← Authors

Quanshi Zhang

48 papers · 2013–2025 · 11 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge 🧭 Keyword Pioneer 🌍 Conference Polyglot (11) πŸƒ Academic Marathon (12) 🐝 Cross-Pollinator (10) 🌈 Renaissance Researcher (8) πŸ—ΊοΈ Taxonomy Completionist (61) πŸ‘‘ Triple Crown πŸ† Keyword Champion (12) 🀝 Dynamic Duo (10) πŸ”¬ Deep Specialist (18) 🧬 Topic Evolution πŸ† Grand Slam πŸ“ˆ Trend Setter πŸ’Ž Century Club (48) πŸ”₯ Unstoppable (9) πŸ—ƒοΈ Keyword Collector (169) ❓ The Questioner (2) ⚑ Prolific Year (11) πŸš€ Conference Pioneer

Conferences

ICML (10) CVPR (9) ICLR (8) AAAI (7) NIPS (5) ICCV (4) ACL (1) AISTATS (1) ECCV (1) EMNLP (1) IJCAI (1)

Top co-authors

Jie Ren (10) Wen Shen (9) Hao Zhang (9) Huiqi Deng (6) Qihan Ren (6) Xu Cheng (6) Mingjie Li (6) Ying Nian Wu (5) Dongrui Liu (5) Xuan Song (4)

Keywords

deep neural network (12) convolutional neural network (6) feature learning (5) feature representation (4) shapley value (4) neural network optimization (3) model interpretability (3) graph matching (3) object part (3) neural network (3) neural network interpretability (3) feature attribution (3) category modeling (3) knowledge distillation (3) graphical model (3) and-or graph (3) representation capacity (3) game theory (2) neural network interpretation (2) adversarial robustness (2)

Papers

Towards Attributions of Input Variables in a Coalition ICML 2025
Monitoring Primitive Interactions During the Training of DNNs AAAI 2025
Where We Have Arrived in Proving the Emergence of Sparse Interaction Primitives in DNNs ICLR 2024
Layerwise Change of Knowledge in Neural Networks ICML 2024
Towards the Dynamics of a DNN Learning Symbolic Interactions NIPS 2024
Identifying Semantic Induction Heads to Understand In-Context Learning ACL 2024
Clarifying the Behavior and the Difficulty of Adversarial Training AAAI 2024
Batch Normalization Is Blind to the First and Second Derivatives of the Loss AAAI 2024
Explaining Generalization Power of a DNN Using Interactive Concepts AAAI 2024
Defining and extracting generalizable interaction primitives from DNNs ICLR 2024
Defining and Quantifying the Emergence of Sparse Concepts in DNNs CVPR 2023
Can We Faithfully Represent Absence States to Compute Shapley Values on a DNN? ICLR 2023
Defects of Convolutional Decoder Networks in Frequency Representation ICML 2023
Bayesian Neural Networks Avoid Encoding Complex and Perturbation-Sensitive Concepts ICML 2023
Does a Neural Network Really Encode Symbolic Concepts? ICML 2023
HarsanyiNet: Computing Accurate Shapley Values in a Single Forward Propagation ICML 2023
Towards the Difficulty for a Deep Neural Network to Learn Concepts of Different Complexities NIPS 2023
Quantification and Analysis of Layer-wise and Pixel-wise Information Discarding ICML 2022
Interpretable Generative Adversarial Networks AAAI 2022
Exploring Image Regions Not Well Encoded by an INN AISTATS 2022
DISCOVERING AND EXPLAINING THE REPRESENTATION BOTTLENECK OF DNNS ICLR 2022
RASAT: Integrating Relational Structures into Pretrained Seq2Seq Model for Text-to-SQL EMNLP 2022
Towards Theoretical Analysis of Transformation Complexity of ReLU DNNs ICML 2022
Building Interpretable Interaction Trees for Deep NLP Models AAAI 2021
Visualizing the Emergence of Intermediate Visual Patterns in DNNs NIPS 2021
Interpreting Representation Quality of DNNs for 3D Point Cloud Processing NIPS 2021
Interpreting Multivariate Shapley Interactions in DNNs AAAI 2021
Towards a Unified Game-Theoretic View of Adversarial Perturbations and Robustness NIPS 2021
Verifiability and Predictability: Interpreting Utilities of Network Architectures for Point Cloud Processing CVPR 2021
Interpreting Attributions and Interactions of Adversarial Attacks ICCV 2021
Interpreting and Boosting Dropout from a Game-Theoretic View ICLR 2021
A Unified Approach to Interpreting and Boosting Adversarial Transferability ICLR 2021
Interpreting and Disentangling Feature Components of Various Complexity from DNNs ICML 2021
Interpretable Compositional Convolutional Neural Networks IJCAI 2021
Explaining Knowledge Distillation by Quantifying the Knowledge CVPR 2020
3D-Rotation-Equivariant Quaternion Neural Networks ECCV 2020
Knowledge Consistency between Neural Networks and Beyond ICLR 2020
Interpretable Complex-Valued Neural Networks for Privacy Protection ICLR 2020
Interpreting CNNs via Decision Trees CVPR 2019
Towards a Deep and Unified Understanding of Deep Neural Models in NLP ICML 2019
Explaining Neural Networks Semantically and Quantitatively ICCV 2019
Interpretable Convolutional Neural Networks CVPR 2018
Mining Object Parts From CNNs via Active Question-Answering CVPR 2017
Mining And-Or Graphs for Graph Matching and Object Discovery ICCV 2015
When 3D Reconstruction Meets Ubiquitous RGB-D Images CVPR 2014
Attributed Graph Mining and Matching: An Attempt to Define and Extract Soft Attributed Patterns CVPR 2014
Learning Graph Matching: Oriented to Category Modeling from Cluttered Scenes ICCV 2013
Category Modeling from Just a Single Labeling: Use Depth Information to Guide the Learning of 2D Models CVPR 2013