Instabilities in Conventional Multi-Coil MRI Reconstruction with Small Adversarial Perturbations. - Chi Zhang 057; Jinghan Jia; Burhaneddin Yaman; Steen Moeller; Sijia Liu 001; Mingyi Hong 001; Mehmet Akçakaya (ACSCC, 2021)

On Instabilities of Conventional Multi-Coil MRI Reconstruction to Small Adverserial Perturbations. - Chi Zhang 057; Jinghan Jia; Burhaneddin Yaman; Steen Moeller; Sijia Liu 001; Mingyi Hong 001; Mehmet Akçakaya (CoRR, 2021)

How to Robustify Black-Box ML Models? A Zeroth-Order Optimization Perspective. - Yimeng Zhang; Yuguang Yao; Jinghan Jia; Jinfeng Yi; Mingyi Hong 001; Shiyu Chang; Sijia Liu 001 (ICLR, 2022)

Text-Visual Prompting for Efficient 2D Temporal Video Grounding. - Yimeng Zhang; Xin Chen; Jinghan Jia; Sijia Liu 001; Ke Ding (CVPR, 2023)

Robustness-Preserving Lifelong Learning Via Dataset Condensation. - Jinghan Jia; Yihua Zhang; Dogyoon Song; Sijia Liu 001; Alfred O. Hero III (ICASSP, 2023)

SMUG: Towards Robust Mri Reconstruction by Smoothed Unrolling. - Hui Li; Jinghan Jia; Shijun Liang; Yuguang Yao; Saiprasad Ravishankar; Sijia Liu 001 (ICASSP, 2023)

TextGrad: Advancing Robustness Evaluation in NLP by Gradient-Driven Optimization. - Bairu Hou; Jinghan Jia; Yihua Zhang; Guanhua Zhang; Yang Zhang 001; Sijia Liu 001; Shiyu Chang (ICLR, 2023)

Model Sparsity Can Simplify Machine Unlearning. - Jinghan Jia; Jiancheng Liu; Parikshit Ram; Yuguang Yao; Gaowen Liu; Yang Liu 018; Pranay Sharma; Sijia Liu 001 (NeurIPS, 2023)

Selectivity Drives Productivity: Efficient Dataset Pruning for Enhanced Transfer Learning. - Yihua Zhang; Yimeng Zhang; Aochuan Chen; Jinghan Jia; Jiancheng Liu; Gaowen Liu; Mingyi Hong 001; Shiyu Chang; Sijia Liu 001 (NeurIPS, 2023)

ClawSAT: Towards Both Robust and Accurate Code Models. - Jinghan Jia; Shashank Srikant; Tamara Mitrovska; Chuang Gan 001; Shiyu Chang; Sijia Liu 001; Una-May O'Reilly (SANER, 2023)

Model Sparsification Can Simplify Machine Unlearning. - Jinghan Jia; Jiancheng Liu; Parikshit Ram; Yuguang Yao; Gaowen Liu; Yang Liu 018; Pranay Sharma; Sijia Liu 001 (CoRR, 2023)

Robust MRI Reconstruction by Smoothed Unrolling (SMUG). - Shijun Liang; Van Hoang Minh Nguyen; Jinghan Jia; Ismail Alkhouri; Sijia Liu 001; Saiprasad Ravishankar (CoRR, 2023)

To Generate or Not? Safety-Driven Unlearned Diffusion Models Are Still Easy to Generate Unsafe Images ... For Now. - Yimeng Zhang; Jinghan Jia; Xin Chen; Aochuan Chen; Yihua Zhang; Jiancheng Liu; Ke Ding; Sijia Liu 001 (ECCV (57), 2024)

SOUL: Unlocking the Power of Second-Order Optimization for LLM Unlearning. - Jinghan Jia; Yihua Zhang; Yimeng Zhang; Jiancheng Liu; Bharat Runwal; James Diffenderfer; Bhavya Kailkhura; Sijia Liu 001 (EMNLP, 2024)

DeepZero: Scaling Up Zeroth-Order Optimization for Deep Model Training. - Aochuan Chen; Yimeng Zhang; Jinghan Jia; James Diffenderfer; Konstantinos Parasyris; Jiancheng Liu; Yihua Zhang; Zheng Zhang 005; Bhavya Kailkhura; Sijia Liu 001 (ICLR, 2024)

Leveraging LLMs for Dialogue Quality Measurement. - Jinghan Jia; Abi Komma; Timothy Leffel; Xujun Peng; Ajay Nagesh; Tamer Soliman; Aram Galstyan; Anoop Kumar (NAACL (Industry Track), 2024)

WAGLE: Strategic Weight Attribution for Effective and Modular Unlearning in Large Language Models. - Jinghan Jia; Jiancheng Liu; Yihua Zhang; Parikshit Ram; Nathalie Baracaldo; Sijia Liu 001 (NeurIPS, 2024)

Defensive Unlearning with Adversarial Training for Robust Concept Erasure in Diffusion Models. - Yimeng Zhang; Xin Chen; Jinghan Jia; Yihua Zhang; Chongyu Fan; Jiancheng Liu; Mingyi Hong 001; Ke Ding; Sijia Liu 001 (NeurIPS, 2024)

