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Journal Articles
- 2024
[j5]Yuguang Yao, Xiao Guo, Vishal Asnani, Yifan Gong, Jiancheng Liu, Xue Lin, Xiaoming Liu, Sijia Liu:
Reverse Engineering of Deceptions on Machine- and Human-Centric Attacks. Found. Trends Priv. Secur. 6(2): 53-152 (2024)- [j4]Meng Zhao, Jiancheng Liu, Yindi Zhang:
Influence of environmental pollution and bacterial hyper-infectivity on dynamics of a waterborne pathogen model with free boundaries. Networks Heterog. Media 19(3): 940-969 (2024) - [j3]Ye Cao
, Song Xiao, Guangning Wu, Guoqiang Gao, Yujun Guo, Baoqiang Zhang, Jiancheng Liu, Xueqin Zhang, Zijing Wang, Pupu Li, Puyang Liu, Yuhui Zhang, Jie Yu:
The Reflux Regulation Methodology of Adapting Transiently-Varying Grounding Impedance for High-Speed Trains Based on Adjustable Resistance Technique. IEEE Trans. Veh. Technol. 73(9): 12718-12730 (2024) - 2023
- [j2]Sirui Duan, Jiancheng Liu, Yucai Pang, Xiang Yu, Chao Wu:
A joint denoising and deep learning detector for OFDM-IM. IET Commun. 17(13): 1513-1523 (2023) - 2000
- [j1]Xiren Yan, Kazuo Yamazaki, Jiancheng Liu:
Recognition of machining features and feature topologies from NC programs. Comput. Aided Des. 32(10): 605-616 (2000)
Conference and Workshop Papers
- 2024
- [c12]Chongyu Fan, Jiancheng Liu, Alfred Olivier Hero, Sijia Liu:
Challenging Forgets: Unveiling the Worst-Case Forget Sets in Machine Unlearning. ECCV (21) 2024: 278-297 - [c11]Yimeng Zhang, Jinghan Jia, Xin Chen, Aochuan Chen, Yihua Zhang, Jiancheng Liu, Ke Ding, Sijia Liu:
To Generate or Not? Safety-Driven Unlearned Diffusion Models Are Still Easy to Generate Unsafe Images ... For Now. ECCV (57) 2024: 385-403 - [c10]Jinghan Jia, Yihua Zhang, Yimeng Zhang, Jiancheng Liu, Bharat Runwal, James Diffenderfer, Bhavya Kailkhura, Sijia Liu:
SOUL: Unlocking the Power of Second-Order Optimization for LLM Unlearning. EMNLP 2024: 4276-4292 - [c9]Aochuan Chen, Yimeng Zhang, Jinghan Jia, James Diffenderfer, Konstantinos Parasyris, Jiancheng Liu, Yihua Zhang, Zheng Zhang, Bhavya Kailkhura, Sijia Liu:
DeepZero: Scaling Up Zeroth-Order Optimization for Deep Model Training. ICLR 2024 - [c8]Chongyu Fan, Jiancheng Liu, Yihua Zhang, Eric Wong, Dennis Wei, Sijia Liu:
SalUn: Empowering Machine Unlearning via Gradient-based Weight Saliency in Both Image Classification and Generation. ICLR 2024 - 2023
- [c7]Jinghan Jia, Jiancheng Liu, Parikshit Ram, Yuguang Yao, Gaowen Liu, Yang Liu, Pranay Sharma, Sijia Liu:
Model Sparsity Can Simplify Machine Unlearning. NeurIPS 2023 - [c6]Yihua Zhang, Yimeng Zhang, Aochuan Chen, Jinghan Jia, Jiancheng Liu, Gaowen Liu, Mingyi Hong, Shiyu Chang, Sijia Liu:
Selectivity Drives Productivity: Efficient Dataset Pruning for Enhanced Transfer Learning. NeurIPS 2023 - 2020
- [c5]Dapeng Zhang, Liu Yajun, Jiancheng Liu:
A Content-Based Deep Hybrid Approach with Segmented Max-Pooling. Intelligent Information Processing 2020: 299-309 - 2019
- [c4]Yuanming Hu, Jiancheng Liu, Andrew Spielberg, Joshua B. Tenenbaum, William T. Freeman, Jiajun Wu, Daniela Rus, Wojciech Matusik:
ChainQueen: A Real-Time Differentiable Physical Simulator for Soft Robotics. ICRA 2019: 6265-6271 - 2017
- [c3]Xi Chen, Erjin Zhou, Yuchen Mo, Jiancheng Liu, Zhimin Cao:
Delving Deep Into Coarse-to-Fine Framework for Facial Landmark Localization. CVPR Workshops 2017: 2088-2095 - 2016
- [c2]Hongzhi Zhao, Jiancheng Liu, Jun Wang, Wenbo Guo, Youxi Tang:
Impacts of Attenuators on Analog Self-Interference Cancellation in Full Duplex Radios. GLOBECOM Workshops 2016: 1-5 - 2008
- [c1]Jiancheng Liu, Xinhua Jiang, Baohua Lan:
Learning TSK Fuzzy Model by GA-BP Method. ICYCS 2008: 1717-1721
