Shen, Li

182 publications

TMLR 2026 Subspace Based Federated Unlearning Guanghao Li, Li Shen, Yan Sun, Yue Hu, Han Hu, Dacheng Tao

NeurIPS 2025 Ada-R1: Hybrid-CoT via Bi-Level Adaptive Reasoning Optimization Haotian Luo, Haiying He, Yibo Wang, Jinluan Yang, Rui Liu, Naiqiang Tan, Xiaochun Cao, Dacheng Tao, Li Shen

NeurIPS 2025 Adaptive Defense Against Harmful Fine-Tuning for Large Language Models via Bayesian Data Scheduler Zixuan Hu, Li Shen, Zhenyi Wang, Yongxian Wei, Dacheng Tao

NeurIPS 2025 AlphaDecay: Module-Wise Weight Decay for Heavy-Tailed Balancing in LLMs Di He, Songjun Tu, Ajay Jaiswal, Li Shen, Ganzhao Yuan, Shiwei Liu, Lu Yin

NeurIPS 2025 Analytic Energy-Guided Policy Optimization for Offline Reinforcement Learning Jifeng Hu, Sili Huang, Zhejian Yang, Shengchao Hu, Li Shen, Hechang Chen, Lichao Sun, Yi Chang, Dacheng Tao

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

NeurIPS 2025 CHPO: Constrained Hybrid-Action Policy Optimization for Reinforcement Learning Ao Zhou, Jiayi Guan, Li Shen, Fan Lu, Sanqing Qu, Junqiao Zhao, Ziqiao Wang, Ya Wu, Guang Chen

ICLR 2025 Combatting Dimensional Collapse in LLM Pre-Training Data via Submodular File Selection Ziqing Fan, Siyuan Du, Shengchao Hu, Pingjie Wang, Li Shen, Ya Zhang, Dacheng Tao, Yanfeng Wang

ICML 2025 Contextual Bandits for Unbounded Context Distributions Puning Zhao, Rongfei Fan, Shaowei Wang, Li Shen, Qixin Zhang, Zong Ke, Tianhang Zheng

NeurIPS 2025 Continual Model Merging Without Data: Dual Projections for Balancing Stability and Plasticity Enneng Yang, Anke Tang, Li Shen, Guibing Guo, Xingwei Wang, Xiaochun Cao, Jie Zhang

ICML 2025 Decision Mixer: Integrating Long-Term and Local Dependencies via Dynamic Token Selection for Decision-Making Hongling Zheng, Li Shen, Yong Luo, Deheng Ye, Bo Du, Jialie Shen, Dacheng Tao

AAAI 2025 Divide, Conquer and Combine: A Training-Free Framework for High-Resolution Image Perception in Multimodal Large Language Models Wenbin Wang, Liang Ding, Minyan Zeng, Xiabin Zhou, Li Shen, Yong Luo, Wei Yu, Dacheng Tao

ICLR 2025 Dynamic Neural Fortresses: An Adaptive Shield for Model Extraction Defense Siyu Luan, Zhenyi Wang, Li Shen, Zonghua Gu, Chao Wu, Dacheng Tao

NeurIPS 2025 Effective Policy Learning for Multi-Agent Online Coordination Beyond Submodular Objectives Qixin Zhang, Yan Sun, Can Jin, Xikun Zhang, Yao Shu, Puning Zhao, Li Shen, Dacheng Tao

NeurIPS 2025 Efficient Federated Learning Against Byzantine Attacks and Data Heterogeneity via Aggregating Normalized Gradients Shiyuan Zuo, Xingrun Yan, Rongfei Fan, Li Shen, Puning Zhao, Jie Xu, Han Hu

ICLR 2025 Enhancing Learning with Label Differential Privacy by Vector Approximation Puning Zhao, Jiafei Wu, Zhe Liu, Li Shen, Zhikun Zhang, Rongfei Fan, Le Sun, Qingming Li

ICLR 2025 Fine-Tuning Attention Modules Only: Enhancing Weight Disentanglement in Task Arithmetic Ruochen Jin, Bojian Hou, Jiancong Xiao, Weijie J Su, Li Shen

ICML 2025 GraphCL: Graph-Based Clustering for Semi-Supervised Medical Image Segmentation Mengzhu Wang, Houcheng Su, Jiao Li, Chuan Li, Nan Yin, Li Shen, Jingcai Guo

IJCAI 2025 Hypernetwork Aggregation for Decentralized Personalized Federated Learning Weishi Li, Yong Peng, Mengyao Du, Fuhui Sun, Xiaoyan Wang, Li Shen

AAAI 2025 Image-to-Video Adaptation with Outlier Modeling and Robust Self-Learning Junbao Zhuo, Shuhui Wang, Zhenghan Chen, Li Shen, Qingming Huang, Huimin Ma

CVPR 2025 Investigating the Role of Weight Decay in Enhancing Nonconvex SGD Tao Sun, Yuhao Huang, Li Shen, Kele Xu, Bao Wang

