| Evaluating Gradient Inversion Attacks and Defenses in Federated Learning Y Huang, S Gupta, Z Song, K Li, S Arora NeurIPS 2021, 2021 | 222 | 2021 |
| Deep Q learning driven CT pancreas segmentation with geometry-aware U-Net Y Man*, Y Huang*, J Feng, X Li, F Wu IEEE Transactions on Medical Imaging, 2019 | 148 | 2019 |
| Instahide: Instance-hiding schemes for private distributed learning Y Huang, Z Song, K Li, S Arora ICML 2020, 2020 | 147 | 2020 |
| Catastrophic Jailbreak of Open-Source LLMs via Exploiting Generation Y Huang, S Gupta, M Xia, K Li, D Chen ICLR 2024, 2024 | 107 | 2024 |
| Detecting pretraining data from large language models W Shi, A Ajith, M Xia, Y Huang, D Liu, T Blevins, D Chen, L Zettlemoyer ICLR 2024, 2024 | 94 | 2024 |
| Recovering Private Text in Federated Learning of Language Models S Gupta*, Y Huang*, Z Zhong, T Gao, K Li, D Chen NeurIPS 2022, 2022 | 56 | 2022 |
| TextHide: Tackling Data Privacy in Language Understanding Tasks Y Huang, Z Song, D Chen, K Li, S Arora EMNLP (Findings) 2020, 2020 | 52 | 2020 |
| Advancing differential privacy: Where we are now and future directions for real-world deployment R Cummings, D Desfontaines, D Evans, R Geambasu, Y Huang, ... arXiv preprint arXiv:2304.06929, 2023 | 31* | 2023 |
| DeepMC: a deep learning method for efficient Monte Carlo beamlet dose calculation by predictive denoising in magnetic resonance-guided radiotherapy R Neph, Q Lyu, Y Huang, YM Yang, K Sheng Physics in Medicine & Biology 66 (3), 035022, 2021 | 29 | 2021 |
| Assessing the Brittleness of Safety Alignment via Pruning and Low-Rank Modifications B Wei*, K Huang*, Y Huang*, T Xie, X Qi, M Xia, P Mittal, M Wang, ... ICML 2024, 2024 | 24 | 2024 |
| A Dataset Auditing Method for Collaboratively Trained Machine Learning Models Y Huang, CY Huang, X Li, K Li IEEE Transactions on Medical Imaging, 2022 | 20* | 2022 |
| Privacy-Preserving Learning via Deep Net Pruning Y Huang, Y Su, S Ravi, Z Song, S Arora, K Li arXiv preprint arXiv:2003.01876, 2020 | 20* | 2020 |
| Privacy Implications of Retrieval-Based Language Models Y Huang, S Gupta, Z Zhong, K Li, D Chen EMNLP 2023, 2023 | 19 | 2023 |
| Deepmcdose: A deep learning method for efficient monte carlo beamlet dose calculation by predictive denoising in mr-guided radiotherapy R Neph, Y Huang, Y Yang, K Sheng Artificial Intelligence in Radiation Therapy: First International Workshop …, 2019 | 13 | 2019 |
| NN-Adapter: Efficient Domain Adaptation for Black-Box Language Models Y Huang, D Liu, Z Zhong, W Shi, YT Lee arXiv preprint arXiv:2302.10879, 2023 | 11 | 2023 |
| A Safe Harbor for AI Evaluation and Red Teaming S Longpre, S Kapoor, K Klyman, A Ramaswami, R Bommasani, ... ICML 2024, 2024 | 8 | 2024 |
| IFGAN: Missing Value Imputation using Feature-specific Generative Adversarial Networks W Qiu, Y Huang, Q Li 2020 IEEE International Conference on Big Data (Big Data), 2020 | 6 | 2020 |
| Sparsity-Preserving Differentially Private Training of Large Embedding Models B Ghazi, Y Huang, P Kamath, R Kumar, P Manurangsi, A Sinha, C Zhang NeurIPS 2023, 2023 | 2 | 2023 |
| Fantastic Copyrighted Beasts and How (Not) to Generate Them L He, Y Huang, W Shi, T Xie, H Liu, Y Wang, L Zettlemoyer, C Zhang, ... arXiv preprint arXiv:2406.14526, 2024 | 1 | 2024 |
| Evaluating Copyright Takedown Methods for Language Models B Wei, W Shi, Y Huang, NA Smith, C Zhang, L Zettlemoyer, K Li, ... arXiv preprint arXiv:2406.18664, 2024 | | 2024 |
Kai LiProfessor of computer science, Princeton university在 cs.princeton.edu 的电子邮件经过验证
