Quanshi Zhang

ORCID

Publication Activity (10 Years)

Years Active: 2009-2024
Publications (10 Years): 131

Top Venues

Publications

Liyao Xiang, Shuang Zhang, Quanshi Zhang
Learning to Prevent Input Leakages in the Mobile Cloud Inference. IEEE Trans. Mob. Comput. 23 (7) (2024)
Junpeng Zhang, Qing Li, Liang Lin, Quanshi Zhang
Two-Phase Dynamics of Interactions Explains the Starting Point of a DNN Learning Over-Fitted Features. CoRR (2024)
Huiqi Deng, Na Zou, Mengnan Du, Weifu Chen, Guocan Feng, Ziwei Yang, Zheyang Li, Quanshi Zhang
Unifying Fourteen Post-Hoc Attribution Methods With Taylor Interactions. IEEE Trans. Pattern Anal. Mach. Intell. 46 (7) (2024)
Siyu Lou, Yuntian Chen, Xiaodan Liang, Liang Lin, Quanshi Zhang
Quantifying In-Context Reasoning Effects and Memorization Effects in LLMs. CoRR (2024)
Huilin Zhou, Hao Zhang, Huiqi Deng, Dongrui Liu, Wen Shen, Shih-Han Chan, Quanshi Zhang
Explaining Generalization Power of a DNN Using Interactive Concepts. AAAI (2024)
Zhanpeng Zhou, Wen Shen, Huixin Chen, Ling Tang, Yuefeng Chen, Quanshi Zhang
Batch Normalization Is Blind to the First and Second Derivatives of the Loss. AAAI (2024)
Jie Ren, Qipeng Guo, Hang Yan, Dongrui Liu, Quanshi Zhang, Xipeng Qiu, Dahua Lin
Identifying Semantic Induction Heads to Understand In-Context Learning. ACL (Findings) (2024)
Huilin Zhou, Jie Ren, Huiqi Deng, Xu Cheng, Jinpeng Zhang, Quanshi Zhang
Interpretability of Neural Networks Based on Game-theoretic Interactions. Mach. Intell. Res. 21 (4) (2024)
Lu Chen, Siyu Lou, Benhao Huang, Quanshi Zhang
Defining and Extracting generalizable interaction primitives from DNNs. CoRR (2024)
Xu Cheng, Hao Zhang, Yue Xin, Wen Shen, Quanshi Zhang
Clarifying the Behavior and the Difficulty of Adversarial Training. AAAI (2024)
Jinghui Qin, Zhongzhan Huang, Ying Zeng, Quanshi Zhang, Liang Lin
An Introspective Data Augmentation Method for Training Math Word Problem Solvers. IEEE ACM Trans. Audio Speech Lang. Process. 32 (2024)
Qihan Ren, Jiayang Gao, Wen Shen, Quanshi Zhang
Where We Have Arrived in Proving the Emergence of Sparse Interaction Primitives in DNNs. ICLR (2024)
Qihan Ren, Yang Xu, Junpeng Zhang, Yue Xin, Dongrui Liu, Quanshi Zhang
Towards the Dynamics of a DNN Learning Symbolic Interactions. CoRR (2024)
Wen Shen, Zhihua Wei, Qihan Ren, Binbin Zhang, Shikun Huang, Jiaqi Fan, Quanshi Zhang
Interpretable Rotation-Equivariant Quaternion Neural Networks for 3D Point Cloud Processing. IEEE Trans. Pattern Anal. Mach. Intell. 46 (5) (2024)
Lu Chen, Siyu Lou, Benhao Huang, Quanshi Zhang
Defining and extracting generalizable interaction primitives from DNNs. ICLR (2024)
Dongrui Liu, Huiqi Deng, Xu Cheng, Qihan Ren, Kangrui Wang, Quanshi Zhang
Towards the Difficulty for a Deep Neural Network to Learn Concepts of Different Complexities. NeurIPS (2023)
Wen Shen, Lei Cheng, Yuxiao Yang, Mingjie Li, Quanshi Zhang
Can the Inference Logic of Large Language Models be Disentangled into Symbolic Concepts? CoRR (2023)
Huilin Zhou, Hao Zhang, Huiqi Deng, Dongrui Liu, Wen Shen, Shih-Han Chan, Quanshi Zhang
Concept-Level Explanation for the Generalization of a DNN. CoRR (2023)
Ling Tang, Wen Shen, Zhanpeng Zhou, Yuefeng Chen, Quanshi Zhang