NeurIPS 2025 Layer as Puzzle Pieces: Compressing Large Language Models Through Layer Concatenation Fei Wang, Li Shen, Liang Ding, Chao Xue, Ye Liu, Changxing Ding

ICLRW 2025 Leveraging Reasoning with Guidelines to Elicit and Utilize Knowledge for Enhancing Safety Alignment Haoyu Wang, Zeyu Qin, Li Shen, Xueqian Wang, Minhao Cheng, Dacheng Tao

CVPR 2025 LoRA Recycle: Unlocking Tuning-Free Few-Shot Adaptability in Visual Foundation Models by Recycling Pre-Tuned LoRAs Zixuan Hu, Yongxian Wei, Li Shen, Chun Yuan, Dacheng Tao

ICML 2025 Mask-Enhanced Autoregressive Prediction: Pay Less Attention to Learn More Xialie Zhuang, Zhikai Jia, Jianjin Li, Zhenyu Zhang, Li Shen, Zheng Cao, Shiwei Liu

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

NeurIPS 2025 Merging on the Fly Without Retraining: A Sequential Approach to Scalable Continual Model Merging Anke Tang, Enneng Yang, Li Shen, Yong Luo, Han Hu, Lefei Zhang, Bo Du, Dacheng Tao

ICLR 2025 Mitigating the Backdoor Effect for Multi-Task Model Merging via Safety-Aware Subspace Jinluan Yang, Anke Tang, Didi Zhu, Zhengyu Chen, Li Shen, Fei Wu

NeurIPS 2025 Mix Data or Merge Models? Balancing the Helpfulness, Honesty, and Harmlessness of Large Language Model via Model Merging Jinluan Yang, Dingnan Jin, Anke Tang, Li Shen, Didi Zhu, Zhengyu Chen, Ziyu Zhao, Daixin Wang, Qing Cui, Zhiqiang Zhang, Jun Zhou, Fei Wu, Kun Kuang

NeurIPS 2025 MixPrompt: Efficient Mixed Prompting for Multimodal Semantic Segmentation Zhiwei Hao, Zhongyu Xiao, Jianyuan Guo, Li Shen, Yong Luo, Han Hu, Dan Zeng

ICML 2025 Modeling Multi-Task Model Merging as Adaptive Projective Gradient Descent Yongxian Wei, Anke Tang, Li Shen, Zixuan Hu, Chun Yuan, Xiaochun Cao

NeurIPS 2025 Mulberry: Empowering MLLM with O1-like Reasoning and Reflection via Collective Monte Carlo Tree Search Huanjin Yao, Jiaxing Huang, Wenhao Wu, Jingyi Zhang, Yibo Wang, Shunyu Liu, Yingjie Wang, YuXin Song, Haocheng Feng, Li Shen, Dacheng Tao

ICML 2025 Multinoulli Extension: A Lossless yet Effective Probabilistic Framework for Subset Selection over Partition Constraints Qixin Zhang, Wei Huang, Can Jin, Puning Zhao, Yao Shu, Li Shen, Dacheng Tao

ICLR 2025 Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Qixin Zhang, Zongqi Wan, Yu Yang, Li Shen, 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

NeurIPS 2025 On the Empirical Power of Goodness-of-Fit Tests in Watermark Detection Weiqing He, Xiang Li, Tianqi Shang, Li Shen, Weijie J Su, Qi Long

ICLR 2025 Open-Vocabulary Customization from CLIP via Data-Free Knowledge Distillation Yongxian Wei, Zixuan Hu, Li Shen, Zhenyi Wang, Chun Yuan, Dacheng Tao

ICLR 2025 PEARL: Towards Permutation-Resilient LLMs Liang Chen, Li Shen, Yang Deng, Xiaoyan Zhao, Bin Liang, Kam-Fai Wong

NeurIPS 2025 Panacea: Mitigating Harmful Fine-Tuning for Large Language Models via Post-Fine-Tuning Perturbation Yibo Wang, Tiansheng Huang, Li Shen, Huanjin Yao, Haotian Luo, Rui Liu, Naiqiang Tan, Jiaxing Huang, Dacheng Tao

TMLR 2025 QPO: Query-Dependent Prompt Optimization via Multi-Loop Offline Reinforcement Learning Yilun Kong, Hangyu Mao, Zhao Qi, Bin Zhang, Jingqing Ruan, Li Shen, Yongzhe Chang, Xueqian Wang, Rui Zhao, Dacheng Tao

ICLRW 2025 Query-Dependent Prompt Optimization via Multi-Loop Offline Reinforcement Learning Yilun Kong, Hangyu Mao, Qi Zhao, Bin Zhang, Jingqing Ruan, Li Shen, Yongzhe Chang, Xueqian Wang, Rui Zhao, Dacheng Tao

NeurIPS 2025 R1-ShareVL: Incentivizing Reasoning Capabilities of Multimodal Large Language Models via Share-GRPO Huanjin Yao, Qixiang Yin, Jingyi Zhang, Min Yang, Yibo Wang, Wenhao Wu, Fei Su, Li Shen, Minghui Qiu, Dacheng Tao, Jiaxing Huang

