Jie Ren

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 24

Top Topics

Pure Nash Equilibrium

Rational Agents

Visual Concepts

Question Answering

Top Venues

Publications

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)
Jie Ren, Zhanpeng Zhou, Qirui Chen, Quanshi Zhang
Can We Faithfully Represent Absence States to Compute Shapley Values on a DNN? ICLR (2023)
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)
Xu Cheng, Hao Zhang, Yue Xin, Wen Shen, Jie Ren, Quanshi Zhang
Why Adversarial Training of ReLU Networks Is Difficult? CoRR (2022)
Jie Ren, Mingjie Li, Meng Zhou, Shih-Han Chan, Quanshi Zhang
Towards Theoretical Analysis of Transformation Complexity of ReLU DNNs. ICML (2022)
Jie Ren, Mingjie Li, Meng Zhou, Shih-Han Chan, Quanshi Zhang
Towards Theoretical Analysis of Transformation Complexity of ReLU DNNs. CoRR (2022)
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)
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)
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)
Huiqi Deng, Qihan Ren, Xu Chen, Hao Zhang, Jie Ren, Quanshi Zhang
Discovering and Explaining the Representation Bottleneck of DNNs. CoRR (2021)
Jie Ren, Mingjie Li, Qirui Chen, Huiqi Deng, Quanshi Zhang
Towards Axiomatic, Hierarchical, and Symbolic Explanation for Deep Models. CoRR (2021)
Dongrui Liu, Shaobo Wang, Jie Ren, Kangrui Wang, Sheng Yin, Quanshi Zhang
Trap of Feature Diversity in the Learning of MLPs. 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)
Liyao Xiang, Hao Zhang, Haotian Ma, Yifan Zhang, Jie Ren, Quanshi Zhang
Interpretable Complex-Valued Neural Networks for Privacy Protection. ICLR (2020)
Jie Ren, Mingjie Li, Zexu Liu, Quanshi Zhang
Interpreting and Disentangling Feature Components of Various Complexity from DNNs. CoRR (2020)
Xin Wang, Jie Ren, Shuyun Lin, Xiangming Zhu, Yisen Wang, Quanshi Zhang
A Unified Approach to Interpreting and Boosting Adversarial Transferability. CoRR (2020)
Runjin Chen, Hao Chen, Ge Huang, Jie Ren, Quanshi Zhang
Explaining Neural Networks Semantically and Quantitatively. ICCV (2019)
Runjin Chen, Hao Chen, Ge Huang, Jie Ren, Quanshi Zhang
Explaining Neural Networks Semantically and Quantitatively. CoRR (2018)