Defects of Convolutional Decoder Networks in Frequency Representation. ICML (2023)
Huilin Zhou, Huijie Tang, Mingjie Li, Hao Zhang, Zhenyu Liu, Quanshi Zhang
Explaining How a Neural Network Play the Go Game and Let People Learn. CoRR (2023)
Qihan Ren, Jiayang Gao, Wen Shen, Quanshi Zhang
Where We Have Arrived in Proving the Emergence of Sparse Symbolic Concepts in AI Models. CoRR (2023)
Xinhao Zheng, Huiqi Deng, Quanshi Zhang
Towards Attributions of Input Variables in a Coalition. CoRR (2023)
Qihan Ren, Huiqi Deng, Yunuo Chen, Siyu Lou, Quanshi Zhang
Bayesian Neural Networks Tend to Ignore Complex and Sensitive Concepts. CoRR (2023)
Qihan Ren, Huiqi Deng, Yunuo Chen, Siyu Lou, Quanshi Zhang
Bayesian Neural Networks Avoid Encoding Complex and Perturbation-Sensitive Concepts. ICML (2023)
Mingjie Li, Quanshi Zhang
Does a Neural Network Really Encode Symbolic Concept? CoRR (2023)
Quanshi Zhang, Xu Cheng, Yilan Chen, Zhefan Rao
Quantifying the Knowledge in a DNN to Explain Knowledge Distillation for Classification. IEEE Trans. Pattern Anal. Mach. Intell. 45 (4) (2023)
Lu Chen, Siyu Lou, Keyan Zhang, Jin Huang, Quanshi Zhang
HarsanyiNet: Computing Accurate Shapley Values in a Single Forward Propagation. ICML (2023)
Huiqi Deng, Na Zou, Mengnan Du, Weifu Chen, Guocan Feng, Ziwei Yang, Zheyang Li, Quanshi Zhang
Understanding and Unifying Fourteen Attribution Methods with Taylor Interactions. CoRR (2023)
Quanshi Zhang, Xu Cheng, Xin Wang, Yu Yang, Yingnian Wu
Network Transplanting for the Functionally Modular Architecture. PRCV (3) (2023)
Lu Chen, Siyu Lou, Keyan Zhang, Jin Huang, Quanshi Zhang
HarsanyiNet: Computing Accurate Shapley Values in a Single Forward Propagation. CoRR (2023)
Jie Ren, Mingjie Li, Qirui Chen, Huiqi Deng, Quanshi Zhang
Defining and Quantifying the Emergence of Sparse Concepts in DNNs. CVPR (2023)
Mingjie Li, Quanshi Zhang
Does a Neural Network Really Encode Symbolic Concepts? ICML (2023)
Jie Ren, Zhanpeng Zhou, Qirui Chen, Quanshi Zhang
Can We Faithfully Represent Absence States to Compute Shapley Values on a DNN? ICLR (2023)
Mingjie Li, Quanshi Zhang
Technical Note: Defining and Quantifying AND-OR Interactions for Faithful and Concise Explanation of DNNs. CoRR (2023)
Jiexing Qi, Jingyao Tang, Ziwei He, Xiangpeng Wan, Yu Cheng, Chenghu Zhou, Xinbing Wang, Quanshi Zhang, Zhouhan Lin
RASAT: Integrating Relational Structures into Pretrained Seq2Seq Model for Text-to-SQL. EMNLP (2022)
Jiexing Qi, Jingyao Tang, Ziwei He, Xiangpeng Wan, Chenghu Zhou, Xinbing Wang, Quanshi Zhang, Zhouhan Lin
RASAT: Integrating Relational Structures into Pretrained Seq2Seq Model for Text-to-SQL. CoRR (2022)
Quanshi Zhang, Xu Cheng, Yilan Chen, Zhefan Rao
Quantifying the Knowledge in a DNN to Explain Knowledge Distillation for Classification. CoRR (2022)
Quanshi Zhang, Xin Wang, Jie Ren, Xu Cheng, Shuyun Lin, Yisen Wang, Xiangming Zhu
Proving Common Mechanisms Shared by Twelve Methods of Boosting Adversarial Transferability. CoRR (2022)
Huiqi Deng, Qihan Ren, Hao Zhang, Quanshi Zhang
Discovering and Explaining the Representation Bottleneck of DNNS. ICLR (2022)
Xu Cheng, Hao Zhang, Yue Xin, Wen Shen, Jie Ren, Quanshi Zhang
Why Adversarial Training of ReLU Networks Is Difficult? CoRR (2022)