ICML 2025 Restoring Calibration for Aligned Large Language Models: A Calibration-Aware Fine-Tuning Approach Jiancong Xiao, Bojian Hou, Zhanliang Wang, Ruochen Jin, Qi Long, Weijie J Su, Li Shen

ICML 2025 Retrieval-Augmented Perception: High-Resolution Image Perception Meets Visual RAG Wenbin Wang, Yongcheng Jing, Liang Ding, Yingjie Wang, Li Shen, Yong Luo, Bo Du, Dacheng Tao

NeurIPS 2025 RoMa: A Robust Model Watermarking Scheme for Protecting IP in Diffusion Models Yingsha Xie, Rui Min, Zeyu Qin, Fei Ma, Li Shen, Fei Yu, Xiaochun Cao

NeurIPS 2025 Robust Policy Expansion for Offline-to-Online RL Under Diverse Data Corruption Longxiang He, Deheng Ye, Junbo Tan, Xueqian Wang, Li Shen

NeurIPS 2025 RobustMerge: Parameter-Efficient Model Merging for MLLMs with Direction Robustness Fanhu Zeng, Haiyang Guo, Fei Zhu, Li Shen, Hao Tang

ICML 2025 Safety Reasoning with Guidelines Haoyu Wang, Zeyu Qin, Li Shen, Xueqian Wang, Dacheng Tao, Minhao Cheng

NeurIPS 2025 Self-Verification Provably Prevents Model Collapse in Recursive Synthetic Training Shi Fu, Yingjie Wang, Yuzhu Chen, Li Shen, Dacheng Tao

ICLRW 2025 Stable-SPAM: How to Train in 4-Bit More Stably than 16-Bit Adam Tianjin Huang, Haotian Hu, Zhenyu Zhang, Gaojie Jin, Xiang Li, Li Shen, Tianlong Chen, Lu Liu, Qingsong Wen, Zhangyang Wang, Shiwei Liu

NeurIPS 2025 Stochastic Regret Guarantees for Online Zeroth- and First-Order Bilevel Optimization Parvin Nazari, Bojian Hou, Davoud Ataee Tarzanagh, Li Shen, George Michailidis

NeurIPS 2025 Tackling Continual Offline RL Through Selective Weights Activation on Aligned Spaces Jifeng Hu, Sili Huang, Li Shen, Zhejian Yang, Shengchao Hu, Shisong Tang, Hechang Chen, Lichao Sun, Yi Chang, Dacheng Tao

ICML 2025 Targeted Low-Rank Refinement: Enhancing Sparse Language Models with Precision Li Shen, Anke Tang, Yong Luo, Tao Sun, Han Hu, Xiaochun Cao

ICLR 2025 Understanding the Stability-Based Generalization of Personalized Federated Learning Yingqi Liu, Qinglun Li, Jie Tan, Yifan Shi, Li Shen, Xiaochun Cao

NeurIPS 2025 Unveiling the Power of Multiple Gossip Steps: A Stability-Based Generalization Analysis in Decentralized Training Qinglun Li, Yingqi Liu, Miao Zhang, Xiaochun Cao, Quanjun Yin, Li Shen

NeurIPS 2025 Vad-R1: Towards Video Anomaly Reasoning via Perception-to-Cognition Chain-of-Thought Chao Huang, Benfeng Wang, Wei Wang, Jie Wen, Chengliang Liu, Li Shen, Xiaochun Cao

NeurIPS 2025 Value-Guided Decision Transformer: A Unified Reinforcement Learning Framework for Online and Offline Settings Hongling Zheng, Li Shen, Yong Luo, Deheng Ye, Shuhan Xu, Bo Du, Jialie Shen, Dacheng Tao

ICML 2025 Vulnerability-Aware Alignment: Mitigating Uneven Forgetting in Harmful Fine-Tuning Liang Chen, Xueting Han, Li Shen, Jing Bai, Kam-Fai Wong

NeurIPS 2024 A Huber Loss Minimization Approach to Mean Estimation Under User-Level Differential Privacy Puning Zhao, Lifeng Lai, Li Shen, Qingming Li, Jiafei Wu, Zhe Liu

ICLR 2024 A Unified and General Framework for Continual Learning Zhenyi Wang, Yan Li, Li Shen, Heng Huang

NeurIPS 2024 A-FedPD: Aligning Dual-Drift Is All Federated Primal-Dual Learning Needs Yan Sun, Li Shen, Dacheng Tao

ICLR 2024 AdaMerging: Adaptive Model Merging for Multi-Task Learning Enneng Yang, Zhenyi Wang, Li Shen, Shiwei Liu, Guibing Guo, Xingwei Wang, Dacheng Tao

ICLR 2024 DREAM: Dual Structured Exploration with Mixup for Open-Set Graph Domain Adaption Nan Yin, Mengzhu Wang, Zhenghan Chen, Li Shen, Huan Xiong, Bin Gu, Xiao Luo