Informal and Other Publications
- 2024
- [i16]Yihua Zhang, Yimeng Zhang, Yuguang Yao, Jinghan Jia, Jiancheng Liu, Xiaoming Liu, Sijia Liu:
UnlearnCanvas: A Stylized Image Dataset to Benchmark Machine Unlearning for Diffusion Models. CoRR abs/2402.11846 (2024) - [i15]Chongyu Fan, Jiancheng Liu, Alfred O. Hero III, Sijia Liu:
Challenging Forgets: Unveiling the Worst-Case Forget Sets in Machine Unlearning. CoRR abs/2403.07362 (2024) - [i14]Jinghan Jia, Yihua Zhang, Yimeng Zhang, Jiancheng Liu, Bharat Runwal, James Diffenderfer, Bhavya Kailkhura, Sijia Liu:
SOUL: Unlocking the Power of Second-Order Optimization for LLM Unlearning. CoRR abs/2404.18239 (2024) - [i13]Yimeng Zhang, Xin Chen, Jinghan Jia, Yihua Zhang, Chongyu Fan, Jiancheng Liu, Mingyi Hong, Ke Ding, Sijia Liu:
Defensive Unlearning with Adversarial Training for Robust Concept Erasure in Diffusion Models. CoRR abs/2405.15234 (2024) - [i12]Zonglin Di, Zhaowei Zhu, Jinghan Jia, Jiancheng Liu, Zafar Takhirov, Bo Jiang, Yuanshun Yao, Sijia Liu, Yang Liu:
Label Smoothing Improves Machine Unlearning. CoRR abs/2406.07698 (2024) - [i11]Mingrui Zhang, Chunyang Wang, Stephan Kramer, Joseph G. Wallwork, Siyi Li, Jiancheng Liu, Xiang Chen, Matthew D. Piggott:
Towards Universal Mesh Movement Networks. CoRR abs/2407.00382 (2024) - [i10]Chongyu Fan, Jiancheng Liu, Licong Lin, Jinghan Jia, Ruiqi Zhang, Song Mei, Sijia Liu:
Simplicity Prevails: Rethinking Negative Preference Optimization for LLM Unlearning. CoRR abs/2410.07163 (2024) - [i9]Jinghan Jia, Jiancheng Liu, Yihua Zhang, Parikshit Ram, Nathalie Baracaldo, Sijia Liu:
WAGLE: Strategic Weight Attribution for Effective and Modular Unlearning in Large Language Models. CoRR abs/2410.17509 (2024) - 2023
- [i8]Yuguang Yao, Jiancheng Liu, Yifan Gong, Xiaoming Liu, Yanzhi Wang, Xue Lin, Sijia Liu:
Can Adversarial Examples Be Parsed to Reveal Victim Model Information? CoRR abs/2303.07474 (2023) - [i7]Jinghan Jia, Jiancheng Liu, Parikshit Ram, Yuguang Yao, Gaowen Liu, Yang Liu, Pranay Sharma, Sijia Liu:
Model Sparsification Can Simplify Machine Unlearning. CoRR abs/2304.04934 (2023) - [i6]Aochuan Chen, Yimeng Zhang, Jinghan Jia, James Diffenderfer, Jiancheng Liu, Konstantinos Parasyris, Yihua Zhang, Zheng Zhang, Bhavya Kailkhura, Sijia Liu:
DeepZero: Scaling up Zeroth-Order Optimization for Deep Model Training. CoRR abs/2310.02025 (2023) - [i5]Yihua Zhang, Yimeng Zhang, Aochuan Chen, Jinghan Jia, Jiancheng Liu, Gaowen Liu, Mingyi Hong, Shiyu Chang, Sijia Liu:
Selectivity Drives Productivity: Efficient Dataset Pruning for Enhanced Transfer Learning. CoRR abs/2310.08782 (2023) - [i4]Yimeng Zhang, Jinghan Jia, Xin Chen, Aochuan Chen, Yihua Zhang, Jiancheng Liu, Ke Ding, Sijia Liu:
To Generate or Not? Safety-Driven Unlearned Diffusion Models Are Still Easy To Generate Unsafe Images ... For Now. CoRR abs/2310.11868 (2023) - [i3]Chongyu Fan, Jiancheng Liu, Yihua Zhang, Dennis Wei, Eric Wong, Sijia Liu:
SalUn: Empowering Machine Unlearning via Gradient-based Weight Saliency in Both Image Classification and Generation. CoRR abs/2310.12508 (2023) - 2022
- [i2]Yu Fang, Jiancheng Liu, Mingrui Zhang, Jiasheng Zhang, Yidong Ma, Minchen Li, Yuanming Hu, Chenfanfu Jiang, Tiantian Liu:
Complex Locomotion Skill Learning via Differentiable Physics. CoRR abs/2206.02341 (2022) - 2018
- [i1]Yuanming Hu, Jiancheng Liu, Andrew Spielberg, Joshua B. Tenenbaum, William T. Freeman, Jiajun Wu, Daniela Rus, Wojciech Matusik:
ChainQueen: A Real-Time Differentiable Physical Simulator for Soft Robotics. CoRR abs/1810.01054 (2018)
Coauthor Index
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