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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
| Date | Stars |
|---|---|
| 2026-07-31 | 339 |
| 2026-08-05 | 339 |
| 2026-08-06 | 339 |
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<div align="center">
<h2>
A Survey on Hallucination in Large Language Models:
Principles, Taxonomy, Challenges, and Open Questions
</h2>
</div>
<div align="center">
<b>Lei Huang</b><sup>1∗</sup>,
<b>Weijiang Yu</b><sup>2∗</sup>,
<b>Weitao Ma</b><sup>1</sup>,
<b>Weihong Zhong</b><sup>1</sup>,
<b>Zhangyin Feng</b><sup>1</sup>,
<b>Haotian Wang</b><sup>1</sup>,
<b>Qianglong Chen</b><sup>2</sup>,
<b>Weihua Peng</b><sup>2</sup>,
<b>Xiaocheng Feng</b><sup>1†</sup>,
<b>Bing Qin</b><sup>1</sup>,
<b>Ting Liu</b><sup>1</sup>
</div>
<div align="center">
<sup>1</sup>Harbin Institute of Technology, Harbin, China
</div>
<div align="center">
<sup>2</sup>Huawei Inc., Shenzhen, China
</div>
This repository contains the resources for our survey paper.
[](https://awesome.re)[](./LICENSE)
<p align=center>
<img src="./figure/categorization.png" width="75%" height="75%" alt="taxonomy"/>
<br>
<em>The main content flow and categorization of this survey.</em>
</p>
## :tada: Updates
- 2023/11/09 The first version of our paper is available on [arXiv](https://arxiv.org/abs/2311.05232)
## :page_with_curl: Papers
We have surveyed papers related to Large Language Model hallucination. This includes **related survey or analytical papers**, **hallucination causes**, **hallucination detection and benchmarks**, **hallucination mitigation**, as well as **challenges and open questions** in the field.
### :memo:Related Survey / Analytical Papers
> We provide a curated list of survey papers that delve into the topic of hallucination in LLMs.
#### Related Survey papers
1. **Survey of Hallucination in Natural Language Generation** `ACM Computing Surveys 2023 `
*Ziwei Ji, Nayeon Lee, Rita Frieske, Tiezheng Yu, Dan Su, Yan Xu, Etsuko Ishii, Yejin Bang, Wenliang Dai, Andrea Madotto, Pascale Fung* [[paper]](https://arxiv.org/abs/2202.03629) 2022.02
2. **Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' Alignment** `arXiv 2023`
*Yang Liu, Yuanshun Yao, Jean-Francois Ton, Xiaoying Zhang, Ruocheng Guo, Hao Cheng, Yegor Klochkov, Muhammad Faaiz Taufiq, Hang Li* [[paper]](https://arxiv.org/abs/2308.05374) 2023.08
3. **Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Models** `arXiv 2023`
*Yue Zhang, Yafu Li, Leyang Cui, Deng Cai, Lemao Liu, Tingchen Fu, Xinting Huang, Enbo Zhao, Yu Zhang, Yulong Chen, Longyue Wang, Anh Tuan Luu, Wei Bi, Freda Shi, Shuming Shi* [[paper]](https://arxiv.org/abs/2309.01219) 2023.09
4. **Cognitive Mirage: A Review of Hallucinations in Large Language Models** `arXiv 2023`
*Hongbin Ye, Tong Liu, Aijia Zhang, Wei Hua, Weiqiang Jia* [[paper]](https://arxiv.org/abs/2309.06794) 2023.09
5. **A Survey of Hallucination in Large Foundation Models** `arXiv 2023`
*Vipula Rawte, Amit Sheth, Amitava Das* [[paper]](https://arxiv.org/abs/2309.05922) 2023.09
6. **Augmenting LLMs with Knowledge: A survey on hallucination prevention** `arXiv 2023`
*Konstantinos Andriopoulos, Johan Pouwelse* [[paper]](https://arxiv.org/abs/2309.16459) 2023.09
7. **Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-Specificity** `arXiv 2023`
*Cunxiang Wang, Xiaoze Liu, Yuanhao Yue, Xiangru Tang, Tianhang Zhang, Cheng Jiayang, Yunzhi Yao, Wenyang Gao, Xuming Hu, Zehan Qi, Yidong Wang, Linyi Yang, Jindong Wang, Xing Xie, Zheng Zhang, Yue Zhang* [[paper]](https://arxiv.org/abs/2310.07521) 2023.10
8. **Insights into Classifying and Mitigating LLMs' Hallucinations** `AIxIA 2023`
*Alessandro Bruno, Pier Luigi Mazzeo, Aladine Chetouani, Marouane Tliba, Mohamed Amine Kerkouri* [[paper]](https://arxiv.org/abs/2311.08117) 2023.11
#### Related Analytical papers
1. **A Multitask, Multilingual, Multimodal EvaluatiExcerpt of 49,942 characters
Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:17f03273d2d929a6, desc:paper list