CVPR 2024 Decentralized Directed Collaboration for Personalized Federated Learning Yingqi Liu, Yifan Shi, Qinglun Li, Baoyuan Wu, Xueqian Wang, Li Shen

NeurIPS 2024 Decomposed Prompt Decision Transformer for Efficient Unseen Task Generalization Hongling Zheng, Li Shen, Yong Luo, Tongliang Liu, Jialie Shen, Dacheng Tao

ACML 2024 Dude: Dual Distribution-Aware Context Prompt Learning for Large Vision-Language Model Duy Minh Ho Nguyen, An Thai Le, Trung Quoc Nguyen, Nghiem Tuong Diep, Tai Nguyen, Duy Duong-Tran, Jan Peters, Li Shen, Mathias Niepert, Daniel Sonntag

CVPR 2024 Embodied Multi-Modal Agent Trained by an LLM from a Parallel TextWorld Yijun Yang, Tianyi Zhou, Kanxue Li, Dapeng Tao, Lusong Li, Li Shen, Xiaodong He, Jing Jiang, Yuhui Shi

AAAI 2024 Evaluate Geometry of Radiance Fields with Low-Frequency Color Prior Qihang Fang, Yafei Song, Keqiang Li, Li Shen, Huaiyu Wu, Gang Xiong, Liefeng Bo

CVPR 2024 FREE: Faster and Better Data-Free Meta-Learning Yongxian Wei, Zixuan Hu, Zhenyi Wang, Li Shen, Chun Yuan, Dacheng Tao

NeurIPS 2024 Fairness-Aware Estimation of Graphical Models Zhuoping Zhou, Davoud Ataee Tarzanagh, Bojian Hou, Qi Long, Li Shen

ICML 2024 Generalization Analysis of Stochastic Weight Averaging with General Sampling Peng Wang, Li Shen, Zerui Tao, Shuaida He, Dacheng Tao

ICML 2024 HarmoDT: Harmony Multi-Task Decision Transformer for Offline Reinforcement Learning Shengchao Hu, Ziqing Fan, Li Shen, Ya Zhang, Yanfeng Wang, Dacheng Tao

ICLR 2024 Improving Non-Transferable Representation Learning by Harnessing Content and Style Ziming Hong, Zhenyi Wang, Li Shen, Yu Yao, Zhuo Huang, Shiming Chen, Chuanwu Yang, Mingming Gong, Tongliang Liu

NeurIPS 2024 Is Mamba Compatible with Trajectory Optimization in Offline Reinforcement Learning? Yang Dai, Oubo Ma, Longfei Zhang, Xingxing Liang, Shengchao Hu, Mengzhu Wang, Shouling Ji, Jincai Huang, Li Shen

ICLR 2024 Learning Multi-Agent Communication from Graph Modeling Perspective Shengchao Hu, Li Shen, Ya Zhang, Dacheng Tao

MLJ 2024 Local AdaGrad-Type Algorithm for Stochastic Convex-Concave Optimization Luofeng Liao, Li Shen, Jia Duan, Mladen Kolar, Dacheng Tao

ICML 2024 Merging Multi-Task Models via Weight-Ensembling Mixture of Experts Anke Tang, Li Shen, Yong Luo, Nan Yin, Lefei Zhang, Dacheng Tao

IJCAI 2024 MuEP: A Multimodal Benchmark for Embodied Planning with Foundation Models Kanxue Li, Baosheng Yu, Qi Zheng, Yibing Zhan, Yuhui Zhang, Tianle Zhang, Yijun Yang, Yue Chen, Lei Sun, Qiong Cao, Li Shen, Lusong Li, Dapeng Tao, Xiaodong He

AAAI 2024 Neural Network Approximation for Pessimistic Offline Reinforcement Learning Di Wu, Yuling Jiao, Li Shen, Haizhao Yang, Xiliang Lu

AISTATS 2024 Online Bilevel Optimization: Regret Analysis of Online Alternating Gradient Methods Davoud Ataee Tarzanagh, Parvin Nazari, Bojian Hou, Li Shen, Laura Balzano

CVPR 2024 POCE: Primal Policy Optimization with Conservative Estimation for Multi-Constraint Offline Reinforcement Learning Jiayi Guan, Li Shen, Ao Zhou, Lusong Li, Han Hu, Xiaodong He, Guang Chen, Changjun Jiang

ICLR 2024 Parameter-Efficient Multi-Task Model Fusion with Partial Linearization Anke Tang, Li Shen, Yong Luo, Yibing Zhan, Han Hu, Bo Du, Yixin Chen, Dacheng Tao

ICML 2024 Q-Value Regularized Transformer for Offline Reinforcement Learning Shengchao Hu, Ziqing Fan, Chaoqin Huang, Li Shen, Ya Zhang, Yanfeng Wang, Dacheng Tao

ICML 2024 Representation Surgery for Multi-Task Model Merging Enneng Yang, Li Shen, Zhenyi Wang, Guibing Guo, Xiaojun Chen, Xingwei Wang, Dacheng Tao

