Jinghan Jia

According to our database, Jinghan Jia authored at least 25 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Forget Vectors at Play: Universal Input Perturbations Driving Machine Unlearning in Image Classification.

Changchang Sun, Ren Wang, Yihua Zhang, Jinghan Jia, Jiancheng Liu, Gaowen Liu, Sijia Liu, Yan Yan

CoRR, 2024

Robust Multi-bit Text Watermark with LLM-based Paraphrasers.

Xiaojun Xu, Jinghan Jia, Yuanshun Yao, Yang Liu, Hang Li

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, Xiangliang Zhang

CoRR, 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

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

CoRR, 2024

Label Smoothing Improves Machine Unlearning.

Zonglin Di, Zhaowei Zhu, Jinghan Jia, Jiancheng Liu, Zafar Takhirov, Bo Jiang, Yuanshun Yao, Sijia Liu, Yang Liu

CoRR, 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, Ke Ding, Sijia Liu

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, Sijia Liu

CoRR, 2024

Rethinking Machine Unlearning for Large Language Models.

Sijia Liu, Yuanshun Yao, Jinghan Jia, Stephen Casper, Nathalie Baracaldo, Peter Hase, Xiaojun Xu, Yuguang Yao, Hang Li, Kush R. Varshney, Mohit Bansal, Sanmi Koyejo, Yang Liu

CoRR, 2024

Leveraging LLMs for Dialogue Quality Measurement.

Jinghan Jia, Abi Komma, Timothy Leffel, Xujun Peng, Ajay Nagesh, Tamer Soliman, Aram Galstyan, Anoop Kumar

Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Industry Track, 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, Bhavya Kailkhura, Sijia Liu

Proceedings of the Twelfth International Conference on Learning Representations, 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

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

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

Proceedings of the Computer Vision - ECCV 2024, 2024

2023

Robust MRI Reconstruction by Smoothed Unrolling (SMUG).

Shijun Liang, Van Hoang Minh Nguyen, Jinghan Jia, Ismail Alkhouri, Sijia Liu, Saiprasad Ravishankar

CoRR, 2023

Model Sparsification Can Simplify Machine Unlearning.

Jinghan Jia, Jiancheng Liu, Parikshit Ram, Yuguang Yao, Gaowen Liu, Yang Liu, Pranay Sharma, Sijia Liu

CoRR, 2023

ClawSAT: Towards Both Robust and Accurate Code Models.

Jinghan Jia, Shashank Srikant, Tamara Mitrovska, Chuang Gan, Shiyu Chang, Sijia Liu, Una-May O'Reilly

Proceedings of the IEEE International Conference on Software Analysis, 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, Shiyu Chang, Sijia Liu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Model Sparsity Can Simplify Machine Unlearning.

Jinghan Jia, Jiancheng Liu, Parikshit Ram, Yuguang Yao, Gaowen Liu, Yang Liu, Pranay Sharma, Sijia Liu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

TextGrad: Advancing Robustness Evaluation in NLP by Gradient-Driven Optimization.

Bairu Hou, Jinghan Jia, Yihua Zhang, Guanhua Zhang, Yang Zhang, Sijia Liu, Shiyu Chang

Proceedings of the Eleventh International Conference on Learning Representations, 2023

SMUG: Towards Robust Mri Reconstruction by Smoothed Unrolling.

Hui Li, Jinghan Jia, Shijun Liang, Yuguang Yao, Saiprasad Ravishankar, Sijia Liu

Proceedings of the IEEE International Conference on Acoustics, 2023

Robustness-Preserving Lifelong Learning Via Dataset Condensation.

Jinghan Jia, Yihua Zhang, Dogyoon Song, Sijia Liu, Alfred O. Hero III

Proceedings of the IEEE International Conference on Acoustics, 2023

Text-Visual Prompting for Efficient 2D Temporal Video Grounding.

Yimeng Zhang, Xin Chen, Jinghan Jia, Sijia Liu, Ke Ding

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

How to Robustify Black-Box ML Models? A Zeroth-Order Optimization Perspective.

Yimeng Zhang, Yuguang Yao, Jinghan Jia, Jinfeng Yi, Mingyi Hong, Shiyu Chang, Sijia Liu

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

On Instabilities of Conventional Multi-Coil MRI Reconstruction to Small Adverserial Perturbations.

Chi Zhang, Jinghan Jia, Burhaneddin Yaman, Steen Moeller, Sijia Liu, Mingyi Hong, Mehmet Akçakaya

CoRR, 2021

Instabilities in Conventional Multi-Coil MRI Reconstruction with Small Adversarial Perturbations.

Chi Zhang, Jinghan Jia, Burhaneddin Yaman, Steen Moeller, Sijia Liu, Mingyi Hong, Mehmet Akçakaya

Proceedings of the 55th Asilomar Conference on Signals, Systems, and Computers, 2021