| Gemini: a family of highly capable multimodal models G Team, R Anil, S Borgeaud, Y Wu, JB Alayrac, J Yu, R Soricut, ... arXiv preprint arXiv:2312.11805, 2023 | 1490 | 2023 |
| Palm 2 technical report R Anil, AM Dai, O Firat, M Johnson, D Lepikhin, A Passos, S Shakeri, ... arXiv preprint arXiv:2305.10403, 2023 | 1321 | 2023 |
| Machine unlearning L Bourtoule, V Chandrasekaran, CA Choquette-Choo, H Jia, A Travers, ... 42nd IEEE Symposium on Security and Privacy, 2021 | 706 | 2021 |
| Label-Only Membership Inference Attacks CA Choquette-Choo, F Tramer, N Carlini, N Papernot 38th International Conference on Machine Learning, 2021 | 481 | 2021 |
| Gemma: Open models based on gemini research and technology G Team, T Mesnard, C Hardin, R Dadashi, S Bhupatiraju, S Pathak, ... arXiv preprint arXiv:2403.08295, 2024 | 425 | 2024 |
| Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context M Reid, N Savinov, D Teplyashin, D Lepikhin, T Lillicrap, J Alayrac, ... arXiv preprint arXiv:2403.05530, 2024 | 358 | 2024 |
| Entangled watermarks as a defense against model extraction H Jia, CA Choquette-Choo, V Chandrasekaran, N Papernot 30th USENIX security symposium (USENIX Security 21), 1937-1954, 2021 | 261 | 2021 |
| Scalable extraction of training data from (production) language models M Nasr, N Carlini, J Hayase, M Jagielski, AF Cooper, D Ippolito, ... arXiv preprint arXiv:2311.17035, 2023 | 178 | 2023 |
| Are aligned neural networks adversarially aligned? N Carlini, M Nasr, CA Choquette-Choo, M Jagielski, I Gao, PWW Koh, ... Advances in Neural Information Processing Systems 36, 2024 | 175 | 2024 |
| Poisoning web-scale training datasets is practical N Carlini, M Jagielski, CA Choquette-Choo, D Paleka, W Pearce, ... 2024 IEEE Symposium on Security and Privacy (SP), 407-425, 2024 | 135 | 2024 |
| Preventing Generation of Verbatim Memorization in Language Models Gives a False Sense of Privacy D Ippolito, F Tramèr, M Nasr, C Zhang, M Jagielski, K Lee, CC Choo, ... Proceedings of the 16th International Natural Language Generation Conference …, 2023 | 110* | 2023 |
| Proof-of-Learning: Definitions and Practice H Jia, M Yaghini, CA Choquette-Choo, N Dullerud, A Thudi, ... 42nd IEEE Symposium on Security and Privacy, 2021 | 94 | 2021 |
| Federated learning of gboard language models with differential privacy Z Xu, Y Zhang, G Andrew, CA Choquette-Choo, P Kairouz, HB McMahan, ... arXiv preprint arXiv:2305.18465, 2023 | 64 | 2023 |
| CaPC Learning: Confidential and Private Collaborative Learning CA Choquette-Choo, N Dullerud, A Dziedzic, Y Zhang, S Jha, N Papernot, ... 9th International Conference on Learning Representations, 2021 | 64 | 2021 |
| Madlad-400: A multilingual and document-level large audited dataset S Kudugunta, I Caswell, B Zhang, X Garcia, CA Choquette-Choo, K Lee, ... Advances in Neural Information Processing Systems 36, 2024 | 58 | 2024 |
| The fundamental price of secure aggregation in differentially private federated learning WN Chen, CAC Choo, P Kairouz, AT Suresh International Conference on Machine Learning, 3056-3089, 2022 | 57 | 2022 |
| Gemma 2: Improving open language models at a practical size G Team, M Riviere, S Pathak, PG Sessa, C Hardin, S Bhupatiraju, ... arXiv preprint arXiv:2408.00118, 2024 | 40 | 2024 |
| Multi-epoch matrix factorization mechanisms for private machine learning CA Choquette-Choo, HB McMahan, K Rush, A Thakurta 40th International Conference on Machine Learning 202, 5924-5963, 2023 | 32* | 2023 |
| Privacy side channels in machine learning systems E Debenedetti, G Severi, N Carlini, CA Choquette-Choo, M Jagielski, ... 33rd USENIX Security Symposium (USENIX Security 24), 6861-6848, 2024 | 22 | 2024 |
| A Multi-label, Dual-Output Deep Neural Network for Automated Bug Triaging CA Choquette-Choo, D Sheldon, J Proppe, J Alphonso-Gibbs, H Gupta 2019 18th IEEE International Conference On Machine Learning And Applications …, 2019 | 22 | 2019 |
Nicolas PapernotUniversity of Toronto and Vector InstituteVerified email at utoronto.ca
