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Cognitive Mirage: A Review of Hallucinations in Large Language Models

Research on hallucinations in large language models provides a taxonomy, theoretical analysis, detection methods, and improvement approaches, as well as future research directions.

Year
2023
Venue
arXiv 2023
Authors
5
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arxiv.org/abs/2309.06794ARXIV-DEFAULT
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Abstract

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.

Authors

5