Ling Tang, Wen Shen, Zhanpeng Zhou, Yuefeng Chen, Quanshi Zhang
Defects of Convolutional Decoder Networks in Frequency Representation. CoRR (2022)
Yuxiang Wu, Shang Wu, Xin Wang, Chengtian Lang, Quanshi Zhang, Quan Wen, Tianqi Xu
Rapid detection and recognition of whole brain activity in a freely behaving Caenorhabditis elegans. PLoS Comput. Biol. 18 (10) (2022)
Haotian Ma, Hao Zhang, Fan Zhou, Yinqing Zhang, Quanshi Zhang
Quantification and Analysis of Layer-wise and Pixel-wise Information Discarding. ICML (2022)
Jie Ren, Mingjie Li, Meng Zhou, Shih-Han Chan, Quanshi Zhang
Towards Theoretical Analysis of Transformation Complexity of ReLU DNNs. ICML (2022)
Chao Li, Kelu Yao, Jin Wang, Boyu Diao, Yongjun Xu, Quanshi Zhang
Interpretable Generative Adversarial Networks. AAAI (2022)
Jie Ren, Mingjie Li, Meng Zhou, Shih-Han Chan, Quanshi Zhang
Towards Theoretical Analysis of Transformation Complexity of ReLU DNNs. CoRR (2022)
Zhanpeng Zhou, Wen Shen, Huixin Chen, Ling Tang, Quanshi Zhang
Batch Normalization Is Blind to the First and Second Derivatives of the Loss. CoRR (2022)
Zenan Ling, Fan Zhou, Meng Wei, Quanshi Zhang
Exploring Image Regions Not Well Encoded by an INN. AISTATS (2022)
Mingjie Li, Shaobo Wang, Quanshi Zhang
Visualizing the Emergence of Intermediate Visual Patterns in DNNs. CoRR (2021)
Hao Zhang, Sen Li, Yinchao Ma, Mingjie Li, Yichen Xie, Quanshi Zhang
Interpreting and Boosting Dropout from a Game-Theoretic View. ICLR (2021)
Yuxiang Wu, Shang Wu, Xin Wang, Chengtian Lang, Quanshi Zhang, Quan Wen, Tianqi Xu
Rapid detection and recognition of whole brain activity in a freely behaving Caenorhabditis elegans. CoRR (2021)
Jie Ren, Die Zhang, Yisen Wang, Lu Chen, Zhanpeng Zhou, Yiting Chen, Xu Cheng, Xin Wang, Meng Zhou, Jie Shi, Quanshi Zhang
Towards a Unified Game-Theoretic View of Adversarial Perturbations and Robustness. NeurIPS (2021)
Quanshi Zhang, Tian Han, Lixin Fan, Zhanxing Zhu, Hang Su, Ying Nian Wu, Jie Ren, Hao Zhang
Proceedings of ICML 2021 Workshop on Theoretic Foundation, Criticism, and Application Trend of Explainable AI. CoRR (2021)
Jie Ren, Zhanpeng Zhou, Qirui Chen, Quanshi Zhang
Learning Baseline Values for Shapley Values. CoRR (2021)
Wen Shen, Qihan Ren, Dongrui Liu, Quanshi Zhang
Interpreting Representation Quality of DNNs for 3D Point Cloud Processing. NeurIPS (2021)
Jie Ren, Die Zhang, Yisen Wang, Lu Chen, Zhanpeng Zhou, Xu Cheng, Xin Wang, Yiting Chen, Jie Shi, Quanshi Zhang
Game-theoretic Understanding of Adversarially Learned Features. CoRR (2021)
Xu Cheng, Xin Wang, Haotian Xue, Zhengyang Liang, Quanshi Zhang
A Hypothesis for the Aesthetic Appreciation in Neural Networks. CoRR (2021)
Quanshi Zhang, Jie Ren, Ge Huang, Ruiming Cao, Ying Nian Wu, Song-Chun Zhu
Mining Interpretable AOG Representations From Convolutional Networks via Active Question Answering. IEEE Trans. Pattern Anal. Mach. Intell. 43 (11) (2021)
Xin Wang, Jie Ren, Shuyun Lin, Xiangming Zhu, Yisen Wang, Quanshi Zhang
A Unified Approach to Interpreting and Boosting Adversarial Transferability. ICLR (2021)
Jie Ren, Mingjie Li, Zexu Liu, Quanshi Zhang
Interpreting and Disentangling Feature Components of Various Complexity from DNNs. ICML (2021)