TMLR 2024 Revisiting Discrete Soft Actor-Critic Haibin Zhou, Tong Wei, Zichuan Lin, Junyou Li, Junliang Xing, Yuanchun Shi, Li Shen, Chao Yu, Deheng Ye

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

CVPR 2024 Sheared Backpropagation for Fine-Tuning Foundation Models Zhiyuan Yu, Li Shen, Liang Ding, Xinmei Tian, Yixin Chen, Dacheng Tao

ICLRW 2024 Simple Permutations Can Fool Llama: Permutation Attack and Defense for Large Language Models Liang Chen, Yatao Bian, Li Shen, Kam-Fai Wong

ICML 2024 Sparse Model Inversion: Efficient Inversion of Vision Transformers for Data-Free Applications Zixuan Hu, Yongxian Wei, Li Shen, Zhenyi Wang, Lei Li, Chun Yuan, 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

ICML 2024 Task Groupings Regularization: Data-Free Meta-Learning with Heterogeneous Pre-Trained Models Yongxian Wei, Zixuan Hu, Li Shen, Zhenyi Wang, Yu Li, Chun Yuan, Dacheng Tao

ECCV 2024 Training a Secure Model Against Data-Free Model Extraction Zhenyi Wang, Li Shen, Junfeng Guo, Tiehang Duan, Siyu Luan, Tongliang Liu, Mingchen Gao

NeurIPS 2024 Uncovering, Explaining, and Mitigating the Superficial Safety of Backdoor Defense Rui Min, Zeyu Qin, Nevin L. Zhang, Li Shen, Minhao Cheng

ECCV 2024 Unmasking Bias in Diffusion Model Training Hu Yu, Li Shen, Jie Huang, Hongsheng Li, Feng Zhao

TMLR 2024 Visual Prompt Based Personalized Federated Learning Guanghao Li, Wansen Wu, Yan Sun, Li Shen, Baoyuan Wu, Dacheng Tao

CVPR 2024 Your Transferability Barrier Is Fragile: Free-Lunch for Transferring the Non-Transferable Learning Ziming Hong, Li Shen, Tongliang Liu

AAAI 2023 AdaTask: A Task-Aware Adaptive Learning Rate Approach to Multi-Task Learning Enneng Yang, Junwei Pan, Ximei Wang, Haibin Yu, Li Shen, Xihua Chen, Lei Xiao, Jie Jiang, Guibing Guo

NeurIPS 2023 An Efficient Dataset Condensation Plugin and Its Application to Continual Learning Enneng Yang, Li Shen, Zhenyi Wang, Tongliang Liu, Guibing Guo

CVPR 2023 Architecture, Dataset and Model-Scale Agnostic Data-Free Meta-Learning Zixuan Hu, Li Shen, Zhenyi Wang, Tongliang Liu, Chun Yuan, Dacheng Tao

ICML 2023 Are Large Kernels Better Teachers than Transformers for ConvNets? Tianjin Huang, Lu Yin, Zhenyu Zhang, Li Shen, Meng Fang, Mykola Pechenizkiy, Zhangyang Wang, Shiwei Liu

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

ICML 2023 COCO: A Coupled Contrastive Framework for Unsupervised Domain Adaptive Graph Classification Nan Yin, Li Shen, Mengzhu Wang, Long Lan, Zeyu Ma, Chong Chen, Xian-Sheng Hua, Xiao Luo

CVPR 2023 Compressing Volumetric Radiance Fields to 1 MB Lingzhi Li, Zhen Shen, Zhongshu Wang, Li Shen, Liefeng Bo

ICCV 2023 Data Augmented Flatness-Aware Gradient Projection for Continual Learning Enneng Yang, Li Shen, Zhenyi Wang, Shiwei Liu, Guibing Guo, Xingwei Wang

CVPRW 2023 DeSRF: Deformable Stylized Radiance Field Shiyao Xu, Lingzhi Li, Li Shen, Zhouhui Lian

NeurIPS 2023 Defending Against Data-Free Model Extraction by Distributionally Robust Defensive Training Zhenyi Wang, Li Shen, Tongliang Liu, Tiehang Duan, Yanjun Zhu, Donglin Zhan, David Doermann, Mingchen Gao

ICML 2023 Dynamic Regularized Sharpness Aware Minimization in Federated Learning: Approaching Global Consistency and Smooth Landscape Yan Sun, Li Shen, Shixiang Chen, Liang Ding, Dacheng Tao

NeurIPS 2023 Dynamic Sparsity Is Channel-Level Sparsity Learner Lu Yin, Gen Li, Meng Fang, Li Shen, Tianjin Huang, Zhangyang "Atlas" Wang, Vlado Menkovski, Xiaolong Ma, Mykola Pechenizkiy, Shiwei Liu

ECML-PKDD 2023 Enhancing Adversarial Training via Reweighting Optimization Trajectory Tianjin Huang, Shiwei Liu, Tianlong Chen, Meng Fang, Li Shen, Vlado Menkovski, Lu Yin, Yulong Pei, Mykola Pechenizkiy

