| Rethinking machine unlearning for large language models S Liu, Y Yao, J Jia, S Casper, N Baracaldo, P Hase, Y Yao, CY Liu, X Xu, ... Nature Machine Intelligence, 2024 | 102 | 2024 |
| Model Sparsity Can Simplify Machine Unlearning J Jia, J Liu, P Ram, Y Yao, G Liu, Y Liu, P Sharma, S Liu NeurIPS'23 Spotlight, 2023 | 101* | 2023 |
| To generate or not? safety-driven unlearned diffusion models are still easy to generate unsafe images... for now Y Zhang*, J Jia*, X Chen, A Chen, Y Zhang, J Liu, K Ding, S Liu ECCV 2024, 2023 | 60 | 2023 |
| Deepzero: Scaling up zeroth-order optimization for deep model training A Chen, Y Zhang, J Jia, J Diffenderfer, J Liu, K Parasyris, Y Zhang, ... ICLR'24, 2023 | 35 | 2023 |
| How to robustify black-box ml models? a zeroth-order optimization perspective Y Zhang, Y Yao, J Jia, J Yi, M Hong, S Chang, S Liu ICLR'22, 2022 | 33 | 2022 |
| UnlearnCanvas: Stylized Image Dataset for Enhanced Machine Unlearning Evaluation in Diffusion Models Y Zhang, C Fan, Y Zhang, Y Yao, J Jia, J Liu, G Zhang, G Liu, ... The Thirty-eight Conference on Neural Information Processing Systems …, 0 | 29* | |
| Text-visual prompting for efficient 2d temporal video grounding Y Zhang, X Chen, J Jia, S Liu, K Ding Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 27 | 2023 |
| Soul: Unlocking the power of second-order optimization for llm unlearning J Jia, Y Zhang, Y Zhang, J Liu, B Runwal, J Diffenderfer, B Kailkhura, ... EMNLP'24 Main Track, 2024 | 24 | 2024 |
| Defensive Unlearning with Adversarial Training for Robust Concept Erasure in Diffusion Models Y Zhang, X Chen, J Jia, Y Zhang, C Fan, J Liu, M Hong, K Ding, S Liu NeurIPS'24, 2024 | 22 | 2024 |
| Textgrad: Advancing robustness evaluation in nlp by gradient-driven optimization B Hou, J Jia, Y Zhang, G Zhang, Y Zhang, S Liu, S Chang ICLR'23, 2022 | 19 | 2022 |
| Instabilities in conventional multi-coil MRI reconstruction with small adversarial perturbations C Zhang, J Jia, B Yaman, S Moeller, S Liu, M Hong, M Akçakaya 2021 55th Asilomar Conference on Signals, Systems, and Computers, 895-899, 2021 | 17 | 2021 |
| Clawsat: Towards both robust and accurate code models J Jia, S Srikant, T Mitrovska, C Gan, S Chang, S Liu, UM O’Reilly 2023 IEEE International Conference on Software Analysis, Evolution and …, 2023 | 16 | 2023 |
| On the robustness of deep learning-based mri reconstruction to image transformations J Jia, M Hong, Y Zhang, M Akçakaya, S Liu arXiv preprint arXiv:2211.04930, 2022 | 8 | 2022 |
| Selectivity Drives Productivity: Efficient Dataset Pruning for Enhanced Transfer Learning Y Zhang, Y Zhang, A Chen, J Jia, J Liu, G Liu, M Hong, S Chang, S Liu Advances in Neural Information Processing Systems 36, 2024 | 6 | 2024 |
| SMUG: Towards robust MRI reconstruction by smoothed unrolling H Li, J Jia, S Liang, Y Yao, S Ravishankar, S Liu ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and …, 2023 | 4 | 2023 |
| Label Smoothing Improves Machine Unlearning Z Di, Z Zhu, J Jia, J Liu, Z Takhirov, B Jiang, Y Yao, S Liu, Y Liu arXiv preprint arXiv:2406.07698, 2024 | 3 | 2024 |
| Robustness-preserving lifelong learning via dataset condensation J Jia, Y Zhang, D Song, S Liu, A Hero ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and …, 2023 | 3 | 2023 |
| Robust MRI Reconstruction by Smoothed Unrolling (SMUG) S Liang, VHM Nguyen, J Jia, I Alkhouri, S Liu, S Ravishankar arXiv preprint arXiv:2312.07784, 2023 | 2 | 2023 |
| WAGLE: Strategic Weight Attribution for Effective and Modular Unlearning in Large Language Models J Jia, J Liu, Y Zhang, P Ram, N Baracaldo, S Liu NeurIPS'24, 2024 | 1 | 2024 |
| Leveraging LLMs for dialogue quality measurement J Jia, A Komma, T Leffel, X Peng, A Nagesh, T Soliman, A Galstyan, ... NAACL'24, 2024 | 1 | 2024 |
Sijia LiuMichigan State University & MIT-IBM Watson AI LabZweryfikowany adres z msu.edu