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2020 – today
- 2024
[j6]Jinghui Chen, Takayuki Mizuno, Shohei Doi:
Analyzing political party positions through multi-language twitter text embeddings. Frontiers Big Data 7 (2024)- [j5]Qingqing Cai, Jinghui Chen, Deyu Luo
, Gang Sun, Hongfang Yu, Mohsen Guizani:
Deter-Pay: A Deterministic Routing Protocol in Concurrent Payment Channel Network. IEEE Internet Things J. 11(19): 31206-31220 (2024) - [j4]Dongruo Zhou, Jinghui Chen, Yuan Cao, Ziyan Yang, Quanquan Gu:
On the Convergence of Adaptive Gradient Methods for Nonconvex Optimization. Trans. Mach. Learn. Res. 2024 (2024) - [c44]Ziyi Yin, Muchao Ye, Tianrong Zhang, Jiaqi Wang, Han Liu, Jinghui Chen, Ting Wang, Fenglong Ma:
VQAttack: Transferable Adversarial Attacks on Visual Question Answering via Pre-trained Models. AAAI 2024: 6755-6763 - [c43]Hangfan Zhang, Zhimeng Guo, Huaisheng Zhu, Bochuan Cao, Lu Lin, Jinyuan Jia, Jinghui Chen, Dinghao Wu:
Jailbreak Open-Sourced Large Language Models via Enforced Decoding. ACL (1) 2024: 5475-5493 - [c42]Bochuan Cao, Yuanpu Cao, Lu Lin, Jinghui Chen:
Defending Against Alignment-Breaking Attacks via Robustly Aligned LLM. ACL (1) 2024: 10542-10560 - [c41]Weiyu Sun, Xinyu Zhang, Hao Lu, Ying-Cong Chen, Ting Wang, Jinghui Chen, Lu Lin:
Backdoor Contrastive Learning via Bi-level Trigger Optimization. ICLR 2024 - [c40]Yujia Wang, Yuanpu Cao, Jingcheng Wu, Ruoyu Chen, Jinghui Chen:
Tackling the Data Heterogeneity in Asynchronous Federated Learning with Cached Update Calibration. ICLR 2024 - [c39]Songtao Liu, Jinghui Chen, Tianfan Fu, Lu Lin, Marinka Zitnik, Dinghao Wu:
Graph Adversarial Diffusion Convolution. ICML 2024 - [c38]Yujia Wang, Shiqiang Wang, Songtao Lu, Jinghui Chen:
FADAS: Towards Federated Adaptive Asynchronous Optimization. ICML 2024 - [c37]Tianrong Zhang, Zhaohan Xi, Ting Wang, Prasenjit Mitra, Jinghui Chen:
PromptFix: Few-shot Backdoor Removal via Adversarial Prompt Tuning. NAACL-HLT 2024: 3212-3225 - [c36]Yuanpu Cao, Bochuan Cao, Jinghui Chen:
Stealthy and Persistent Unalignment on Large Language Models via Backdoor Injections. NAACL-HLT 2024: 4920-4935 - [c35]Changjiang Li, Ren Pang, Bochuan Cao, Zhaohan Xi, Jinghui Chen, Shouling Ji, Ting Wang:
On the Difficulty of Defending Contrastive Learning against Backdoor Attacks. USENIX Security Symposium 2024 - [c34]Yuanxin Zhuang, Chuan Shi, Mengmei Zhang, Jinghui Chen, Lingjuan Lyu, Pan Zhou, Lichao Sun:
Unveiling the Secrets without Data: Can Graph Neural Networks Be Exploited through Data-Free Model Extraction Attacks? USENIX Security Symposium 2024 - [i39]Ziyi Yin, Muchao Ye, Tianrong Zhang, Jiaqi Wang, Han Liu, Jinghui Chen, Ting Wang, Fenglong Ma:
VQAttack: Transferable Adversarial Attacks on Visual Question Answering via Pre-trained Models. CoRR abs/2402.11083 (2024) - [i38]Weiyu Sun, Xinyu Zhang, Hao Lu, Yingcong Chen, Ting Wang, Jinghui Chen, Lu Lin:
Backdoor Contrastive Learning via Bi-level Trigger Optimization. CoRR abs/2404.07863 (2024) - [i37]Tianrong Zhang, Bochuan Cao, Yuanpu Cao, Lu Lin, Prasenjit Mitra, Jinghui Chen:
WordGame: Efficient & Effective LLM Jailbreak via Simultaneous Obfuscation in Query and Response. CoRR abs/2405.14023 (2024) - [i36]Yurui Chang, Bochuan Cao, Yujia Wang, Jinghui Chen, Lu Lin:
XPrompt:Explaining Large Language Model's Generation via Joint Prompt Attribution. CoRR abs/2405.20404 (2024) - [i35]Yuanpu Cao, Tianrong Zhang, Bochuan Cao, Ziyi Yin, Lu Lin, Fenglong Ma, Jinghui Chen:
Personalized Steering of Large Language Models: Versatile Steering Vectors Through Bi-directional Preference Optimization. CoRR abs/2406.00045 (2024) - [i34]Songtao Liu, Jinghui Chen, Tianfan Fu, Lu Lin, Marinka Zitnik, Dinghao Wu:
Graph Adversarial Diffusion Convolution. CoRR abs/2406.02059 (2024) - [i33]Tianrong Zhang, Zhaohan Xi, Ting Wang, Prasenjit Mitra, Jinghui Chen:
PromptFix: Few-shot Backdoor Removal via Adversarial Prompt Tuning. CoRR abs/2406.04478 (2024) - [i32]Changjiang Li, Ren Pang, Bochuan Cao, Jinghui Chen, Fenglong Ma, Shouling Ji, Ting Wang:
Watch the Watcher! Backdoor Attacks on Security-Enhancing Diffusion Models. CoRR abs/2406.09669 (2024) - [i31]Jooyoung Lee, Toshini Agrawal, Adaku Uchendu, Thai Le, Jinghui Chen, Dongwon Lee:
PlagBench: Exploring the Duality of Large Language Models in Plagiarism Generation and Detection. CoRR abs/2406.16288 (2024) - [i30]Yujia Wang, Shiqiang Wang, Songtao Lu, Jinghui Chen:
FADAS: Towards Federated Adaptive Asynchronous Optimization. CoRR abs/2407.18365 (2024) - [i29]Yuanpu Cao, Lu Lin, Jinghui Chen:
Adversarially Robust Industrial Anomaly Detection Through Diffusion Model. CoRR abs/2408.04839 (2024) - [i28]Jiaqi Wang, Xiaochen Wang, Lingjuan Lyu, Jinghui Chen, Fenglong Ma:
FEDMEKI: A Benchmark for Scaling Medical Foundation Models via Federated Knowledge Injection. CoRR abs/2408.09227 (2024) - [i27]Xiaochen Wang, Jiaqi Wang, Houping Xiao, Jinghui Chen, Fenglong Ma:
FEDKIM: Adaptive Federated Knowledge Injection into Medical Foundation Models. CoRR abs/2408.10276 (2024) - 2023
- [c33]Pei Fang, Jinghui Chen:
On the Vulnerability of Backdoor Defenses for Federated Learning. AAAI 2023: 11800-11808 - [c32]Hangzhi Guo, Feiran Jia, Jinghui Chen, Anna Cinzia Squicciarini, Amulya Yadav:
RoCourseNet: Robust Training of a Prediction Aware Recourse Model. CIKM 2023: 619-628 - [c31]Lu Lin, Jinghui Chen, Hongning Wang:
Spectral Augmentation for Self-Supervised Learning on Graphs. ICLR 2023 - [c30]Hangfan Zhang, Jinghui Chen, Lu Lin, Jinyuan Jia, Dinghao Wu:
Graph Contrastive Backdoor Attacks. ICML 2023: 40888-40910 - [c29]Muchao Ye, Jinghui Chen, Chenglin Miao, Han Liu, Ting Wang, Fenglong Ma:
PAT: Geometry-Aware Hard-Label Black-Box Adversarial Attacks on Text. KDD 2023: 3093-3104 - [c28]Ziyi Yin, Muchao Ye, Tianrong Zhang, Tianyu Du, Jinguo Zhu, Han Liu, Jinghui Chen, Ting Wang, Fenglong Ma:
VLATTACK: Multimodal Adversarial Attacks on Vision-Language Tasks via Pre-trained Models. NeurIPS 2023 - [c27]Bochuan Cao, Changjiang Li, Ting Wang, Jinyuan Jia, Bo Li, Jinghui Chen:
IMPRESS: Evaluating the Resilience of Imperceptible Perturbations Against Unauthorized Data Usage in Diffusion-Based Generative AI. NeurIPS 2023 - [c26]Zhaohan Xi, Tianyu Du, Changjiang Li, Ren Pang, Shouling Ji, Jinghui Chen, Fenglong Ma, Ting Wang:
Defending Pre-trained Language Models as Few-shot Learners against Backdoor Attacks. NeurIPS 2023 - [c25]Muchao Ye, Ziyi Yin, Tianrong Zhang, Tianyu Du, Jinghui Chen, Ting Wang, Fenglong Ma:
UniT: A Unified Look at Certified Robust Training against Text Adversarial Perturbation. NeurIPS 2023 - [c24]Hangfan Zhang, Jinyuan Jia, Jinghui Chen, Lu Lin, Dinghao Wu:
A3FL: Adversarially Adaptive Backdoor Attacks to Federated Learning. NeurIPS 2023 - [c23]Jinghui Chen, Yuan Cao, Quanquan Gu:
Benign Overfitting in Adversarially Robust Linear Classification. UAI 2023: 313-323 - [c22]Jooyoung Lee, Thai Le, Jinghui Chen, Dongwon Lee:
Do Language Models Plagiarize? WWW 2023: 3637-3647 - [i26]Pei Fang, Jinghui Chen:
On the Vulnerability of Backdoor Defenses for Federated Learning. CoRR abs/2301.08170 (2023) - [i25]Zhaohan Xi, Tianyu Du, Changjiang Li, Ren Pang, Shouling Ji, Jinghui Chen, Fenglong Ma, Ting Wang:
Defending Pre-trained Language Models as Few-shot Learners against Backdoor Attacks. CoRR abs/2309.13256 (2023) - [i24]Bochuan Cao, Yuanpu Cao, Lu Lin, Jinghui Chen:
Defending Against Alignment-Breaking Attacks via Robustly Aligned LLM. CoRR abs/2309.14348 (2023) - [i23]Hangfan Zhang, Zhimeng Guo, Huaisheng Zhu, Bochuan Cao, Lu Lin, Jinyuan Jia, Jinghui Chen, Dinghao Wu:
On the Safety of Open-Sourced Large Language Models: Does Alignment Really Prevent Them From Being Misused? CoRR abs/2310.01581 (2023) - [i22]Ziyi Yin, Muchao Ye, Tianrong Zhang, Tianyu Du, Jinguo Zhu, Han Liu, Jinghui Chen, Ting Wang, Fenglong Ma:
VLAttack: Multimodal Adversarial Attacks on Vision-Language Tasks via Pre-trained Models. CoRR abs/2310.04655 (2023) - [i21]Bochuan Cao, Changjiang Li, Ting Wang, Jinyuan Jia, Bo Li, Jinghui Chen:
IMPRESS: Evaluating the Resilience of Imperceptible Perturbations Against Unauthorized Data Usage in Diffusion-Based Generative AI. CoRR abs/2310.19248 (2023) - [i20]Yuanpu Cao, Bochuan Cao, Jinghui Chen:
Stealthy and Persistent Unalignment on Large Language Models via Backdoor Injections. CoRR abs/2312.00027 (2023) - [i19]Changjiang Li, Ren Pang, Bochuan Cao, Zhaohan Xi, Jinghui Chen, Shouling Ji, Ting Wang:
On the Difficulty of Defending Contrastive Learning against Backdoor Attacks. CoRR abs/2312.09057 (2023) - [i18]Tiejin Chen, Yuanpu Cao, Yujia Wang, Cho-Jui Hsieh, Jinghui Chen:
Federated Learning with Projected Trajectory Regularization. CoRR abs/2312.14380 (2023) - 2022
- [c21]Jinghui Chen, Yu Cheng, Zhe Gan, Quanquan Gu, Jingjing Liu:
Efficient Robust Training via Backward Smoothing. AAAI 2022: 6222-6230 - [c20]Yujia Wang, Lu Lin, Jinghui Chen:
Communication-Compressed Adaptive Gradient Method for Distributed Nonconvex Optimization. AISTATS 2022: 6292-6320 - [c19]Weiqi Peng, Jinghui Chen:
Learnability Lock: Authorized Learnability Control Through Adversarial Invertible Transformations. ICLR 2022 - [c18]Yujia Wang, Lu Lin, Jinghui Chen:
Communication-Efficient Adaptive Federated Learning. ICML 2022: 22802-22838 - [c17]Muchao Ye, Jinghui Chen, Chenglin Miao, Ting Wang, Fenglong Ma:
LeapAttack: Hard-Label Adversarial Attack on Text via Gradient-Based Optimization. KDD 2022: 2307-2315 - [c16]Shuwen Chai, Jinghui Chen:
One-shot Neural Backdoor Erasing via Adversarial Weight Masking. NeurIPS 2022 - [i17]Weiqi Peng, Jinghui Chen:
Learnability Lock: Authorized Learnability Control Through Adversarial Invertible Transformations. CoRR abs/2202.03576 (2022) - [i16]Jooyoung Lee, Thai Le, Jinghui Chen, Dongwon Lee:
Do Language Models Plagiarize? CoRR abs/2203.07618 (2022) - [i15]Yujia Wang, Lu Lin, Jinghui Chen:
Communication-Efficient Adaptive Federated Learning. CoRR abs/2205.02719 (2022) - [i14]Hangzhi Guo, Feiran Jia, Jinghui Chen, Anna Cinzia Squicciarini, Amulya Yadav:
RoCourseNet: Distributionally Robust Training of a Prediction Aware Recourse Model. CoRR abs/2206.00700 (2022) - [i13]Shuwen Chai, Jinghui Chen:
One-shot Neural Backdoor Erasing via Adversarial Weight Masking. CoRR abs/2207.04497 (2022) - [i12]Songtao Liu, Rex Ying, Hanze Dong, Lu Lin, Jinghui Chen, Dinghao Wu:
How Powerful is Implicit Denoising in Graph Neural Networks. CoRR abs/2209.14514 (2022) - [i11]Lu Lin, Jinghui Chen, Hongning Wang:
Spectral Augmentation for Self-Supervised Learning on Graphs. CoRR abs/2210.00643 (2022) - 2021
- [b1]Jinghui Chen:
Evaluating and Understanding Adversarial Robustness in Deep Learning. University of California, Los Angeles, USA, 2021 - [c15]Boxi Wu, Jinghui Chen, Deng Cai, Xiaofei He, Quanquan Gu:
Do Wider Neural Networks Really Help Adversarial Robustness? NeurIPS 2021: 7054-7067 - [i10]Yujia Wang, Lu Lin, Jinghui Chen:
Communication-Compressed Adaptive Gradient Method for Distributed Nonconvex Optimization. CoRR abs/2111.00705 (2021) - [i9]Jinghui Chen, Yuan Cao, Quanquan Gu:
Benign Overfitting in Adversarially Robust Linear Classification. CoRR abs/2112.15250 (2021) - 2020
- [j3]Chen Dong, Yulin Liu, Jinghui Chen, Ximeng Liu, Wenzhong Guo, Yuzhong Chen:
An Unsupervised Detection Approach for Hardware Trojans. IEEE Access 8: 158169-158183 (2020) - [c14]Jinghui Chen, Dongruo Zhou, Jinfeng Yi, Quanquan Gu:
A Frank-Wolfe Framework for Efficient and Effective Adversarial Attacks. AAAI 2020: 3486-3494 - [c13]Xiao Zhang, Jinghui Chen, Quanquan Gu, David Evans:
Understanding the Intrinsic Robustness of Image Distributions using Conditional Generative Models. AISTATS 2020: 3883-3893 - [c12]Jinghui Chen, Dongruo Zhou, Yiqi Tang, Ziyan Yang, Yuan Cao, Quanquan Gu:
Closing the Generalization Gap of Adaptive Gradient Methods in Training Deep Neural Networks. IJCAI 2020: 3267-3275 - [c11]Jinghui Chen, Quanquan Gu:
RayS: A Ray Searching Method for Hard-label Adversarial Attack. KDD 2020: 1739-1747 - [i8]Xiao Zhang, Jinghui Chen, Quanquan Gu, David Evans:
Understanding the Intrinsic Robustness of Image Distributions using Conditional Generative Models. CoRR abs/2003.00378 (2020) - [i7]Jinghui Chen, Quanquan Gu:
