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ORCIDKaiwen Zhou 0001
Person information
- affiliation: Huawei Noah's Ark Lab, Shenzhen, China
- affiliation (PhD 2022): Chinese University of Hong Kong, Department of Computer Science and Engineering, Hong Kong
Other persons with the same name
- Kaiwen Zhou
- Kaiwen Zhou 0002 — University of California, Santa Cruz, CA, USA
- Kaiwen Zhou 0003
![[0009-0005-1017-8878]](https://devdomain4test.ir/img/orcid-mark.12x12.png "0009-0005-1017-8878")
— Zhejiang University, College of Computer Science and Technology, Advanced Computing and Emerging Service (ACES) Laboratory, Hangzhou, China - Kaiwen Zhou 0004 — Fudan University, State Key Laboratory of Integrated Chips and Systems, Shanghai, China
- Kaiwen Zhou 0005 — Shanghai University, School of Communication and Information Engineering, China
- Kaiwen Zhou 0006 — Heilongjiang Institute of Technology, Harbin, China
- Kaiwen Zhou 0007 — Hohai University, College of Mechanical and Electrical Engineering, Changzhou, China
- Kaiwen Zhou 0008 — East China Normal University, School of Data Science and Engineering, Shanghai, China
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2020 – today
- 2026
[c28]Wei Li, Renshan Zhang, Rui Shao, Zhijian Fang, Kaiwen Zhou, Zhuotao Tian, Liqiang Nie:
SemanticVLA: Semantic-Aligned Sparsification and Enhancement for Efficient Robotic Manipulation. AAAI 2026: 18397-18405- [c27]Mingming Zhao, Xiaokang Wei, Yuanqi Shao, Kaiwen Zhou, Lin Yang, Siwei Rao, Junhui Zhan, Zhitang Chen:
A²Flow: Automating Agentic Workflow Generation via Self-Adaptive Abstraction Operators. AAAI 2026: 29930-29938 - [c26]Haoyu Lei, Kaiwen Zhou, Yinchuan Li, Zhitang Chen, Farzan Farnia:
Boosting Cross-problem Generalization in Diffusion-Based Neural Combinatorial Solver via Inference Time Adaptation. AAAI 2026: 36289-36297 - [i42]Rui Shao, Ruize Gao, Bin Xie, Yixing Li, Kaiwen Zhou, Shuai Wang, Weili Guan, Gongwei Chen:
HATS: Hardness-Aware Trajectory Synthesis for GUI Agents. CoRR abs/2603.12138 (2026) - [i41]Ruize Gao, Kaiwen Zhou, Yongqiang Chen, Feng Liu:
A Unified Perspective on Adversarial Membership Manipulation in Vision Models. CoRR abs/2604.02780 (2026) - [i40]Tiantian He, Yihang Chen, Keyue Jiang, Ka Yiu Lee, Kaiwen Zhou, Kun Shao, Shuai Wang:
EE-MCP: Self-Evolving MCP-GUI Agents via Automated Environment Generation and Experience Learning. CoRR abs/2604.09815 (2026) - 2025
- [c25]Bin Xie, Rui Shao, Gongwei Chen, Kaiwen Zhou, Yinchuan Li, Jie Liu, Min Zhang, Liqiang Nie:
GUI-explorer: Autonomous Exploration and Mining of Transition-aware Knowledge for GUI Agent. ACL (1) 2025: 5650-5667 - [c24]Gongwei Chen, Xurui Zhou, Rui Shao, Yibo Lyu, Kaiwen Zhou, Shuai Wang, Wentao Li, Yinchuan Li, Zhongang Qi, Liqiang Nie:
Less is More: Empowering GUI Agent with Context-Aware Simplification. ICCV 2025: 5901-5911 - [c23]Renshan Zhang, Rui Shao, Gongwei Chen, Miao Zhang, Kaiwen Zhou, Weili Guan, Liqiang Nie:
FALCON: Resolving Visual Redundancy and Fragmentation in High-Resolution Multimodal Large Language Models via Visual Registers. ICCV 2025: 23530-23540 - [c22]Jingxuan Chen, Derek Yuen, Bin Xie, Yuhao Yang, Gongwei Chen, Zhihao Wu, Li Yixing, Xurui Zhou, Weiwen Liu, Shuai Wang, Kaiwen Zhou, Rui Shao, Liqiang Nie, Yasheng Wang, Jianye Hao, Jun Wang, Kun Shao:
Spa-Bench: a comprehensive Benchmark for Smartphone Agent Evaluation. ICLR 2025 - [c21]Garry Yang, Zizhe Chen, Man Hon Wong, Haoyu Lei, Yongqiang Chen, Zhenguo Li, Kaiwen Zhou, James Cheng:
MESH - Understanding Videos Like Human: Measuring Hallucinations in Large Video Models. ACM Multimedia 2025: 4827-4836 - [c20]Yuqi Zhou, Sunhao Dai, Shuai Wang, Kaiwen Zhou, Qinglin Jia, Jun Xu:
GUI-G1: Understanding R1-Zero-Like Training for Visual Grounding in GUI Agents. NeurIPS 2025 - [i39]Renshan Zhang, Rui Shao, Gongwei Chen, Kaiwen Zhou, Weili Guan, Liqiang Nie:
FALCON: Resolving Visual Redundancy and Fragmentation in High-resolution Multimodal Large Language Models via Visual Registers. CoRR abs/2501.16297 (2025) - [i38]Haoyu Lei, Kaiwen Zhou, Yinchuan Li, Zhitang Chen, Farzan Farnia:
Boosting Generalization in Diffusion-Based Neural Combinatorial Solver via Energy-guided Sampling. CoRR abs/2502.12188 (2025) - [i37]Yinchuan Li, Xinyu Shao, Jianping Zhang, Haozhi Wang, Leo Maxime Brunswic, Kaiwen Zhou, Jiqian Dong, Kaiyang Guo, Xiu Li, Zhitang Chen, Jun Wang, Jianye Hao:
Generative Models in Decision Making: A Survey. CoRR abs/2502.17100 (2025) - [i36]Zhuo Zhi, Qiangqiang Wu, Minghe shen, Wenbo Li, Yinchuan Li, Kun Shao, Kaiwen Zhou:
VideoAgent2: Enhancing the LLM-Based Agent System for Long-Form Video Understanding by Uncertainty-Aware CoT. CoRR abs/2504.04471 (2025) - [i35]Yuqi Zhou, Sunhao Dai, Shuai Wang, Kaiwen Zhou, Qinglin Jia, Jun Xu:
GUI-G1: Understanding R1-Zero-Like Training for Visual Grounding in GUI Agents. CoRR abs/2505.15810 (2025) - [i34]Bin Xie, Rui Shao, Gongwei Chen, Kaiwen Zhou, Yinchuan Li, Jie Liu, Min Zhang, Liqiang Nie:
GUI-explorer: Autonomous Exploration and Mining of Transition-aware Knowledge for GUI Agent. CoRR abs/2505.16827 (2025) - [i33]Yuquan Xie, Zaijing Li, Rui Shao, Gongwei Chen, Kaiwen Zhou, Yinchuan Li, Dongmei Jiang, Liqiang Nie:
Mirage-1: Augmenting and Updating GUI Agent with Hierarchical Multimodal Skills. CoRR abs/2506.10387 (2025) - [i32]Gongwei Chen, Xurui Zhou, Rui Shao, Yibo Lyu, Kaiwen Zhou, Shuai Wang, Wentao Li, Yinchuan Li, Zhongang Qi, Liqiang Nie:
Less is More: Empowering GUI Agent with Context-Aware Simplification. CoRR abs/2507.03730 (2025) - [i31]Chao Hao, Shuai Wang, Kaiwen Zhou:
Uncertainty-Aware GUI Agent: Adaptive Perception through Component Recommendation and Human-in-the-Loop Refinement. CoRR abs/2508.04025 (2025) - [i30]Garry Yang, Zizhe Chen, Man Hon Wong, Haoyu Lei, Yongqiang Chen, Zhenguo Li, Kaiwen Zhou, James Cheng:
MESH - Understanding Videos Like Human: Measuring Hallucinations in Large Video Models. CoRR abs/2509.08538 (2025) - [i29]Xinyu Shao, Yanzhe Tang, Pengwei Xie, Kaiwen Zhou, Yuzheng Zhuang, Xingyue Quan, Jianye Hao, Long Zeng, Xiu Li:
More than A Point: Capturing Uncertainty with Adaptive Affordance Heatmaps for Spatial Grounding in Robotic Tasks. CoRR abs/2510.10912 (2025) - [i28]Wei Li, Renshan Zhang, Rui Shao, Zhijian Fang, Kaiwen Zhou, Zhuotao Tian, Liqiang Nie:
