Zeliang Zhang
Ph.D. Student, University of Rochester
hust0426 @ gmail.com
Bio
I am a PhD student in the Department of Computer Science at the University of Rochester, advised by Prof. Chenliang Xu. I received my B.Eng. from CS Department, Huazhong University of Science and Technology in 2022. In my undergrad, I worked with Prof. Kun He and Mr. Xiaosen Wang at HUST on adversarial machine learning, Prof. Yijie Peng at PKU on gradient estimation (Zeroth-Order optimization), and Prof. Xiao-Yang Liu at RPI/Columbia on high-performance quantum and tensor computation. I also work closely with Jinyang Jiang at PKU, Wei Yao at RUC, and Mingqian Feng at UR, who have strong backgrouds in machine learning theory. I am good at playing Erhu and familiar with Violin. Welcome to reach out to chat:)
I am broadly interested in: - Trustworthy AI: security, privacy, and explainability; - Optimization Theory: zeroth-order optimization, stochastic optimization; - Efficient AI: GPU tensor core, tensor computation;
Currently, I mainly work on efficient and reliable AI for my Ph.D. degree.
News
Publications & Projects
Google Scholar.
* indicates equal contribution. The order of co-first author may be different from the literature.
† indicates the project leader.
Do More Details Always Introduce More Hallucinations in LVLM-based Image Captioning?
Mingqian Feng, Yunlong Tang, Zeliang Zhang, Chenliang Xu
Preprint arXiv 2024.
Discover and Mitigate Multiple Biased Subgroups in Image Classifiers
Zeliang Zhang*, Mingqian Feng*, Zhiheng Li, Chenliang Xu
CVPR 2024.
Learning to Transform Dynamically for Better Adversarial Transferability
Rongyi Zhu*, Zeliang Zhang*†, Susan Liang, Zhuo Liu, Chenliang Xu
CVPR 2024.
Forward Learning with Differential Privacy
Mingqian Feng, Zeliang Zhang, Jinyang Jiang, Chenliang Xu
Bag of Tricks to Boost the Adversarial Transferability
Zeliang Zhang*†, Rongyi Zhu*, Wei Yao, Xiaosen Wang, Chenliang Xu
Preprint arXiv 2024
Random Smooth-based Certified Defense against Text Adversarial Attack
Zeliang Zhang*†, Wei Yao*, Susan Liang, Chenliang Xu
Findings of EACL 2024.
Diversifying the High-level Features for better Adversarial Transferability
Zeliang Zhang*, Zhiyuan Wang*, Siyuan Liang, Xiaosen Wang
BMVC 2023.
Structure Invariant Transformation for better Adversarial Transferability
Xiaosen Wang, Zeliang Zhang, Jianping Zhang
ICCV 2023.
Triangle Attack: A Query-efficient Decision-based Adversarial Attack
Xiaosen Wang, Zeliang Zhang, Kangheng Tong, Dihong Gong, Kun He, Zhifeng Li, Wei Liu
ECCV 2022.
Forward Learning for Gradient-based Black-box Saliency Map Generation
Zeliang Zhang*†, Mingqian Feng*, Jinyang Jiang, Rongyi Zhu, Yijie Peng, Chenliang Xu
Preprint arXiv 2024.
Approximated Likelihood Ratio: A Forward-Only and Parallel Framework for Boosting Neural Network Training
Zeliang Zhang*†, Jinyang Jiang*, Zhuo Liu, Susan Liang, Yijie Peng, Chenliang Xu
Preprint arXiv 2024.
How Robust is your Fair Model? Exploring the Robustness of Diverse Fairness Strategies
Edward Small, Wei Shao, Zeliang Zhang, Peihan Liu, Jeffrey Chan, Kacper Sokol, Flora Salim
Data Mining and Knowledge Discovery.
One Forward is Enough for Training Neural Networks via the Likelihood Ratio Method
Jinyang Jiang*, Zeliang Zhang*, Chenliang Xu, Zhaofei Yu, Yijie Peng
ICLR 2024.
Noise Optimization for Artificial Neural Networks
Li Xiao (Advisor), Zeliang Zhang, Jinyang Jiang, Yijie Peng
first CASE 2022, then IEEE Transactions on Automation Science and Engineering.
DHN: DEEP HAMILTONIAN NETWORK FOR VARIATIONAL REINFORCEMENT LEARNING
Zeliang Zhang, Yipeng Wang, Zeqi Liu, Xiao-Yang Liu
NIPS 2021 QTNML W.
Video Understanding with Large Language Models: A Survey
Prof. Chenliang Xu and Prof. Jiebo Luo's Labs at URCS
TransferAttack
Trustworthy AI Group
Elegant RL
AI4Finance Foundation
RL for Quantum Circuits
AI4Finance Foundation
Classical Simulation of Quantum Circuits using Reinforcement Learning: Parallel Environments and Benchmark
Xiao-Yang Liu, Zeliang Zhang
NeurIPS dataset and benchmark track 2024.
Scalable CP Decomposition for Tensor Learning using GPU Tensor Cores
Zeliang Zhang, Zhuo Liu, Susan Liang, Zhiyuan Wang, Yifan Zhu, Chen Ding, Chenliang Xu
DAC 2024 WIP.