ICCV 2023 Enhancing Fine-Tuning Based Backdoor Defense with Sharpness-Aware Minimization Mingli Zhu, Shaokui Wei, Li Shen, Yanbo Fan, Baoyuan Wu

AAAI 2023 Evaluating Model-Free Reinforcement Learning Toward Safety-Critical Tasks Linrui Zhang, Qin Zhang, Li Shen, Bo Yuan, Xueqian Wang, Dacheng Tao

NeurIPS 2023 Fair Canonical Correlation Analysis Zhuoping Zhou, Davoud Ataee Tarzanagh, Bojian Hou, Boning Tong, Jia Xu, Yanbo Feng, Qi Long, Li Shen

UAI 2023 Fairness-Aware Class Imbalanced Learning on Multiple Subgroups Davoud Ataee Tarzanagh, Bojian Hou, Boning Tong, Qi Long, Li Shen

AAAI 2023 FedABC: Targeting Fair Competition in Personalized Federated Learning Dui Wang, Li Shen, Yong Luo, Han Hu, Kehua Su, Yonggang Wen, Dacheng Tao

TMLR 2023 FedDAG: Federated DAG Structure Learning Erdun Gao, Junjia Chen, Li Shen, Tongliang Liu, Mingming Gong, Howard Bondell

ICLR 2023 FedSpeed: Larger Local Interval, Less Communication Round, and Higher Generalization Accuracy Yan Sun, Li Shen, Tiansheng Huang, Liang Ding, Dacheng Tao

NeurIPS 2023 Federated Learning with Manifold Regularization and Normalized Update Reaggregation Xuming An, Li Shen, Han Hu, Yong Luo

NeurIPS 2023 FlatMatch: Bridging Labeled Data and Unlabeled Data with Cross-Sharpness for Semi-Supervised Learning Zhuo Huang, Li Shen, Jun Yu, Bo Han, Tongliang Liu

TMLR 2023 Fusion of Global and Local Knowledge for Personalized Federated Learning Tiansheng Huang, Li Shen, Yan Sun, Weiwei Lin, Dacheng Tao

ICCV 2023 Global Balanced Experts for Federated Long-Tailed Learning Yaopei Zeng, Lei Liu, Li Liu, Li Shen, Shaoguo Liu, Baoyuan Wu

ICLR 2023 Harnessing Out-of-Distribution Examples via Augmenting Content and Style Zhuo Huang, Xiaobo Xia, Li Shen, Bo Han, Mingming Gong, Chen Gong, Tongliang Liu

ICML 2023 Improving the Model Consistency of Decentralized Federated Learning Yifan Shi, Li Shen, Kang Wei, Yan Sun, Bo Yuan, Xueqian Wang, 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

CoLLAs 2023 Learning Meta Representations for Agents in Multi-Agent Reinforcement Learning Shenao Zhang, Li Shen, Lei Han, Li Shen

CoLLAs 2023 Learning Meta Representations for Agents in Multi-Agent Reinforcement Learning Shenao Zhang, Li Shen, Lei Han, Li Shen

ICML 2023 Learning to Learn from APIs: Black-Box Data-Free Meta-Learning Zixuan Hu, Li Shen, Zhenyi Wang, Baoyuan Wu, Chun Yuan, Dacheng Tao

CVPR 2023 Make Landscape Flatter in Differentially Private Federated Learning Yifan Shi, Yingqi Liu, Kang Wei, Li Shen, Xueqian Wang, Dacheng Tao

CVPR 2023 MetaMix: Towards Corruption-Robust Continual Learning with Temporally Self-Adaptive Data Transformation Zhenyi Wang, Li Shen, Donglin Zhan, Qiuling Suo, Yanjun Zhu, Tiehang Duan, Mingchen Gao

AAAI 2023 Offline Quantum Reinforcement Learning in a Conservative Manner Zhihao Cheng, Kaining Zhang, Li Shen, Dacheng Tao

ICCV 2023 Rethinking the Role of Pre-Trained Networks in Source-Free Domain Adaptation Wenyu Zhang, Li Shen, Chuan-Sheng Foo

CVPR 2023 Robust Generalization Against Photon-Limited Corruptions via Worst-Case Sharpness Minimization Zhuo Huang, Miaoxi Zhu, Xiaobo Xia, Li Shen, Jun Yu, Chen Gong, Bo Han, Bo Du, Tongliang Liu

ICLRW 2023 SaFormer: A Conditional Sequence Modeling Approach to Offline Safe Reinforcement Learning Qin Zhang, Linrui Zhang, Li Shen, Haoran Xu, Bowen Wang, Bo Yuan, Yongzhe Chang, Xueqian Wang

NeurIPS 2023 Stability and Generalization of the Decentralized Stochastic Gradient Descent Ascent Algorithm Miaoxi Zhu, Li Shen, Bo Du, Dacheng Tao

ICLR 2023 Towards One-Shot Neural Combinatorial Solvers: Theoretical and Empirical Notes on the Cardinality-Constrained Case Runzhong Wang, Li Shen, Yiting Chen, Xiaokang Yang, Dacheng Tao, Junchi Yan

