--- title: "Who cites Hui Wang" description: "159 papers of the Elamur Research library cite the works of Hui Wang, found in their bibliographies; the most cited first." canonical: "https://research.elamur.ai/free/en/authors/hui-wang/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/hui-wang/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Hui Wang](https://md.research.elamur.ai/free/en/authors/hui-wang/) / cited by # Who cites Hui Wang 159 citations of their works from 159 papers of our library (of the 140,884 whose bibliographies we read) · 21 with a page here, the most cited first · [← Hui Wang](https://md.research.elamur.ai/free/en/authors/hui-wang/) 1. [**A Survey of Large Language Models**Wayne Xin Zhao, Kun Zhou, Junyi Li, et al.*2023 · 2,847 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2023-survey-large-language-models/) 2. [**PaLM: Scaling Language Modeling with Pathways**Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, et al.*2022 · 2,603 citations*](https://md.research.elamur.ai/free/en/papers/chowdhery-2022-palm-scaling-language-modeling-pathways/) 3. [**A Comprehensive Overview of Large Language Models**Humza Naveed, Asad Ullah Khan, Shi Qiu, et al.*2023 · 1,286 citations*](https://md.research.elamur.ai/free/en/papers/naveed-2023-comprehensive-overview-large-language-models/) 4. [**GPT-NeoX-20B: An Open-Source Autoregressive Language Model**Sidney Black, Stella Biderman, Eric Hallahan, et al.*2022 · 818 citations*](https://md.research.elamur.ai/free/en/papers/black-2022-gpt-neox-20b-open-source/) 5. [**GLM-130B: An Open Bilingual Pre-trained Model**Aohan Zeng, Xiao Liu, Zhengxiao Du, et al.*2022 · 775 citations*](https://md.research.elamur.ai/free/en/papers/zeng-2022-glm-130b-open-bilingual-pre/) 6. [**Using DeepSpeed and Megatron to Train Megatron-Turing NLG 530B, A Large-Scale Generative Language Model**Shaden Smith, Mostofa Patwary, Brandon Norick, et al.*2022 · 595 citations*](https://md.research.elamur.ai/free/en/papers/smith-2022-using-deepspeed-megatron-train-megatron/) 7. [**The Falcon Series of Open Language Models**Ebtesam Almazrouei, Hamza Alobeidli, Abdulaziz Alshamsi, et al.*2023 · 436 citations*](https://md.research.elamur.ai/free/en/papers/almazrouei-2023-falcon-series-open-language-models/) 8. [**ERNIE 3.0: Large-scale Knowledge Enhanced Pre-training for Language Understanding and Generation**Yu Sun, Shuohuan Wang, Shikun Feng, et al.*2021 · 324 citations*](https://md.research.elamur.ai/free/en/papers/sun-2021-ernie-3-0-large/) 9. [**Aya Model: An Instruction Finetuned Open-Access Multilingual Language Model**Ahmet Üstün, Viraat Aryabumi, Zheng-Xin Yong, et al.*2024 · 245 citations*](https://md.research.elamur.ai/free/en/papers/ustun-2024-aya-model-instruction-finetuned-open/) 10. [**Qwen2.5-Omni Technical Report**Jin Xu, Zhifang Guo, Jinzheng He, et al.*2025 · 218 citations*](https://md.research.elamur.ai/free/en/papers/xu-2025-qwen2-5-omni-technical/) 11. [**Teaching language models to support answers with verified quotes**Jacob Menick, Maja Trebacz, Vladimir Mikulik, et al.*2022 · 211 citations*](https://md.research.elamur.ai/free/en/papers/menick-2022-teaching-language-models-support-answers/) 12. [**Fanar: An Arabic-Centric Multimodal Generative AI Platform**Fanar Team: Ummar Abbas, Mohammad Shahmeer Ahmad, Firoj Alam, et al.*2025 · 127 citations*](https://md.research.elamur.ai/free/en/papers/abbas-2025-fanar-arabic-centric-multimodal-generative/) 13. [**Large Language Model Alignment: A Survey**Tianhao Shen, Renren Jin, Yufei Huang, et al.*2023 · 123 citations*](https://md.research.elamur.ai/free/en/papers/shen-2023-large-language-model-alignment-survey/) 14. [**Qwen3-Omni Technical Report**Jin Xu, Zhifang Guo, Hangrui Hu, et al.*2025 · 114 citations*](https://md.research.elamur.ai/free/en/papers/xu-2025-qwen3-omni-technical-report/) 15. [**JABER and SABER: Junior and Senior Arabic BERt**Abbas Ghaddar, Yimeng Wu, Ahmad Rashid, et al.*2021 · 16 citations*](https://md.research.elamur.ai/free/en/papers/ghaddar-2021-jaber-saber-junior-senior-arabic/) 16. [**Revisiting Pre-trained Language Models and their Evaluation for Arabic Natural Language Understanding**Abbas Ghaddar, Yimeng Wu, Sunyam Bagga, et al.*2022 · 9 citations*](https://md.research.elamur.ai/free/en/papers/ghaddar-2022-revisiting-pre-trained-language-models-their/) 17. [**Deep Learning Based Code Generation Methods: Literature Review (基于深度学习的代码生成方法研究进展)**Zezhou Yang (杨泽洲), Sirong Chen (陈思榕), Cuiyun Gao (高翠芸), et al.*2023 · 1 citation*](https://md.research.elamur.ai/free/en/papers/yang-2023-deep-learning-code/) 18. [**Probing Discrete Speech Tokens of Spoken Language Models**Sven Naber, Julia Koch, Pranav Singh, et al.*2026*](https://md.research.elamur.ai/free/en/papers/naber-2026-probing-discrete-speech-tokens-spoken/) 19. [**Survey on Key Technologies for Large Language Model Pre-training Systems (大语言模型预训练系统关键技术综述)**Yanjie Gao (高彦杰), Yueguo Chen (陈跃国)*2025*](https://md.research.elamur.ai/free/en/papers/gao-2025-key-technologies-large/) 20. [**From Foundation Intelligence to General Intelligence: Status and Prospects of Large-Model-Based GenAI and AGI (从基础智能到通用智能: 基于大模型的GenAI和AGI之现状与展望)**Qinghai Miao (缪青海), Xingxia Wang (王兴霞), Jing Yang (杨静), et al.*2024*](https://md.research.elamur.ai/free/en/papers/miao-2024-foundation-intelligence-general/) 21. [**Questions After ChatGPT: Opportunities and Challenges of Very Large Pre-trained Models (问答ChatGPT之后: 超大预训练模型的机遇和挑战)**Jingwei Lu (卢经纬), Chao Guo (郭超), Xingyuan Dai (戴星原), et al.*2023*](https://md.research.elamur.ai/free/en/papers/lu-2023-questions-after-chatgpt/) 138 more citing papers of our library have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/authors/hui-wang/) — Hui Wang