High-Performance Tensor Learning Primitives Using GPU Tensor Cores
Xiao-Yang Liu*, Zeliang Zhang*, Zhiyuan Wang, Han Lu, Xiaodong Wang, Anwar Walid
IEEE Transactions on Computers (CCF-A journal).
Trillion-Tensor: Trillion-Scale CP Tensor Decomposition
Zeliang Zhang, Xiao-Yang Liu, Pan Zhou
IJCAI 2020 TNRML W.
Parallel TTr1-Tensor: Randomized Compression-based Scheme for Tensor Train Rank-1 Decomposition
Zeliang Zhang, Junzhe Zhang, Guoping Lin, Zeyuan Yin, Kun He
NIPS 2020 QTNML W.
Do More Details Always Introduce More Hallucinations in LVLM-based Image Captioning?
Mingqian Feng, Yunlong Tang, Zeliang Zhang, Chenliang Xu
Preprint arXiv 2024.
Discover and Mitigate Multiple Biased Subgroups in Image Classifiers
Zeliang Zhang*, Mingqian Feng*, Zhiheng Li, Chenliang Xu
CVPR 2024.
Learning to Transform Dynamically for Better Adversarial Transferability
Rongyi Zhu*, Zeliang Zhang*†, Susan Liang, Zhuo Liu, Chenliang Xu
CVPR 2024.
Forward Learning with Differential Privacy
Mingqian Feng, Zeliang Zhang, Jinyang Jiang, Chenliang Xu
Forward Learning for Gradient-based Black-box Saliency Map Generation
Zeliang Zhang*†, Mingqian Feng*, Jinyang Jiang, Rongyi Zhu, Yijie Peng, Chenliang Xu
Preprint arXiv 2024.
Approximated Likelihood Ratio: A Forward-Only and Parallel Framework for Boosting Neural Network Training
Zeliang Zhang*†, Jinyang Jiang*, Zhuo Liu, Susan Liang, Yijie Peng, Chenliang Xu
Preprint arXiv 2024.
How Robust is your Fair Model? Exploring the Robustness of Diverse Fairness Strategies
Edward Small, Wei Shao, Zeliang Zhang, Peihan Liu, Jeffrey Chan, Kacper Sokol, Flora Salim
Data Mining and Knowledge Discovery.
One Forward is Enough for Training Neural Networks via the Likelihood Ratio Method
Jinyang Jiang*, Zeliang Zhang*, Chenliang Xu, Zhaofei Yu, Yijie Peng
ICLR 2024.
Bag of Tricks to Boost the Adversarial Transferability
Zeliang Zhang*†, Rongyi Zhu*, Wei Yao, Xiaosen Wang, Chenliang Xu
Preprint arXiv 2024
Random Smooth-based Certified Defense against Text Adversarial Attack
Zeliang Zhang*†, Wei Yao*, Susan Liang, Chenliang Xu
Findings of EACL 2024.
Classical Simulation of Quantum Circuits using Reinforcement Learning: Parallel Environments and Benchmark
Xiao-Yang Liu, Zeliang Zhang
NeurIPS dataset and benchmark track 2024.
Diversifying the High-level Features for better Adversarial Transferability
Zeliang Zhang*, Zhiyuan Wang*, Siyuan Liang, Xiaosen Wang
BMVC 2023.
Structure Invariant Transformation for better Adversarial Transferability
Xiaosen Wang, Zeliang Zhang, Jianping Zhang
ICCV 2023.
Scalable CP Decomposition for Tensor Learning using GPU Tensor Cores
Zeliang Zhang, Zhuo Liu, Susan Liang, Zhiyuan Wang, Yifan Zhu, Chen Ding, Chenliang Xu
DAC 2024 WIP.
High-Performance Tensor Learning Primitives Using GPU Tensor Cores
Xiao-Yang Liu*, Zeliang Zhang*, Zhiyuan Wang, Han Lu, Xiaodong Wang, Anwar Walid
IEEE Transactions on Computers (CCF-A journal).
Triangle Attack: A Query-efficient Decision-based Adversarial Attack
Xiaosen Wang, Zeliang Zhang, Kangheng Tong, Dihong Gong, Kun He, Zhifeng Li, Wei Liu
ECCV 2022.
Noise Optimization for Artificial Neural Networks
Li Xiao (Advisor), Zeliang Zhang, Jinyang Jiang, Yijie Peng
first CASE 2022, then IEEE Transactions on Automation Science and Engineering.
Trillion-Tensor: Trillion-Scale CP Tensor Decomposition
Zeliang Zhang, Xiao-Yang Liu, Pan Zhou
IJCAI 2020 TNRML W.
Parallel TTr1-Tensor: Randomized Compression-based Scheme for Tensor Train Rank-1 Decomposition
Zeliang Zhang, Junzhe Zhang, Guoping Lin, Zeyuan Yin, Kun He
NIPS 2020 QTNML W.
DHN: DEEP HAMILTONIAN NETWORK FOR VARIATIONAL REINFORCEMENT LEARNING
Zeliang Zhang, Yipeng Wang, Zeqi Liu, Xiao-Yang Liu
NIPS 2021 QTNML W.
Video Understanding with Large Language Models: A Survey
Prof. Chenliang Xu and Prof. Jiebo Luo's Labs at URCS
TransferAttack
Trustworthy AI Group
Elegant RL
AI4Finance Foundation
RL for Quantum Circuits
AI4Finance Foundation
Education
Experiences
