| Model sparsification can simplify machine unlearning J Jia, J Liu, P Ram, Y Yao, G Liu, Y Liu, P Sharma, S Liu arXiv preprint arXiv:2304.04934 1 (2), 3, 2023 | 105* | 2023 |
| 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, 1-14, 2025 | 104 | 2025 |
| Understanding and improving visual prompting: A label-mapping perspective A Chen, Y Yao, PY Chen, Y Zhang, S Liu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 80 | 2023 |
| Advancing model pruning via bi-level optimization Y Zhang, Y Yao, P Ram, P Zhao, T Chen, M Hong, Y Wang, S Liu Advances in Neural Information Processing Systems 35, 18309-18326, 2022 | 66 | 2022 |
| Deeplora: Learning accurate path loss model for long distance links in lpwan L Liu, Y Yao, Z Cao, M Zhang IEEE INFOCOM 2021-IEEE Conference on Computer Communications, 1-10, 2021 | 61 | 2021 |
| Visual prompting for adversarial robustness A Chen, P Lorenz, Y Yao, PY Chen, S Liu ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and …, 2023 | 39 | 2023 |
| Wi-fi see it all: generative adversarial network-augmented versatile wi-fi imaging C Li, Z Liu, Y Yao, Z Cao, M Zhang, Y Liu Proceedings of the 18th Conference on Embedded Networked Sensor Systems, 436-448, 2020 | 38 | 2020 |
| An introduction to bilevel optimization: Foundations and applications in signal processing and machine learning Y Zhang, P Khanduri, I Tsaknakis, Y Yao, M Hong, S Liu IEEE Signal Processing Magazine 41 (1), 38-59, 2024 | 37 | 2024 |
| 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 arXiv preprint arXiv:2203.14195, 2022 | 35 | 2022 |
| Unlearncanvas: A stylized image dataset to benchmark machine unlearning for diffusion models Y Zhang, Y Zhang, Y Yao, J Jia, J Liu, X Liu, S Liu arXiv e-prints, arXiv: 2402.11846, 2024 | 28 | 2024 |
| Reverse engineering of imperceptible adversarial image perturbations Y Gong, Y Yao, Y Li, Y Zhang, X Liu, X Lin, S Liu arXiv preprint arXiv:2203.14145, 2022 | 23 | 2022 |
| Patronus: Preventing unauthorized speech recordings with support for selective unscrambling L Li, M Liu, Y Yao, F Dang, Z Cao, Y Liu Proceedings of the 18th Conference on Embedded Networked Sensor Systems, 245-257, 2020 | 22 | 2020 |
| LoSee: Long-Range Shared Bike Communication System Based on LoRaWAN Protocol. Y Yao, Z Ma, Z Cao EWSN, 407-412, 2019 | 15 | 2019 |
| CryoRL: reinforcement learning enables efficient cryo-EM data collection Q Fan, Y Li, Y Yao, J Cohn, S Liu, Z Xu, S Vos, M Cianfrocco Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2024 | 9 | 2024 |
| Learning to generate image source-agnostic universal adversarial perturbations P Zhao, P Ram, S Lu, Y Yao, D Bouneffouf, X Lin, S Liu arXiv preprint arXiv:2009.13714, 2020 | 8 | 2020 |
| Backdoor secrets unveiled: Identifying backdoor data with optimized scaled prediction consistency S Pal, Y Yao, R Wang, B Shen, S Liu arXiv preprint arXiv:2403.10717, 2024 | 7 | 2024 |
| From trojan horses to castle walls: Unveiling bilateral backdoor effects in diffusion models Z Pan, Y Yao, G Liu, B Shen, HV Zhao, RR Kompella, S Liu NeurIPS 2023 Workshop on Backdoors in Deep Learning-The Good, the Bad, and …, 2023 | 6 | 2023 |
| Towards understanding how self-training tolerates data backdoor poisoning S Pal, R Wang, Y Yao, S Liu arXiv preprint arXiv:2301.08751, 2023 | 6 | 2023 |
| Reverse engineering of deceptions on machine-and human-centric attacks Y Yao, X Guo, V Asnani, Y Gong, J Liu, X Lin, X Liu, S Liu Foundations and Trends® in Privacy and Security 6 (2), 53-152, 2024 | 5 | 2024 |
| Visual prompting reimagined: The power of activation prompts, 2024 Y Zhang, H Li, Y Yao, A Chen, S Zhang, PY Chen, M Wang, S Liu URL https://openreview. net/forum, 0 | 5 | |
Sijia LiuMichigan State University & MIT-IBM Watson AI LabE-mailová adresa ověřena na: msu.edu