Large language models are human-level prompt engineers. arXiv preprint arXiv:2211.01910 (2022).

[249] Kaijie Zhu, Jindong Wang, Jiaheng Zhou, Zichen Wang, Hao Chen, Yidong Wang, Linyi Yang, Wei Ye, Neil Zhenqiang
Gong, Yue Zhang, et al. 2023. PromptBench: Towards Evaluating the Robustness of Large Language Models on
Adversarial Prompts. arXiv preprint arXiv:2306.04528 (2023).

[250] Yan Zhuang, Qi Liu, Yuting Ning, Weizhe Huang, Rui Lv, Zhenya Huang, Guanhao Zhao, Zheng Zhang, Qingyang
Mao, Shijin Wang, et al. 2023. Efficiently Measuring the Cognitive Ability of LLMs: An Adaptive Testing Perspective.
arXiv preprint arXiv:2306.10512 (2023).

[251] Terry Yue Zhuo, Yujin Huang, Chunyang Chen, and Zhenchang Xing. 2023. Exploring ai ethics of chatgpt: A diagnostic

analysis. arXiv preprint arXiv:2301.12867 (2023).
ASurveyonEvaluationofLargeLanguageModels