1. Wang, J. , Hu, X. , Hou, W. , Chen, H. , Zheng, R. , Wang, Y. , Yang, L. , Huang, H. , Ye, W. , Geng, X. , Jiao, B. , Zhang, Y. and Xie, X. (2023). On the robustness of chatgpt: an adversarial and out-of-distribution perspective. ArXiv, abs/2302.12095.
2. Emerging trends: unfair, biased, addictive, dangerous, deadly, and insanely profitable;Church;Natural Language Engineering,2023
3. Morris, J. , Lifland, E. , Yoo, J.Y. , Grigsby, J. , Jin, D. and Qi, Y. (2020). TextAttack: a framework for adversarial attacks, data augmentation, and adversarial training in NLP. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: System Demonstrations. Association for Computational Linguistics, pp. 119–126. Online.
4. Chain-of-thought prompting elicits reasoning in large language models;Wei;Advances in Neural Information Processing Systems,2022