NeurIPS 2023 Towards Stable Backdoor Purification Through Feature Shift Tuning Rui Min, Zeyu Qin, Li Shen, Minhao Cheng

NeurIPS 2023 Understanding How Consistency Works in Federated Learning via Stage-Wise Relaxed Initialization Yan Sun, Li Shen, Dacheng Tao

NeurIPS 2022 Boosting the Transferability of Adversarial Attacks with Reverse Adversarial Perturbation Zeyu Qin, Yanbo Fan, Yi Liu, Li Shen, Yong Zhang, Jue Wang, Baoyuan Wu

ICML 2022 Deep Neural Network Fusion via Graph Matching with Applications to Model Ensemble and Federated Learning Chang Liu, Chenfei Lou, Runzhong Wang, Alan Yuhan Xi, Li Shen, Junchi Yan

CVPR 2022 Depth-Aware Generative Adversarial Network for Talking Head Video Generation Fa-Ting Hong, Longhao Zhang, Li Shen, Dan Xu

ICML 2022 DisPFL: Towards Communication-Efficient Personalized Federated Learning via Decentralized Sparse Training Rong Dai, Li Shen, Fengxiang He, Xinmei Tian, Dacheng Tao

IJCAI 2022 Few-Shot Adaptation of Pre-Trained Networks for Domain Shift Wenyu Zhang, Li Shen, Wanyue Zhang, Chuan-Sheng Foo

CVPR 2022 Fine-Tuning Global Model via Data-Free Knowledge Distillation for Non-IID Federated Learning Lin Zhang, Li Shen, Liang Ding, Dacheng Tao, Ling-Yu Duan

ICML 2022 Improving Task-Free Continual Learning by Distributionally Robust Memory Evolution Zhenyi Wang, Li Shen, Le Fang, Qiuling Suo, Tiehang Duan, Mingchen Gao

ICLRW 2022 Learning Meta Representations for Agents in Multi-Agent Reinforcement Learning Shenao Zhang, Li Shen, Lei Han, Li Shen

ICLRW 2022 Learning Meta Representations for Agents in Multi-Agent Reinforcement Learning Shenao Zhang, Li Shen, Lei Han, Li Shen

CVPR 2022 Learning to Learn and Remember Super Long Multi-Domain Task Sequence Zhenyi Wang, Li Shen, Tiehang Duan, Donglin Zhan, Le Fang, Mingchen Gao

NeurIPS 2022 Make Sharpness-Aware Minimization Stronger: A Sparsified Perturbation Approach Peng Mi, Li Shen, Tianhe Ren, Yiyi Zhou, Xiaoshuai Sun, Rongrong Ji, Dacheng Tao

UAI 2022 Meta-Learning Without Data via Wasserstein Distributionally-Robust Model Fusion Zhenyi Wang, Xiaoyang Wang, Li Shen, Qiuling Suo, Kaiqiang Song, Dong Yu, Yan Shen, Mingchen Gao

ECCV 2022 Meta-Learning with Less Forgetting on Large-Scale Non-Stationary Task Distributions Zhenyi Wang, Li Shen, Le Fang, Qiuling Suo, Donglin Zhan, Tiehang Duan, Mingchen Gao

NeurIPS 2022 MissDAG: Causal Discovery in the Presence of Missing Data with Continuous Additive Noise Models Erdun Gao, Ignavier Ng, Mingming Gong, Li Shen, Wei Huang, Tongliang Liu, Kun Zhang, Howard Bondell

IJCAI 2022 Penalized Proximal Policy Optimization for Safe Reinforcement Learning Linrui Zhang, Li Shen, Long Yang, Shixiang Chen, Xueqian Wang, Bo Yuan, Dacheng Tao

ICLR 2022 Robust Unlearnable Examples: Protecting Data Privacy Against Adversarial Learning Shaopeng Fu, Fengxiang He, Yang Liu, Li Shen, Dacheng Tao

IJCAI 2022 Robust Weight Perturbation for Adversarial Training Chaojian Yu, Bo Han, Mingming Gong, Li Shen, Shiming Ge, Du Bo, Tongliang Liu

NeurIPS 2022 Streaming Radiance Fields for 3D Video Synthesis Lingzhi Li, Zhen Shen, Zhongshu Wang, Li Shen, Ping Tan

ICLR 2022 The Unreasonable Effectiveness of Random Pruning: Return of the Most Naive Baseline for Sparse Training Shiwei Liu, Tianlong Chen, Xiaohan Chen, Li Shen, Decebal Constantin Mocanu, Zhangyang Wang, Mykola Pechenizkiy

MLJ 2022 Towards Harnessing Feature Embedding for Robust Learning with Noisy Labels Chuang Zhang, Li Shen, Jian Yang, Chen Gong

JMLR 2022 Towards Practical Adam: Non-Convexity, Convergence Theory, and Mini-Batch Acceleration Congliang Chen, Li Shen, Fangyu Zou, Wei Liu