UnlearnCanvas: Stylized Image Dataset for Enhanced Machine Unlearning Evaluation in Diffusion Models. - Yihua Zhang; Chongyu Fan; Yimeng Zhang; Yuguang Yao; Jinghan Jia; Jiancheng Liu; Gaoyuan Zhang; Gaowen Liu; Ramana Kompella; Xiaoming Liu 002; Sijia Liu 001 (NeurIPS, 2024)

Rethinking Machine Unlearning for Large Language Models. - Sijia Liu 001; Yuanshun Yao; Jinghan Jia; Stephen Casper; Nathalie Baracaldo; Peter Hase; Xiaojun Xu; Yuguang Yao; Hang Li 001; Kush R. Varshney; Mohit Bansal; Sanmi Koyejo; et al. (CoRR, 2024)

UnlearnCanvas: A Stylized Image Dataset to Benchmark Machine Unlearning for Diffusion Models. - Yihua Zhang; Yimeng Zhang; Yuguang Yao; Jinghan Jia; Jiancheng Liu; Xiaoming Liu 002; Sijia Liu 001 (CoRR, 2024)

Label Smoothing Improves Machine Unlearning. - Zonglin Di; Zhaowei Zhu; Jinghan Jia; Jiancheng Liu; Zafar Takhirov; Bo Jiang; Yuanshun Yao; Sijia Liu 001; Yang Liu 018 (CoRR, 2024)

Simplicity Prevails: Rethinking Negative Preference Optimization for LLM Unlearning. - Chongyu Fan; Jiancheng Liu; Licong Lin; Jinghan Jia; Ruiqi Zhang; Song Mei; Sijia Liu 001 (CoRR, 2024)

UOE: Unlearning One Expert Is Enough For Mixture-of-experts LLMS. - Haomin Zhuang; Yihua Zhang; Kehan Guo; Jinghan Jia; Gaowen Liu; Sijia Liu 001; Xiangliang Zhang 001 (CoRR, 2024)

Robust Multi-bit Text Watermark with LLM-based Paraphrasers. - Xiaojun Xu; Jinghan Jia; Yuanshun Yao; Yang Liu; Hang Li 001 (CoRR, 2024)

Forget Vectors at Play: Universal Input Perturbations Driving Machine Unlearning in Image Classification. - Changchang Sun; Ren Wang 008; Yihua Zhang; Jinghan Jia; Jiancheng Liu; Gaowen Liu; Sijia Liu 001; Yan Yan (CoRR, 2024)

SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? - Haomin Zhuang; Yihua Zhang; Kehan Guo; Jinghan Jia; Gaowen Liu; Sijia Liu 001; Xiangliang Zhang 001 (ACL (1), 2025)

Rethinking machine unlearning for large language models. - Sijia Liu 001; Yuanshun Yao; Jinghan Jia; Stephen Casper; Nathalie Baracaldo; Peter Hase; Yuguang Yao; Chris Yuhao Liu; Xiaojun Xu; Hang Li 001; Kush R. Varshney; Mohit Bansal; et al. (Nat. Mac. Intell., 2025)

Towards LLM Unlearning Resilient to Relearning Attacks: A Sharpness-Aware Minimization Perspective and Beyond. - Chongyu Fan; Jinghan Jia; Yihua Zhang; Anil Ramakrishna; Mingyi Hong 001; Sijia Liu 001 (CoRR, 2025)

Invariance Makes LLM Unlearning Resilient Even to Unanticipated Downstream Fine-Tuning. - Changsheng Wang; Yihua Zhang; Jinghan Jia; Parikshit Ram; Dennis Wei; Yuguang Yao; Soumyadeep Pal; Nathalie Baracaldo; Sijia Liu 001 (CoRR, 2025)

EPiC: Towards Lossless Speedup for Reasoning Training through Edge-Preserving CoT Condensation. - Jinghan Jia; Hadi Reisizadeh; Chongyu Fan; Nathalie Baracaldo; Mingyi Hong 001; Sijia Liu 001 (CoRR, 2025)

BLUR: A Bi-Level Optimization Approach for LLM Unlearning. - Hadi Reisizadeh; Jinghan Jia; Zhiqi Bu; Bhanukiran Vinzamuri; Anil Ramakrishna; Kai-Wei Chang; Volkan Cevher; Sijia Liu 001; Mingyi Hong 001 (CoRR, 2025)

CyclicReflex: Improving Large Reasoning Models via Cyclical Reflection Token Scheduling. - Chongyu Fan; Yihua Zhang; Jinghan Jia; Alfred Olivier Hero; Sijia Liu 001 (CoRR, 2025)

Reasoning Model Unlearning: Forgetting Traces, Not Just Answers, While Preserving Reasoning Skills. - Changsheng Wang; Chongyu Fan; Yihua Zhang; Jinghan Jia; Dennis Wei; Parikshit Ram; Nathalie Baracaldo; Sijia Liu 001 (CoRR, 2025)