Xu Cheng, Chuntung Chu, Yi Zheng, Jie Ren, Quanshi Zhang
A Game-Theoretic Taxonomy of Visual Concepts in DNNs. CoRR (2021)
Wen Shen, Qihan Ren, Dongrui Liu, Quanshi Zhang
Interpreting Representation Quality of DNNs for 3D Point Cloud Processing. CoRR (2021)
Huiqi Deng, Qihan Ren, Xu Chen, Hao Zhang, Jie Ren, Quanshi Zhang
Discovering and Explaining the Representation Bottleneck of DNNs. CoRR (2021)
Quanshi Zhang, Xin Wang, Ying Nian Wu, Huilin Zhou, Song-Chun Zhu
Interpretable CNNs for Object Classification. IEEE Trans. Pattern Anal. Mach. Intell. 43 (10) (2021)
Hao Zhang, Yichen Xie, Longjie Zheng, Die Zhang, Quanshi Zhang
Interpreting Multivariate Shapley Interactions in DNNs. AAAI (2021)
Jie Ren, Mingjie Li, Qirui Chen, Huiqi Deng, Quanshi Zhang
Towards Axiomatic, Hierarchical, and Symbolic Explanation for Deep Models. CoRR (2021)
Mingjie Li, Shaobo Wang, Quanshi Zhang
Visualizing the Emergence of Intermediate Visual Patterns in DNNs. NeurIPS (2021)
Die Zhang, Hao Zhang, Huilin Zhou, Xiaoyi Bao, Da Huo, Ruizhao Chen, Xu Cheng, Mengyue Wu, Quanshi Zhang
Building Interpretable Interaction Trees for Deep NLP Models. AAAI (2021)
Quanshi Zhang, Xin Wang, Ruiming Cao, Ying Nian Wu, Feng Shi, Song-Chun Zhu
Extraction of an Explanatory Graph to Interpret a CNN. IEEE Trans. Pattern Anal. Mach. Intell. 43 (11) (2021)
Xin Wang, Shuyun Lin, Hao Zhang, Yufei Zhu, Quanshi Zhang
Interpreting Attributions and Interactions of Adversarial Attacks. CoRR (2021)
Wen Shen, Zhihua Wei, Shikun Huang, Binbin Zhang, Jiaqi Fan, Ping Zhao, Quanshi Zhang
Interpretable Compositional Convolutional Neural Networks. IJCAI (2021)
Xin Wang, Shuyun Lin, Hao Zhang, Yufei Zhu, Quanshi Zhang
Interpreting Attributions and Interactions of Adversarial Attacks. ICCV (2021)
Dongrui Liu, Shaobo Wang, Jie Ren, Kangrui Wang, Sheng Yin, Quanshi Zhang
Trap of Feature Diversity in the Learning of MLPs. CoRR (2021)
Wen Shen, Zhihua Wei, Shikun Huang, Binbin Zhang, Panyue Chen, Ping Zhao, Quanshi Zhang
Verifiability and Predictability: Interpreting Utilities of Network Architectures for Point Cloud Processing. CVPR (2021)
Wen Shen, Zhihua Wei, Shikun Huang, Binbin Zhang, Jiaqi Fan, Ping Zhao, Quanshi Zhang
Interpretable Compositional Convolutional Neural Networks. CoRR (2021)
Jie Ren, Die Zhang, Yisen Wang, Lu Chen, Zhanpeng Zhou, Yiting Chen, Xu Cheng, Xin Wang, Meng Zhou, Jie Shi, Quanshi Zhang
A Unified Game-Theoretic Interpretation of Adversarial Robustness. CoRR (2021)
Hao Zhang, Yiting Chen, Liyao Xiang, Haotian Ma, Jie Shi, Quanshi Zhang
Deep Quaternion Features for Privacy Protection. CoRR (2020)
Die Zhang, Huilin Zhou, Xiaoyi Bao, Da Huo, Ruizhao Chen, Xu Cheng, Hao Zhang, Mengyue Wu, Quanshi Zhang
Interpreting Hierarchical Linguistic Interactions in DNNs. CoRR (2020)
Hao Zhang, Yiting Chen, Haotian Ma, Xu Cheng, Qihan Ren, Liyao Xiang, Jie Shi, Quanshi Zhang
Rotation-Equivariant Neural Networks for Privacy Protection. CoRR (2020)
Shufan Wang, Ningyi Liao, Liyao Xiang, Nanyang Ye, Quanshi Zhang
Achieving Adversarial Robustness via Sparsity. CoRR (2020)
Hao Zhang, Sen Li, Yinchao Ma, Mingjie Li, Yichen Xie, Quanshi Zhang
Interpreting and Boosting Dropout from a Game-Theoretic View. CoRR (2020)