SemanticVLA: Semantic-Aligned Sparsification and Enhancement for Efficient Robotic Manipulation. CoRR abs/2511.10518 (2025) - [i27]Mingming Zhao, Xiaokang Wei, Yuanqi Shao, Kaiwen Zhou, Lin Yang, Siwei Rao, Junhui Zhan, Zhitang Chen:
A2Flow: Automating Agentic Workflow Generation via Self-Adaptive Abstraction Operators. CoRR abs/2511.20693 (2025) - [i26]Haoyu Lei, Chin Wa Lau, Kaiwen Zhou, Nian Guo, Farzan Farnia:
Consistency Flow Model Achieves One-step Denoising Error Correction Codes. CoRR abs/2512.01389 (2025) - [i25]Xurui Zhou, Gongwei Chen, Yuquan Xie, Zaijing Li, Kaiwen Zhou, Shuai Wang, Shuo Yang, Zhuotao Tian, Rui Shao:
HiconAgent: History Context-aware Policy Optimization for GUI Agents. CoRR abs/2512.01763 (2025) - 2024
- [j2]Chenhan Jin, Kaiwen Zhou, Bo Han, James Cheng, Tieyong Zeng:
Efficient private SCO for heavy-tailed data via averaged clipping. Mach. Learn. 113(11): 8487-8532 (2024) - [c19]Binghui Xie, Yongqiang Chen, Jiaqi Wang, Kaiwen Zhou, Bo Han, Wei Meng, James Cheng:
Enhancing Evolving Domain Generalization through Dynamic Latent Representations. AAAI 2024: 16040-16048 - [c18]Binghui Xie, Yatao Bian, Kaiwen Zhou, Yongqiang Chen, Peilin Zhao, Bo Han, Wei Meng, James Cheng:
Enhancing Neural Subset Selection: Integrating Background Information into Set Representations. ICLR 2024 - [c17]Haoyu Chen, Wenbo Li, Jinjin Gu, Jingjing Ren, Sixiang Chen, Tian Ye, Renjing Pei, Kaiwen Zhou, Fenglong Song, Lei Zhu:
RestoreAgent: Autonomous Image Restoration Agent via Multimodal Large Language Models. NeurIPS 2024 - [c16]Binghui Xie, Yixuan Wang, Yongqiang Chen, Kaiwen Zhou, Yu Li, Wei Meng, James Cheng:
HORSE: Hierarchical Representation for Large-Scale Neural Subset Selection. NeurIPS 2024 - [i24]Binghui Xie, Yongqiang Chen, Jiaqi Wang, Kaiwen Zhou, Bo Han, Wei Meng, James Cheng:
Enhancing Evolving Domain Generalization through Dynamic Latent Representations. CoRR abs/2401.08464 (2024) - [i23]Binghui Xie, Yatao Bian, Kaiwen Zhou, Yongqiang Chen, Peilin Zhao, Bo Han, Wei Meng, James Cheng:
Enhancing Neural Subset Selection: Integrating Background Information into Set Representations. CoRR abs/2402.03139 (2024) - [i22]Haoyu Chen, Wenbo Li, Jinjin Gu, Jingjing Ren, Sixiang Chen, Tian Ye, Renjing Pei, Kaiwen Zhou, Fenglong Song, Lei Zhu:
RestoreAgent: Autonomous Image Restoration Agent via Multimodal Large Language Models. CoRR abs/2407.18035 (2024) - [i21]Jingxuan Chen, Derek Yuen, Bin Xie, Yuhao Yang, Gongwei Chen, Zhihao Wu, Li Yixing, Xurui Zhou, Weiwen Liu, Shuai Wang, Kaiwen Zhou, Rui Shao, Liqiang Nie, Yasheng Wang, Jianye Hao, Jun Wang, Kun Shao:
SPA-Bench: A Comprehensive Benchmark for SmartPhone Agent Evaluation. CoRR abs/2410.15164 (2024) - [i20]Haoze Sun, Wenbo Li, Jiayue Liu, Kaiwen Zhou, Yongqiang Chen, Yong Guo, Yanwei Li, Renjing Pei, Long Peng, Yujiu Yang:
Beyond Pixels: Text Enhances Generalization in Real-World Image Restoration. CoRR abs/2412.00878 (2024) - 2023
- [c15]Kaiwen Zhou, Zhilin Chen, Guochen Liu, Zhitang Chen:
