Xu Cheng - RankMe

21 papers A* 6Journal 14Unranked 1

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Interpretable Rotation-Equivariant Multiary-Valued Network for Attribute Obfuscation. IEEE Trans. Pattern Anal. Mach. Intell. Quanshi Zhang, Hao Zhang, Yiting Chen, Qihan Ren, Jie Ren, Xu Cheng, Liyao Xiang
2024	A*	`conf`	Clarifying the Behavior and the Difficulty of Adversarial Training. AAAI Xu Cheng, Hao Zhang, Yue Xin, Wen Shen, Quanshi Zhang
2024	J	`jnl`	Interpretability of Neural Networks Based on Game-theoretic Interactions. Mach. Intell. Res. Huilin Zhou, Jie Ren, Huiqi Deng, Xu Cheng, Jinpeng Zhang, Quanshi Zhang
2024	A*	`conf`	Layerwise Change of Knowledge in Neural Networks. ICML Xu Cheng, Lei Cheng, Zhaoran Peng, Yang Xu, Tian Han, Quanshi Zhang
2024	J	`jnl`	Layerwise Change of Knowledge in Neural Networks. CoRR Xu Cheng, Lei Cheng, Zhaoran Peng, Yang Xu, Tian Han, Quanshi Zhang
2023	—	`conf`	Network Transplanting for the Functionally Modular Architecture. PRCV (3) Quanshi Zhang, Xu Cheng, Xin Wang, Yu Yang, Yingnian Wu
2023	J	`jnl`	Quantifying the Knowledge in a DNN to Explain Knowledge Distillation for Classification. IEEE Trans. Pattern Anal. Mach. Intell. Quanshi Zhang, Xu Cheng, Yilan Chen, Zhefan Rao
2023	A*	`conf`	Towards the Difficulty for a Deep Neural Network to Learn Concepts of Different Complexities. NeurIPS Dongrui Liu, Huiqi Deng, Xu Cheng, Qihan Ren, Kangrui Wang, Quanshi Zhang
2022	J	`jnl`	Proving Common Mechanisms Shared by Twelve Methods of Boosting Adversarial Transferability. CoRR Quanshi Zhang, Xin Wang, Jie Ren, Xu Cheng, Shuyun Lin, Yisen Wang, Xiangming Zhu
2022	J	`jnl`	Quantifying the Knowledge in a DNN to Explain Knowledge Distillation for Classification. CoRR Quanshi Zhang, Xu Cheng, Yilan Chen, Zhefan Rao
2022	J	`jnl`	Why Adversarial Training of ReLU Networks Is Difficult? CoRR Xu Cheng, Hao Zhang, Yue Xin, Wen Shen, Jie Ren, Quanshi Zhang
2021	J	`jnl`	A Game-Theoretic Taxonomy of Visual Concepts in DNNs. CoRR Xu Cheng, Chuntung Chu, Yi Zheng, Jie Ren, Quanshi Zhang
2021	J	`jnl`	A Hypothesis for the Aesthetic Appreciation in Neural Networks. CoRR Xu Cheng, Xin Wang, Haotian Xue, Zhengyang Liang, Quanshi Zhang
2021	A*	`conf`	Building Interpretable Interaction Trees for Deep NLP Models. AAAI Die Zhang, Hao Zhang, Huilin Zhou, Xiaoyi Bao, Da Huo, Ruizhao Chen, Xu Cheng, Mengyue Wu, Quanshi Zhang
2021	J	`jnl`	Game-theoretic Understanding of Adversarially Learned Features. CoRR Jie Ren, Die Zhang, Yisen Wang, Lu Chen, Zhanpeng Zhou, Xu Cheng, Xin Wang, Yiting Chen, Jie Shi, Quanshi Zhang
2021	A*	`conf`	Towards a Unified Game-Theoretic View of Adversarial Perturbations and Robustness. NeurIPS Jie Ren, Die Zhang, Yisen Wang, Lu Chen, Zhanpeng Zhou, Yiting Chen, Xu Cheng, Xin Wang, Meng Zhou, Jie Shi, Quanshi Zhang
2020	A*	`conf`	Explaining Knowledge Distillation by Quantifying the Knowledge. CVPR Xu Cheng, Zhefan Rao, Yilan Chen, Quanshi Zhang
2020	J	`jnl`	Explaining Knowledge Distillation by Quantifying the Knowledge. CoRR Xu Cheng, Zhefan Rao, Yilan Chen, Quanshi Zhang
2020	J	`jnl`	Game-Theoretic Interactions of Different Orders. CoRR Hao Zhang, Xu Cheng, Yiting Chen, Quanshi Zhang
2020	J	`jnl`	Interpreting Hierarchical Linguistic Interactions in DNNs. CoRR Die Zhang, Huilin Zhou, Xiaoyi Bao, Da Huo, Ruizhao Chen, Xu Cheng, Hao Zhang, Mengyue Wu, Quanshi Zhang
2020	J	`jnl`	Rotation-Equivariant Neural Networks for Privacy Protection. CoRR Hao Zhang, Yiting Chen, Haotian Ma, Xu Cheng, Qihan Ren, Liyao Xiang, Jie Shi, Quanshi Zhang