: A Review of Hallucinations in Large Language Models
Hongbin Ye Tong Liu Aijia Zhang Wei Hua Weiqiang Jia
As large language models continue to develop in the field of AI, text
generation systems are susceptible to a worrisome phenomenon known as
hallucination. In this study, we summarize recent compelling insights into
hallucinations in LLMs. We present a novel taxonomy of hallucinations from
various text generation tasks, thus provide theoretical insights, detection
methods and improvement approaches. Based on this, future research directions
are proposed. Our contribution are threefold: (1) We provide a detailed and
complete taxonomy for hallucinations appearing in text generation tasks; (2) We
provide theoretical analyses of hallucinations in LLMs and provide existing
detection and improvement methods; (3) We propose several research directions
that can be developed in the future. As hallucinations garner significant
attention from the community, we will maintain updates on relevant research
progress.