Wang, Zhangyang

Adversarial Robustness: From Self-Supervised Pre-Training to Fine-Tuning

Chen, T., Liu, S., Chang, S., Cheng, Y., Amini, L., & Wang, Z. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Adversarial Robustness in Machine LearningMachine Learning and Data Classification

Cited by 205

Chasing Sparsity in Vision Transformers: An End-to-End Exploration

Chen, T., Cheng, Y., Gan, Z., Yuan, L., Zhang, L., & Wang, Z. (2021) · arXiv

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 111

Auto-ViT-Acc: An FPGA-Aware Automatic Acceleration Framework for Vision Transformer with Mixed-Scheme Quantization

Li, Z., Sun, M., Lu, A., Ma, H., Yuan, G., Xie, Y., Tang, H., Li, Y., Leeser, M., Wang, Z., et al. (2022) · 2022 32nd International Conference on Field-Programmable Logic and Applications (FPL)

Advanced Neural Network ApplicationsEmbedded Systems Design Techniques

Cited by 85

Anti-Oversmoothing in Deep Vision Transformers via the Fourier Domain Analysis: From Theory to Practice

Wang, P., Zheng, W., Chen, T., & Wang, Z. (2022) · arXiv

Advanced Neural Network ApplicationsVisual Attention and Saliency Detection

Cited by 80

IA-RED$^2$: Interpretability-Aware Redundancy Reduction for Vision Transformers

Pan, B., Panda, R., Jiang, Y., Wang, Z., Feris, R., & Oliva, A. (2021) · arXiv

Advanced Neural Network ApplicationsExplainable Artificial Intelligence (XAI)

Cited by 70

Explainable Deep Relational Networks for Predicting Compound-Protein Affinities and Contacts

Karimi, M., Wu, D., Wang, Z., & Shen, Y. (2019) · Journal of Chemical Information and Modeling

Computational Drug Discovery MethodsMachine Learning in Bioinformatics

Cited by 64

Explainable Deep Relational Networks for Predicting Compound–Protein Affinities and Contacts

Karimi, M., Wu, D., Wang, Z., & Shen, Y. (2021) · Journal of Chemical Information and Modeling

Computational Drug Discovery MethodsMachine Learning in Bioinformatics

Cited by 64

Taxonomy of Machine Learning Safety: A Survey and Primer

Mohseni, S., Wang, H., Xiao, C., Yu, Z., Wang, Z., & Yadawa, J. (2023) · ACM Computing Surveys

Safety Systems Engineering in AutonomyAdversarial Robustness in Machine Learning

Cited by 53

StreamingT2V: Consistent, Dynamic, and Extendable Long Video Generation from Text

Henschel, R., Khachatryan, L., Poghosyan, H., Hayrapetyan, D., Tadevosyan, V., Wang, Z., Navasardyan, S., & Shi, H. (2024) · arXiv

Generative Adversarial Networks and Image SynthesisMultimodal Machine Learning Applications

Cited by 44

The Unreasonable Effectiveness of Random Pruning: Return of the Most Naive Baseline for Sparse Training

Liu, S., Chen, T., Chen, X., Shen, L., Mocanu, D. C., Wang, Z., & Pechenizkiy, M. (2022) · arXiv

Advanced Neural Network ApplicationsMachine Learning and Data Classification

Cited by 43

LLM-PBE: Assessing Data Privacy in Large Language Models

Li, Q., Hong, J., Xie, C., Tan, J., Xin, R., Hou, J., Yin, X., Wang, Z., Hendrycks, D., Wang, Z., et al. (2024) · Proceedings of the VLDB Endowment

Privacy-Preserving Technologies in DataAdversarial Robustness in Machine Learning

Cited by 42

LLM-PBE: Assessing Data Privacy in Large Language Models

Li, Q., Hong, J., Xie, C., Tan, J., Xin, R., Hou, J., Yin, X., Wang, Z., Hendrycks, D., Wang, Z., et al. (2024) · arXiv

Privacy-Preserving Technologies in DataAdversarial Robustness in Machine Learning

Cited by 42

Mm3dgs slam: Multi-modal 3d gaussian splatting for slam using vision, depth, and inertial measurements

Sun, L. C., Bhatt, N. P., Liu, J. C., Fan, Z., Wang, Z., Humphreys, T. E., & Topcu, U. (2024) · 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

Robotics and Sensor-Based Localization3D Surveying and Cultural Heritage

Cited by 34

VAQF: Fully Automatic Software-hardware Co-design Framework for Low-bit Vision Transformer

Sun, M., Ma, H., Kang, G., Jiang, Y., Chen, T., Ma, X., Wang, Z., & Wang, Y. (2022) · arXiv

Embedded Systems Design TechniquesAdvanced Neural Network Applications

Cited by 32

MedHallu: A Comprehensive Benchmark for Detecting Medical Hallucinations in Large Language Models

Pandit, S., Xu, J., Hong, J., Wang, Z., Chen, T., Xu, K., & Ding, Y. (2025) · arXiv

Topic ModelingArtificial Intelligence in Healthcare and Education

Cited by 31

Uncertainty Quantification for Deep Context-Aware Mobile Activity Recognition and Unknown Context Discovery

Huo, Z., PakBin, A., Chen, X., Hurley, N., Yuan, Y., Qian, X., Wang, Z., Huang, S., & Mortazavi, B. (2020) · arXiv

Context-Aware Activity Recognition SystemsHuman Mobility and Location-Based Analysis

Cited by 10

LLM-AutoDiff: Auto-Differentiate Any LLM Workflow

Yin, L., & Wang, Z. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 0

From Low Rank Gradient Subspace Stabilization to Low-Rank Weights: Observations, Theories, and Applications

Jaiswal, A., Wang, Y., Yin, L., Liu, S., Chen, R., Zhao, J., Grama, A., Tian, Y., & Wang, Z. (2024) · arXiv

Advanced Neural Network ApplicationsTopic Modeling

Cited by 0