| Universal adversarial triggers for attacking and analyzing NLP E Wallace, S Feng, N Kandpal, M Gardner, S Singh arXiv preprint arXiv:1908.07125, 2019 | 956 | 2019 |
| Large language models struggle to learn long-tail knowledge N Kandpal, H Deng, A Roberts, E Wallace, C Raffel International Conference on Machine Learning, 15696-15707, 2023 | 468 | 2023 |
| Deduplicating training data mitigates privacy risks in language models N Kandpal, E Wallace, C Raffel International Conference on Machine Learning, 10697-10707, 2022 | 275 | 2022 |
| Backdoor attacks for in-context learning with language models N Kandpal, M Jagielski, F Tramèr, N Carlini arXiv preprint arXiv:2307.14692, 2023 | 80 | 2023 |
| User inference attacks on large language models N Kandpal, K Pillutla, A Oprea, P Kairouz, CA Choquette-Choo, Z Xu arXiv preprint arXiv:2310.09266, 2023 | 26 | 2023 |
| Music enhancement via image translation and vocoding N Kandpal, O Nieto, Z Jin ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022 | 18 | 2022 |
| Git-theta: A git extension for collaborative development of machine learning models N Kandpal, B Lester, M Muqeeth, A Mascarenhas, M Evans, V Baskaran, ... International Conference on Machine Learning, 15708-15719, 2023 | 12 | 2023 |
| User inference attacks on LLMs N Kandpal, K Pillutla, A Oprea, P Kairouz, C Choquette-Choo, Z Xu Socially responsible language modelling research, 2023 | 6 | 2023 |
| AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution F Liu, N Kandpal, C Raffel arXiv preprint arXiv:2411.15102, 2024 | | 2024 |