Hao Zhang, Yichen Xie, Longjie Zheng, Die Zhang, Quanshi Zhang
Interpreting Multivariate Interactions in DNNs. CoRR (2020)
Xu Cheng, Zhefan Rao, Yilan Chen, Quanshi Zhang
Explaining Knowledge Distillation by Quantifying the Knowledge. CoRR (2020)
Xu Cheng, Zhefan Rao, Yilan Chen, Quanshi Zhang
Explaining Knowledge Distillation by Quantifying the Knowledge. CVPR (2020)
Liyao Xiang, Hao Zhang, Haotian Ma, Yifan Zhang, Jie Ren, Quanshi Zhang
Interpretable Complex-Valued Neural Networks for Privacy Protection. ICLR (2020)
Hao Zhang, Xu Cheng, Yiting Chen, Quanshi Zhang
Game-Theoretic Interactions of Different Orders. CoRR (2020)
Jie Ren, Mingjie Li, Zexu Liu, Quanshi Zhang
Interpreting and Disentangling Feature Components of Various Complexity from DNNs. CoRR (2020)
Wen Shen, Binbin Zhang, Shikun Huang, Zhihua Wei, Quanshi Zhang
3D-Rotation-Equivariant Quaternion Neural Networks. ECCV (20) (2020)
Ruofan Liang, Tianlin Li, Longfei Li, Jing Wang, Quanshi Zhang
Knowledge Consistency between Neural Networks and Beyond. ICLR (2020)
Xin Wang, Jie Ren, Shuyun Lin, Xiangming Zhu, Yisen Wang, Quanshi Zhang
A Unified Approach to Interpreting and Boosting Adversarial Transferability. CoRR (2020)
Hao Zhang, Jiayi Chen, Haotian Xue, Quanshi Zhang
Towards a Unified Evaluation of Explanation Methods without Ground Truth. CoRR (2019)
Haotian Ma, Yinqing Zhang, Fan Zhou, Quanshi Zhang
Quantifying Layerwise Information Discarding of Neural Networks. CoRR (2019)
Shuang Zhang, Liyao Xiang, Congcong Li, Yixuan Wang, Zeyu Liu, Quanshi Zhang, Bo Li
Preventing Information Leakage with Neural Architecture Search. CoRR (2019)
Quanshi Zhang, Yu Yang, Qian Yu, Ying Nian Wu
Network Transplanting (extended abstract). CoRR (2019)
Quanshi Zhang, Ying Nian Wu, Song-Chun Zhu
Interpretable CNNs. CoRR (2019)
Quanshi Zhang, Xuan Song, Yu Yang, Haotian Ma, Ryosuke Shibasaki
Visual graph mining for graph matching. Comput. Vis. Image Underst. 178 (2019)
Guy Barash, Mauricio Castillo-Effen, Niyati Chhaya, Peter Clark, Huáscar Espinoza, Eitan Farchi, Christopher W. Geib, Odd Erik Gundersen, Seán Ó hÉigeartaigh, José Hernández-Orallo, Chiori Hori, Xiaowei Huang, Kokil Jaidka, Pavan Kapanipathi, Sarah Keren, Seokhwan Kim, Marc Lanctot, Danny Lange, Julian J. McAuley, David R. Martinez, Marwan Mattar, Mausam, Martin Michalowski, Reuth Mirsky, Roozbeh Mottaghi, Joseph C. Osborn, Julien Pérolat, Martin Schmid, Arash Shaban-Nejad, Onn Shehory, Biplav Srivastava, William W. Streilein, Kartik Talamadupula, Julian Togelius, Koichiro Yoshino, Quanshi Zhang, Imed Zitouni
Reports of the Workshops Held at the 2019 AAAI Conference on Artificial Intelligence. AI Mag. 40 (3) (2019)
Chaoyu Guan, Xiting Wang, Quanshi Zhang, Runjin Chen, Di He, Xing Xie
Towards a Deep and Unified Understanding of Deep Neural Models in NLP. ICML (2019)
Quanshi Zhang, Yu Yang, Ying Nian Wu
Unsupervised Learning of Neural Networks to Explain Neural Networks (extended abstract). CoRR (2019)
Shikun Huang, Binbin Zhang, Wen Shen, Zhihua Wei, Quanshi Zhang
Utility Analysis of Network Architectures for 3D Point Cloud Processing. CoRR (2019)

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Publication Activity (10 Years)

Top Topics

Top Venues

Quanshi Zhang