Hallucination in a foundation model (FM) refers to the generation of content that strays from factual reality or includes fabricated information. This survey paper provides an extensive overview of recent efforts that aim to identify, elucidate, and tackle the problem of hallucination, with a particular focus on ``Large'' Foundation Models (LFMs). The paper classifies various types of hallucination phenomena that are specific to LFMs and establishes evaluation criteria for assessing the extent of hallucination. It also examines existing strategies for mitigating hallucination in LFMs and discusses potential directions for future research in this area. Essentially, the paper offers a comprehensive examination of the challenges and solutions related to hallucination in LFMs.

翻译：基础模型中的幻觉（hallucination）指生成内容偏离事实或包含虚构信息的现象。本综述论文对近期旨在识别、阐释并应对幻觉问题的研究工作进行了全面梳理，重点关注"大型"基础模型（LFM）。论文分类阐述了LFM特有的各类幻觉现象，建立了评估幻觉程度的评价标准，系统考察了现有缓解LFM幻觉的策略，并探讨了该领域未来的研究方向。本质上，本文对LFM中幻觉相关问题面临的挑战与解决方案进行了全面审视。