A Novel Extrapolation Technique to Accelerate WMMSE. ICASSP 2023: 1-5 - [c14]Yongqiang Chen, Kaiwen Zhou, Yatao Bian, Binghui Xie, Bingzhe Wu, Yonggang Zhang, Kaili Ma, Han Yang, Peilin Zhao, Bo Han, James Cheng:
Pareto Invariant Risk Minimization: Towards Mitigating the Optimization Dilemma in Out-of-Distribution Generalization. ICLR 2023 - [c13]Yongqiang Chen, Yatao Bian, Kaiwen Zhou, Binghui Xie, Bo Han, James Cheng:
Does Invariant Graph Learning via Environment Augmentation Learn Invariance? NeurIPS 2023 - [c12]Yongqiang Chen, Wei Huang, Kaiwen Zhou, Yatao Bian, Bo Han, James Cheng:
Understanding and Improving Feature Learning for Out-of-Distribution Generalization. NeurIPS 2023 - [i19]Yongqiang Chen, Wei Huang, Kaiwen Zhou, Yatao Bian, Bo Han, James Cheng:
Towards Understanding Feature Learning in Out-of-Distribution Generalization. CoRR abs/2304.11327 (2023) - [i18]Yongqiang Chen, Yatao Bian, Kaiwen Zhou, Binghui Xie, Bo Han, James Cheng:
Does Invariant Graph Learning via Environment Augmentation Learn Invariance? CoRR abs/2310.19035 (2023) - [i17]Yongqiang Chen, Binghui Xie, Kaiwen Zhou, Bo Han, Yatao Bian, James Cheng:
Positional Information Matters for Invariant In-Context Learning: A Case Study of Simple Function Classes. CoRR abs/2311.18194 (2023) - 2022
- [c11]Kaiwen Zhou, Lai Tian, Anthony Man-Cho So, James Cheng:
Practical Schemes for Finding Near-Stationary Points of Convex Finite-Sums. AISTATS 2022: 3684-3708 - [c10]Ruize Gao, Jiongxiao Wang, Kaiwen Zhou, Feng Liu, Binghui Xie, Gang Niu, Bo Han, James Cheng:
Fast and Reliable Evaluation of Adversarial Robustness with Minimum-Margin Attack. ICML 2022: 7144-7163 - [c9]Lai Tian, Kaiwen Zhou, Anthony Man-Cho So:
On the Finite-Time Complexity and Practical Computation of Approximate Stationarity Concepts of Lipschitz Functions. ICML 2022: 21360-21379 - [i16]Binghui Xie, Chenhan Jin, Kaiwen Zhou, James Cheng, Wei Meng:
An Adaptive Incremental Gradient Method With Support for Non-Euclidean Norms. CoRR abs/2205.02273 (2022) - [i15]Ruize Gao, Jiongxiao Wang, Kaiwen Zhou, Feng Liu, Binghui Xie, Gang Niu, Bo Han, James Cheng:
Fast and Reliable Evaluation of Adversarial Robustness with Minimum-Margin Attack. CoRR abs/2206.07314 (2022) - [i14]Yongqiang Chen, Kaiwen Zhou, Yatao Bian, Binghui Xie, Kaili Ma, Yonggang Zhang, Han Yang, Bo Han, James Cheng:
Pareto Invariant Risk Minimization. CoRR abs/2206.07766 (2022) - [i13]Chenhan Jin, Kaiwen Zhou, Bo Han, James Cheng, Ming-Chang Yang:
Efficient Private SCO for Heavy-Tailed Data via Clipping. CoRR abs/2206.13011 (2022) - 2021
- [i12]Kaiwen Zhou, Lai Tian, Anthony Man-Cho So, James Cheng:
Practical Schemes for Finding Near-Stationary Points of Convex Finite-Sums. CoRR abs/2105.12062 (2021) - [i11]Ruize Gao, Feng Liu, Kaiwen Zhou, Gang Niu, Bo Han, James Cheng:
Local Reweighting for Adversarial Training. CoRR abs/2106.15776 (2021) - [i10]Kaiwen Zhou, Anthony Man-Cho So, James Cheng:
Accelerating Perturbed Stochastic Iterates in Asynchronous Lock-Free Optimization. CoRR abs/2109.15292 (2021) - 2020
- [j1]Fanhua Shang, Kaiwen Zhou, Hongying Liu, James Cheng, Ivor W. Tsang, Lijun Zhang, Dacheng Tao, Licheng Jiao:
