Robust Safety Classifier for Large Language Models: Adversarial Prompt Shield

cjadams, J. Sorensen, J. Elliott, L. Dixon, M. McDonald, nithum, and W. Cukierski, “Toxic comment classification challenge,” 2017. [Online]. Available: https://kaggle.com/competitions/jigsaw-toxic-comment-classification-challenge

2017

Earlier work this paper cites.

A. Madry, A. Makelov, L. Schmidt, D. Tsipras, and A. Vladu, “Towards deep learning models resistant to adversarial attacks,” in International Conference on Learning Representations , 2018. [Online]. Available: https://openreview.net/forum?id=rJzIBfZAb

2018

Earlier work this paper cites.

E. Dinan, S. Humeau, B. Chintagunta, and J. Weston, “Build it break it fix it for dialogue safety: Robustness from adversarial human attack,” in Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP) . Hong Kong, China: Association for Computational Linguistics, Nov. 2019, pp. 4537–4546. [Online]. Available: https://aclanthology.org/D19-1461

2019

Earlier work this paper cites.

J. Devlin, M.-W. Chang, K. Lee, and K. Toutanova, “BERT: Pre-training of deep bidirectional transformers for language understanding,” in Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers) . Minneapolis, Minnesota: Association for Computational Linguistics, Jun. 2019, pp. 4171–4186. [Online]. Available: https://aclanthology.org/N19-1423

2019

Earlier work this paper cites.

D. Adiwardana, M.-T. Luong, D. R. So, J. Hall, N. Fiedel, R. Thoppilan, Z. Yang, A. Kulshreshtha, G. Nemade, Y. Lu et al. , “Towards a human-like open-domain chatbot,” arXiv preprint arXiv:2001.09977 , 2020

Original

2020

Earlier work this paper cites.

V. Sanh, L. Debut, J. Chaumond, and T. Wolf, “Distilbert, a distilled version of bert: smaller, faster, cheaper and lighter,” 2020

2020

Earlier work this paper cites.

J. Xu, D. Ju, M. Li, Y.-L. Boureau, J. Weston, and E. Dinan, “Bot-adversarial dialogue for safe conversational agents,” in Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies . Online: Association for Computational Linguistics, Jun. 2021, pp. 2950–2968. [Online]. Available: https://aclanthology.org/2021.naacl-main.235

2021

Earlier work this paper cites.

Y. Bai, S. Kadavath, S. Kundu, A. Askell, J. Kernion, A. Jones, A. Chen, A. Goldie, A. Mirhoseini, C. McKinnon, C. Chen, C. Olsson, C. Olah, D. Hernandez, D. Drain, D. Ganguli, D. Li, E. Tran-Johnson, E. Perez, J. Kerr, J. Mueller, J. Ladish, J. Landau, K. Ndousse, K. Lukosuite, L. Lovitt, M. Sellitto, N. Elhage, N. Schiefer, N. Mercado, N. DasSarma, R. Lasenby, R. Larson, S. Ringer, S. Johnston, S. Kravec, S. E. Showk, S. Fort, T. Lanham, T. Telleen-Lawton, T. Conerly, T. Henighan, T. Hume, S. R. Bowman, Z. Hatfield-Dodds, B. Mann, D. Amodei, N. Joseph, S. McCandlish, T. Brown, and J. Kaplan, “Constitutional ai: Harmlessness from ai feedback,” 2022

2022

Cited alongside, same era.

Y. Bai, A. Jones, K. Ndousse, A. Askell, A. Chen, N. DasSarma, D. Drain, S. Fort, D. Ganguli, T. Henighan, N. Joseph, S. Kadavath, J. Kernion, T. Conerly, S. El-Showk, N. Elhage, Z. Hatfield-Dodds, D. Hernandez, T. Hume, S. Johnston, S. Kravec, L. Lovitt, N. Nanda, C. Olsson, D. Amodei, T. Brown, J. Clark, S. McCandlish, C. Olah, B. Mann, and J. Kaplan, “Training a helpful and harmless assistant with reinforcement learning from human feedback,” 2022

2022

Cited alongside, same era.

N. Jain, A. Schwarzschild, Y. Wen, G. Somepalli, J. Kirchenbauer, P.-y. Chiang, M. Goldblum, A. Saha, J. Geiping, and T. Goldstein, “Baseline defenses for adversarial attacks against aligned language models,” arXiv preprint arXiv:2309.00614 , 2023

Original

2023

Closest in time.

Y. Liu, G. Deng, Z. Xu, Y. Li, Y. Zheng, Y. Zhang, L. Zhao, T. Zhang, and Y. Liu, “Jailbreaking chatgpt via prompt engineering: An empirical study,” 2023

2023

Closest in time.

M. King, “Meet dan — the ‘jailbreak’ version of chatgpt and how to use it — ai unchained and unfiltered,” accessed: 2023-09-29. [Online]. Available: https://medium.com/@neonforge/meet-dan-the-jailbreak-version-of-chatgpt-and-how-to-use-it-ai-unchained-and-unfiltered-f91bfa679024

2023

Closest in time.

W.-L. Chiang, Z. Li, Z. Lin, Y. Sheng, Z. Wu, H. Zhang, L. Zheng, S. Zhuang, Y. Zhuang, J. E. Gonzalez, I. Stoica, and E. P. Xing, “Vicuna: An open-source chatbot impressing gpt-4 with 90%* chatgpt quality,” March 2023. [Online]. Available: https://lmsys.org/blog/2023-03-30-vicuna/