ICML 2022 Understanding Robust Overfitting of Adversarial Training and Beyond Chaojian Yu, Bo Han, Li Shen, Jun Yu, Chen Gong, Mingming Gong, Tongliang Liu

AISTATS 2021 Communication Efficient Primal-Dual Algorithm for Nonconvex Nonsmooth Distributed Optimization Congliang Chen, Jiawei Zhang, Li Shen, Peilin Zhao, Zhiquan Luo

NeurIPS 2021 Sparse Training via Boosting Pruning Plasticity with Neuroregeneration Shiwei Liu, Tianlong Chen, Xiaohan Chen, Zahra Atashgahi, Lu Yin, Huanyu Kou, Li Shen, Mykola Pechenizkiy, Zhangyang Wang, Decebal Constantin Mocanu

AAAI 2020 Adaptive Activation Network and Functional Regularization for Efficient and Flexible Deep Multi-Task Learning Yingru Liu, Xuewen Yang, Dongliang Xie, Xin Wang, Li Shen, Haozhi Huang, Niranjan Balasubramanian

ICML 2020 Communication-Efficient Distributed Stochastic AUC Maximization with Deep Neural Networks Zhishuai Guo, Mingrui Liu, Zhuoning Yuan, Li Shen, Wei Liu, Tianbao Yang

IJCAI 2019 Discrete Trust-Aware Matrix Factorization for Fast Recommendation Guibing Guo, Enneng Yang, Li Shen, Xiaochun Yang, Xiaodong He

ICML 2018 An Algorithmic Framework of Variable Metric Over-Relaxed Hybrid Proximal Extra-Gradient Method Li Shen, Peng Sun, Yitong Wang, Wei Liu, Tong Zhang

ECCV 2018 Comparator Networks Weidi Xie, Li Shen, Andrew Zisserman

NeurIPS 2018 Gather-Excite: Exploiting Feature Context in Convolutional Neural Networks Jie Hu, Li Shen, Samuel Albanie, Gang Sun, Andrea Vedaldi

AAAI 2017 Adaptive Proximal Average Approximation for Composite Convex Minimization Li Shen, Wei Liu, Junzhou Huang, Yu-Gang Jiang, Shiqian Ma

ICML 2017 GSOS: Gauss-Seidel Operator Splitting Algorithm for Multi-Term Nonsmooth Convex Composite Optimization Li Shen, Wei Liu, Ganzhao Yuan, Shiqian Ma

AAAI 2016 Co-Occurrence Feature Learning for Skeleton Based Action Recognition Using Regularized Deep LSTM Networks Wentao Zhu, Cuiling Lan, Junliang Xing, Wenjun Zeng, Yanghao Li, Li Shen, Xiaohui Xie

ECCV 2016 Relay Backpropagation for Effective Learning of Deep Convolutional Neural Networks Li Shen, Zhouchen Lin, Qingming Huang

IJCAI 2015 Adaptive Sharing for Image Classification Li Shen, Gang Sun, Zhouchen Lin, Qingming Huang, Enhua Wu

CVPR 2015 Shadow Optimization from Structured Deep Edge Detection Li Shen, Teck Wee Chua, Karianto Leman

CVPR 2014 A New Perspective on Material Classification and Ink Identification Rakesh Shiradkar, Li Shen, George Landon, Sim Heng Ong, Ping Tan

CVPR 2013 Multi-Level Discriminative Dictionary Learning Towards Hierarchical Visual Categorization Li Shen, Shuhui Wang, Gang Sun, Shuqiang Jiang, Qingming Huang

NeurIPS 2012 High-Order Multi-Task Feature Learning to Identify Longitudinal Phenotypic Markers for Alzheimer's Disease Progression Prediction Hua Wang, Feiping Nie, Heng Huang, Jingwen Yan, Sungeun Kim, Shannon Risacher, Andrew Saykin, Li Shen

CVPR 2012 Sparse Bayesian Multi-Task Learning for Predicting Cognitive Outcomes from Neuroimaging Measures in Alzheimer's Disease Jing Wan, Zhilin Zhang, Jingwen Yan, Taiyong Li, Bhaskar D. Rao, Shiaofen Fang, Sungeun Kim, Shannon L. Risacher, Andrew J. Saykin, Li Shen

CVPR 2011 Intrinsic Images Decomposition Using a Local and Global Sparse Representation of Reflectance Li Shen, Chuohao Yeo

ICCV 2011 Sparse Multi-Task Regression and Feature Selection to Identify Brain Imaging Predictors for Memory Performance Hua Wang, Feiping Nie, Heng Huang, Shannon L. Risacher, Chris H. Q. Ding, Andrew J. Saykin, Li Shen

CVPR 2009 Photometric Stereo and Weather Estimation Using Internet Images Li Shen, Ping Tan

CVPR 2008 Intrinsic Image Decomposition with Non-Local Texture Cues Li Shen, Ping Tan, Stephen Lin

CVPR 2006 Spatial Reflectance Recovery Under Complex Illumination from Sparse Images Li Shen, Haruo Takemura