VR-SGD: A Simple Stochastic Variance Reduction Method for Machine Learning. IEEE Trans. Knowl. Data Eng. 32(1): 188-202 (2020) - [c8]Qinghua Ding, Kaiwen Zhou, James Cheng:
Tight Convergence Rate of Gradient Descent for Eigenvalue Computation. IJCAI 2020: 3276-3282 - [c7]Kaiwen Zhou, Anthony Man-Cho So, James Cheng:
Boosting First-Order Methods by Shifting Objective: New Schemes with Faster Worst-Case Rates. NeurIPS 2020 - [c6]Xinyan Dai, Xiao Yan, Kaiwen Zhou, Yuxuan Wang, Han Yang, James Cheng:
Convolutional Embedding for Edit Distance. SIGIR 2020: 599-608 - [c5]Kaiwen Zhou, Yanghua Jin, Qinghua Ding, James Cheng:
Amortized Nesterov's Momentum: A Robust Momentum and Its Application to Deep Learning. UAI 2020: 211-220 - [i9]Xinyan Dai, Xiao Yan, Kaiwen Zhou, Yuxuan Wang, Han Yang, James Cheng:
Edit Distance Embedding using Convolutional Neural Networks. CoRR abs/2001.11692 (2020) - [i8]Kaiwen Zhou, Anthony Man-Cho So, James Cheng:
Boosting First-order Methods by Shifting Objective: New Schemes with Faster Worst Case Rates. CoRR abs/2005.12061 (2020)
2010 – 2019
- 2019
- [c4]Kaiwen Zhou, Qinghua Ding, Fanhua Shang, James Cheng, Danli Li, Zhi-Quan Luo:
Direct Acceleration of SAGA using Sampled Negative Momentum. AISTATS 2019: 1602-1610 - [i7]Xinyan Dai, Xiao Yan, Kaiwen Zhou, Han Yang, Kelvin Kai Wing Ng, James Cheng, Yu Fan:
Hyper-Sphere Quantization: Communication-Efficient SGD for Federated Learning. CoRR abs/1911.04655 (2019) - 2018
- [c3]Fanhua Shang, Licheng Jiao, Kaiwen Zhou, James Cheng, Yan Ren, Yufei Jin:
ASVRG: Accelerated Proximal SVRG. ACML 2018: 815-830 - [c2]Fanhua Shang, Yuanyuan Liu, Kaiwen Zhou, James Cheng, Kelvin Kai Wing Ng, Yuichi Yoshida:
Guaranteed Sufficient Decrease for Stochastic Variance Reduced Gradient Optimization. AISTATS 2018: 1027-1036 - [c1]Kaiwen Zhou, Fanhua Shang, James Cheng:
A Simple Stochastic Variance Reduced Algorithm with Fast Convergence Rates. ICML 2018: 5975-5984 - [i6]Fanhua Shang, Kaiwen Zhou, James Cheng, Ivor W. Tsang, Lijun Zhang, Dacheng Tao:
VR-SGD: A Simple Stochastic Variance Reduction Method for Machine Learning. CoRR abs/1802.09932 (2018) - [i5]Fanhua Shang, Yuanyuan Liu, Kaiwen Zhou, James Cheng, Kelvin Kai Wing Ng, Yuichi Yoshida:
Guaranteed Sufficient Decrease for Stochastic Variance Reduced Gradient Optimization. CoRR abs/1802.09933 (2018) - [i4]Kaiwen Zhou, Fanhua Shang, James Cheng:
A Simple Stochastic Variance Reduced Algorithm with Fast Convergence Rates. CoRR abs/1806.11027 (2018) - [i3]Kaiwen Zhou:
Direct Acceleration of SAGA using Sampled Negative Momentum. CoRR abs/1806.11048 (2018) - [i2]Fanhua Shang, Licheng Jiao, Kaiwen Zhou, James Cheng, Yan Ren, Yufei Jin:
ASVRG: Accelerated Proximal SVRG. CoRR abs/1810.03105 (2018) - [i1]Xiao Yan, Xinyan Dai, Jie Liu, Kaiwen Zhou, James Cheng:
Norm-Range Partition: A Univiseral Catalyst for LSH based Maximum Inner Product Search (MIPS). CoRR abs/1810.09104 (2018)
Coauthor Index
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last updated on 2026-07-20 01:26 CEST by the dblp team
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