认知幻象：大型语言模型中的幻觉综述
Cognitive Mirage: A Review of Hallucinations in Large Language Models
AI总结：
本文综述了大型语言模型中的幻觉现象，提出了新的幻觉分类法，总结了理论分析、检测与改进方法，并指出了未来研究方向。
摘要：
随着大型语言模型在AI领域持续发展，文本生成系统容易受到一种被称为幻觉的令人担忧的现象的影响。在本研究中，我们总结了关于LLMs幻觉的最新引人注目的见解。我们提出了来自各种文本生成任务的幻觉新分类法，从而提供理论见解、检测方法和改进方法。基于此，提出了未来的研究方向。我们的贡献有三个方面：(1) 我们为文本生成任务中出现的幻觉提供了详细且完整的分类法；(2) 我们对LLMs中的幻觉提供理论分析，并提供现有的检测和改进方法；(3) 我们提出了未来可以发展的几个研究方向。随着幻觉引起社区的极大关注，我们将持续更新相关研究进展。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