RayS: A Ray Searching Method for Hard-label Adversarial Attack. CoRR abs/2006.12792 (2020) - [i6]Jinghui Chen, Yu Cheng, Zhe Gan, Quanquan Gu, Jingjing Liu:
Efficient Robust Training via Backward Smoothing. CoRR abs/2010.01278 (2020) - [i5]Boxi Wu, Jinghui Chen, Deng Cai, Xiaofei He, Quanquan Gu:
Does Network Width Really Help Adversarial Robustness? CoRR abs/2010.01279 (2020)
2010 – 2019
- 2019
- [j2]Jinghui Chen, Chen Dong, Guorong He, Xiaoyu Zhang:
A method for indoor Wi-Fi location based on improved back propagation neural network. Turkish J. Electr. Eng. Comput. Sci. 27(4): 2511-2525 (2019) - [j1]Chen Dong, Jinghui Chen, Wenzhong Guo, Jian Zou:
A machine-learning-based hardware-Trojan detection approach for chips in the Internet of Things. Int. J. Distributed Sens. Networks 15(12) (2019) - 2018
- [c10]Jinghui Chen, Pan Xu, Lingxiao Wang, Jian Ma, Quanquan Gu:
Covariate Adjusted Precision Matrix Estimation via Nonconvex Optimization. ICML 2018: 921-930 - [c9]Jinghui Chen, Micayla Goodrum, Ronald A. Metoyer, Jane Cleland-Huang:
How do practitioners perceive assurance cases in safety-critical software systems? CHASE@ICSE 2018: 57-60 - [c8]Pan Xu, Jinghui Chen, Difan Zou, Quanquan Gu:
Global Convergence of Langevin Dynamics Based Algorithms for Nonconvex Optimization. NeurIPS 2018: 3126-3137 - [i4]Jinghui Chen, Quanquan Gu:
Closing the Generalization Gap of Adaptive Gradient Methods in Training Deep Neural Networks. CoRR abs/1806.06763 (2018) - [i3]Jinghui Chen, Jinfeng Yi, Quanquan Gu:
A Frank-Wolfe Framework for Efficient and Effective Adversarial Attacks. CoRR abs/1811.10828 (2018) - 2017
- [c7]Jinghui Chen, Quanquan Gu:
Fast Newton Hard Thresholding Pursuit for Sparsity Constrained Nonconvex Optimization. KDD 2017: 757-766 - [c6]Jinghui Chen, Saket Sathe, Charu C. Aggarwal, Deepak S. Turaga:
Outlier Detection with Autoencoder Ensembles. SDM 2017: 90-98 - [i2]Jinghui Chen, Lingxiao Wang, Xiao Zhang, Quanquan Gu:
Robust Wirtinger Flow for Phase Retrieval with Arbitrary Corruption. CoRR abs/1704.06256 (2017) - [i1]Pan Xu, Jinghui Chen, Quanquan Gu:
Global Convergence of Langevin Dynamics Based Algorithms for Nonconvex Optimization. CoRR abs/1707.06618 (2017) - 2016
- [c5]Jinghui Chen, Quanquan Gu:
Accelerated Stochastic Block Coordinate Gradient Descent for Sparsity Constrained Nonconvex Optimization. UAI 2016 - 2015
- [c4]Florian Baumann, Jinghui Chen, Karsten Vogt, Bodo Rosenhahn:
Improved Threshold Selection by Using Calibrated Probabilities for Random Forest Classifiers. CRV 2015: 155-160 - 2012
- [c3]Jinghui Chen, Feng Ye, Jinhong Di, Chun Liu, Aidong Men:
Depth map compression via edge-based inpainting. PCS 2012: 57-60 - 2010
- [c2]Xiaoping Li, Jinghui Chen, Yinxing Li, Qiong Xu:
The study of network layer topology discovery algorithm for optimization problem based on SNMP. NCM 2010: 161-163
2000 – 2009
- 2007
- [c1]Xueping Zhang, Fen Qin, Jiayao Wang, Yongheng Fu, Jinghui Chen:
Clustering Spatial Data with Obstacles Constraints by PSO. FSKD (3) 2007: 543-547
Coauthor Index
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