--- title: "Who cites Performance of ChatGPT on USMLE: Potential for…" description: "89 papers of the Elamur Research library cite «Performance of ChatGPT on USMLE: Potential for AI-assisted medical education using large language models»…" canonical: "https://research.elamur.ai/free/en/papers/kung-2023-performance-chatgpt-usmle-potential-ai/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/kung-2023-performance-chatgpt-usmle-potential-ai/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Performance of ChatGPT on USMLE: Potential for…](https://md.research.elamur.ai/free/en/papers/kung-2023-performance-chatgpt-usmle-potential-ai/) / cited by # Who cites «Performance of ChatGPT on USMLE: Potential for AI-assisted medical education using large language models» 89 papers of our library cite it (of the 140,884 whose bibliographies we read) · 17 with a page here, the most cited first · [← the paper](https://md.research.elamur.ai/free/en/papers/kung-2023-performance-chatgpt-usmle-potential-ai/) 1. [**ChatGPT for Good? On Opportunities and Challenges of Large Language Models for Education**Enkelejda Kasneci, Kathrin Seßler, Stefan Küchemann, et al.*2023 · 7,429 citations*](https://md.research.elamur.ai/free/en/papers/kasneci-2023-chatgpt-good-opportunities-challenges-large/) 2. [**A Survey on Evaluation of Large Language Models**Yupeng Chang, Xu Wang, Jindong Wang, et al.*2023 · 3,640 citations*](https://md.research.elamur.ai/free/en/papers/chang-2023-survey-evaluation-large-language-models/) 3. [**ChatGPT: Jack of all trades, master of none**Jan Kocon, Igor Cichecki, Oliwier Kaszyca, et al.*2023 · 863 citations*](https://md.research.elamur.ai/free/en/papers/kocon-2023-chatgpt-jack-all-trades-master/) 4. [**Capabilities of GPT-4 on Medical Challenge Problems**Harsha Nori, Nicholas King, Scott Mayer McKinney, et al.*2023 · 700 citations*](https://md.research.elamur.ai/free/en/papers/nori-2023-capabilities-gpt-4-medical-challenge/) 5. [**Mathematical Capabilities of ChatGPT**Simon Frieder, Luca Pinchetti, Alexis Chevalier, et al.*2023 · 443 citations*](https://md.research.elamur.ai/free/en/papers/frieder-2023-mathematical-capabilities-chatgpt/) 6. [**ChatGPT Beyond English: Towards a Comprehensive Evaluation of Large Language Models in Multilingual Learning**Viet Dac Lai, Nghia Ngo, Amir Pouran Ben Veyseh, et al.*2023 · 418 citations*](https://md.research.elamur.ai/free/en/papers/lai-2023-chatgpt-beyond-english-comprehensive-evaluation/) 7. [**BeaverTails: Towards Improved Safety Alignment of LLM via a Human-Preference Dataset**Jiaming Ji, Mickel Liu, Juntao Dai, et al.*2023 · 351 citations*](https://md.research.elamur.ai/free/en/papers/ji-2023-beavertails-towards-improved-safety-alignment/) 8. [**AugGPT: Leveraging ChatGPT for Text Data Augmentation**Haixing Dai; Zhengliang Liu; Wenxiong Liao; Xiaoke Huang; Yihan Cao; Zihao Wu; Lin Zhao; Shaochen Xu; Wei Liu; Ninghao Liu; Sheng Li; Dajiang Zhu; Hongmin Cai; Lichao Sun; Quanzheng Li; Dinggang Shen; Tianming Liu;, Xiang Li*2023 · 302 citations*](https://md.research.elamur.ai/free/en/papers/dai-2023-auggpt-leveraging-chatgpt-text-data/) 9. [**MedAgents: Large Language Models as Collaborators for Zero-shot Medical Reasoning**Xiangru Tang, Anni Zou, Zhuosheng Zhang, et al.*2024 · 244 citations*](https://md.research.elamur.ai/free/en/papers/tang-2024-medagents-large-language-models-as/) 10. [**TrustLLM: Trustworthiness in Large Language Models**Yue Huang, Lichao Sun, Haoran Wang, et al.*2024 · 226 citations*](https://md.research.elamur.ai/free/en/papers/huang-2024-trustllm-trustworthiness-large-language-models/) 11. [**Safe RLHF: Safe Reinforcement Learning from Human Feedback**Josef Dai, Xuehai Pan, Ruiyang Sun, et al.*2023 · 207 citations*](https://md.research.elamur.ai/free/en/papers/dai-2023-safe-rlhf-safe-reinforcement-learning/) 12. [**Leak, Cheat, Repeat: Data Contamination and Evaluation Malpractices in Closed-Source LLMs**Simone Balloccu, Patrícia Schmidtová, Mateusz Lango, et al.*2024 · 170 citations*](https://md.research.elamur.ai/free/en/papers/balloccu-2024-leak-cheat-repeat-data-contamination/) 13. [**Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-Specificity**Cunxiang Wang, Xiaoze Liu, Yuanhao Yue, et al.*2023 · 169 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-survey-factuality-large-language-models/) 14. [**PMC-LLaMA: Towards Building Open-source Language Models for Medicine**Chaoyi Wu, Weixiong Lin, Xiaoman Zhang, et al.*2023 · 142 citations*](https://md.research.elamur.ai/free/en/papers/wu-2023-pmc-llama-towards-building-open/) 15. [**GPT detectors are biased against non-native English writers**Weixin Liang, Mert Yuksekgonul, Yining Mao, et al.*2023 · 106 citations*](https://md.research.elamur.ai/free/en/papers/liang-2023-gpt-detectors-biased-against-non/) 16. [**Can ChatGPT capture swearing nuances? Evidence from translating Arabic oaths**Mohammed Q. Shormani*2024 · 3 citations*](https://md.research.elamur.ai/free/en/papers/shormani-2024-chatgpt-capture-swearing-nuances-evidence/) 17. [**Enhancing Medical Support in the Arabic Language Through Personalized ChatGPT Assistance**Mohamed Issa, Ahmed Abdelwahed*2024*](https://md.research.elamur.ai/free/en/papers/issa-2024-enhancing-medical-support-arabic-language/) 72 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/kung-2023-performance-chatgpt-usmle-potential-ai/) — Performance of ChatGPT on USMLE: Potential for AI-assisted medical education using large language models