梳理大模型幻觉类型与成因，给出实用缓解方法。
A Concise Review of Hallucinations in LLMs and their Mitigation
- 归纳当前主流幻觉类型及其产生机制
- 总结现有缓解策略的有效性与适用场景
- 适合想快速掌握幻觉问题的研究者与工程师
传统语言模型面临幻觉问题的挑战，其存在对自然语言处理领域构成了广泛而危险的影响。深入理解当前各类幻觉的表现形式、根本原因以及缓解手段变得至关重要。本文提供了一个简洁明了的综述，系统梳理了幻觉的分类、生成机理与现有抑制方法，旨在成为该领域的一站式入门资源，帮助读者全面掌握幻觉现象的本质及应对策略。
原文摘要 · Abstract (English)
Traditional language models face a challenge from hallucinations. Their very presence casts a large, dangerous shadow over the promising realm of natural language processing. It becomes crucial to understand the various kinds of hallucinations that occur nowadays, their origins, and ways of reducing them. This document provides a concise and straightforward summary of that. It serves as a one-stop resource for a general understanding of hallucinations and how to mitigate them.
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