Ma, Guozheng

11 publications

TMLR 2025 Are Large Language Models Really Robust to Word-Level Perturbations? Haoyu Wang, Guozheng Ma, Cong Yu, Ning Gui, Linrui Zhang, Zhiqi Huang, Suwei Ma, Yongzhe Chang, Sen Zhang, Li Shen, Xueqian Wang, Peilin Zhao, Dacheng Tao

ICCV 2025 Faster and Better 3D Splatting via Group Training Chengbo Wang, Guozheng Ma, Yifei Xue, Yizhen Lao

ICML 2025 Mastering Massive Multi-Task Reinforcement Learning via Mixture-of-Expert Decision Transformer Yilun Kong, Guozheng Ma, Qi Zhao, Haoyu Wang, Li Shen, Xueqian Wang, Dacheng Tao

ICLRW 2025 Mastering Massive Multi-Task Reinforcement Learning via Mixture-of-Expert Decision Transformer Yilun Kong, Guozheng Ma, Qi Zhao, Haoyu Wang, Li Shen, Xueqian Wang, Dacheng Tao

ICML 2025 Network Sparsity Unlocks the Scaling Potential of Deep Reinforcement Learning Guozheng Ma, Lu Li, Zilin Wang, Li Shen, Pierre-Luc Bacon, Dacheng Tao

ICLR 2024 Revisiting Plasticity in Visual Reinforcement Learning: Data, Modules and Training Stages Guozheng Ma, Lu Li, Sen Zhang, Zixuan Liu, Zhen Wang, Yixin Chen, Li Shen, Xueqian Wang, Dacheng Tao

ICMLW 2024 Step-on-Feet Tuning: Scaling Self-Alignment of LLMs via Bootstrapping Haoyu Wang, Guozheng Ma, Ziqiao Meng, Zeyu Qin, Li Shen, Zhong Zhang, Bingzhe Wu, Liu Liu, Yatao Bian, Tingyang Xu, Xueqian Wang, Peilin Zhao

NeurIPSW 2023 Are Large Language Models Really Robust to Word-Level Perturbations? Haoyu Wang, Guozheng Ma, Cong Yu, Ning Gui, Linrui Zhang, Zhiqi Huang, Suwei Ma, Yongzhe Chang, Sen Zhang, Li Shen, Xueqian Wang, Peilin Zhao, Dacheng Tao

NeurIPS 2023 Learning Better with Less: Effective Augmentation for Sample-Efficient Visual Reinforcement Learning Guozheng Ma, Linrui Zhang, Haoyu Wang, Lu Li, Zilin Wang, Zhen Wang, Li Shen, Xueqian Wang, Dacheng Tao

NeurIPSW 2023 Normalization Enhances Generalization in Visual Reinforcement Learning Lu Li, Jiafei Lyu, Guozheng Ma, Zilin Wang, Zhenjie Yang, Xiu Li, Zhiheng Li

IJCAI 2022 Don't Touch What Matters: Task-Aware Lipschitz Data Augmentation for Visual Reinforcement Learning Zhecheng Yuan, Guozheng Ma, Yao Mu, Bo Xia, Bo Yuan, Xueqian Wang, Ping Luo, Huazhe Xu