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2020 – today
- 2025
[j2]Jiawei Sun, Ruoxin Chen, Jie Li, Yue Ding, Chentao Wu, Zhi Liu, Junchi Yan:
Understanding and mitigating dimensional collapse of Graph Contrastive Learning: A non-maximum removal approach. Neural Networks 181: 106652 (2025)- [j1]Bowen Li
, Hanlin Gu, Ruoxin Chen, Jie Li, Chentao Wu, Na Ruan, Xueming Si, Lixin Fan:
Temporal Gradient Inversion Attacks With Robust Optimization. IEEE Trans. Dependable Secur. Comput. 22(4): 3383-3397 (2025) - [c6]Weijian Ma, Ruoxin Chen, Ke-Yue Zhang, Shuang Wu, Shouhong Ding:
Instruct Where the Model Fails: Generative Data Augmentation via Guided Self-contrastive Fine-tuning. AAAI 2025: 5991-5999 - [i10]Zheng Yang, Ruoxin Chen, Zhiyuan Yan, Ke-Yue Zhang, Xinghe Fu, Shuang Wu, Xiujun Shu, Taiping Yao, Junchi Yan, Shouhong Ding, Xi Li:
All Patches Matter, More Patches Better: Enhance AI-Generated Image Detection via Panoptic Patch Learning. CoRR abs/2504.01396 (2025) - [i9]Ruoxin Chen, Junwei Xi, Zhiyuan Yan, Ke-Yue Zhang, Shuang Wu, Jingyi Xie, Xu Chen, Lei Xu, Isabel Guan, Taiping Yao, Shouhong Ding:
Dual Data Alignment Makes AI-Generated Image Detector Easier Generalizable. CoRR abs/2505.14359 (2025) - [i8]Kaiqing Lin, Zhiyuan Yan, Ruoxin Chen, Junyan Ye, Ke-Yue Zhang, Yue Zhou, Peng Jin, Bin Li, Taiping Yao, Shouhong Ding:
Seeing Before Reasoning: A Unified Framework for Generalizable and Explainable Fake Image Detection. CoRR abs/2509.25502 (2025) - 2024
- [c5]Jiawei Sun, Kailai Li, Ruoxin Chen, Jie Li, Chentao Wu, Yue Ding, Junchi Yan:
InterpGNN: Understand and Improve Generalization Ability of Transdutive GNNs through the Lens of Interplay between Train and Test Nodes. ICLR 2024 - [i7]Ruoxin Chen, Zhe Wang, Ke-Yue Zhang, Shuang Wu, Jiamu Sun, Shouli Wang, Taiping Yao, Shouhong Ding:
Decoupled Data Augmentation for Improving Image Classification. CoRR abs/2411.02592 (2024) - 2023
- [c4]Kailai Li, Jiawei Sun, Ruoxin Chen, Wei Ding, Kexue Yu, Jie Li, Chentao Wu:
Towards Practical Edge Inference Attacks Against Graph Neural Networks. ICASSP 2023: 1-5 - [i6]Bowen Li, Hanlin Gu, Ruoxin Chen, Jie Li, Chentao Wu, Na Ruan, Xueming Si, Lixin Fan:
Temporal Gradient Inversion Attacks with Robust Optimization. CoRR abs/2306.07883 (2023) - 2022
- [c3]Ruoxin Chen, Jie Li, Junchi Yan, Ping Li, Bin Sheng:
Input-Specific Robustness Certification for Randomized Smoothing. AAAI 2022: 6295-6303 - [c2]Xiang Yu, Ruoxin Chen, Jie Li, Jiawei Sun, Shijing Yuan, Huxiao Ji, Xinyu Lu, Chentao Wu:
Zero-Shot Scene Graph Generation with Knowledge Graph Completion. ICME 2022: 1-6 - [c1]Ruoxin Chen, Zenan Li, Jie Li, Junchi Yan, Chentao Wu:
On Collective Robustness of Bagging Against Data Poisoning. ICML 2022: 3299-3319 - [i5]Jiawei Sun, Junchi Yan, Chentao Wu, Yue Ding, Ruoxin Chen, Xiang Yu, Xinyu Lu, Jie Li:
GraphCoCo: Graph Complementary Contrastive Learning. CoRR abs/2203.12821 (2022) - [i4]Ruoxin Chen, Zenan Li, Jie Li, Chentao Wu, Junchi Yan:
On Collective Robustness of Bagging Against Data Poisoning. CoRR abs/2205.13176 (2022) - 2021
- [i3]Ruoxin Chen, Jie Li, Junchi Yan, Ping Li, Bin Sheng:
Input-Specific Robustness Certification for Randomized Smoothing. CoRR abs/2112.12084 (2021) - 2020
- [i2]Ruoxin Chen, Jie Li, Chentao Wu, Bin Sheng, Ping Li:
A Framework of Randomized Selection Based Certified Defenses Against Data Poisoning Attacks. CoRR abs/2009.08739 (2020) - [i1]Yi Gu, Yuting Gao, Ruoxin Chen, Feiyang Cai, Jie Li, Chentao Wu:
Association: Remind Your GAN not to Forget. CoRR abs/2011.13553 (2020)
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