Adaptive Proximal Average Approximation for Composite Convex Minimization. - Li Shen 008; Wei Liu 005; Junzhou Huang; Yu-Gang Jiang 001; Shiqian Ma (AAAI, 2017)

A Generalized Matrix Splitting Algorithm. - Ganzhao Yuan; Wei-Shi Zheng 001; Li Shen 008; Bernard Ghanem (CoRR, 2018)

A Decomposition Algorithm for the Sparse Generalized Eigenvalue Problem. - Ganzhao Yuan; Li Shen 008; Wei-Shi Zheng 001 (CVPR, 2019)

Discrete Trust-aware Matrix Factorization for Fast Recommendation. - Guibing Guo; Enneng Yang; Li Shen 008; Xiaochun Yang 001; Xiaodong He 001 (IJCAI, 2019)

MAP Inference via L2-Sphere Linear Program Reformulation. - Baoyuan Wu; Li Shen 008; Bernard Ghanem; Tong Zhang 001 (CoRR, 2019)

Adaptive Activation Network and Functional Regularization for Efficient and Flexible Deep Multi-Task Learning. - Yingru Liu; Xuewen Yang; Dongliang Xie; Xin Wang 001; Li Shen 008; Haozhi Huang 001; Niranjan Balasubramanian (AAAI, 2020)

A Block Decomposition Algorithm for Sparse Optimization. - Ganzhao Yuan; Li Shen 008; Wei-Shi Zheng 001 (KDD, 2020)

Generalized Embedding Machines for Recommender Systems. - Enneng Yang; Xin Xin 007; Li Shen 008; Guibing Guo (CoRR, 2020)

Task-agnostic Temporally Consistent Facial Video Editing. - Meng Cao 002; Haozhi Huang 001; Hao Wang 050; Xuan Wang 009; Li Shen 008; Sheng Wang; Linchao Bao; Zhifeng Li 001; Jiebo Luo 001 (CoRR, 2020)

Adaptive Compact Attention For Few-shot Video-to-video Translation. - Risheng Huang; Li Shen 008; Xuan Wang 009; Cheng Lin; Hao-Zhi Huang 001 (CoRR, 2020)

MAP Inference Via ℓ 2-Sphere Linear Program Reformulation. - Baoyuan Wu; Li Shen 008; Tong Zhang 001; Bernard Ghanem (Int. J. Comput. Vis., 2020)

DAG-GAN: Causal Structure Learning with Generative Adversarial Nets. - Yinghua Gao; Li Shen 008; Shu-Tao Xia (ICASSP, 2021)

Sparse Training via Boosting Pruning Plasticity with Neuroregeneration. - Shiwei Liu 003; Tianlong Chen 001; Xiaohan Chen; Zahra Atashgahi; Lu Yin 006; Huanyu Kou; Li Shen 008; Mykola Pechenizkiy; Zhangyang Wang; Decebal Constantin Mocanu (NeurIPS, 2021)

Local AdaGrad-Type Algorithm for Stochastic Convex-Concave Minimax Problems. - Luofeng Liao; Li Shen 008; Jia Duan; Mladen Kolar; Dacheng Tao (CoRR, 2021)

End-to-End Adaptive Monte Carlo Denoising and Super-Resolution. - Xinyue Wei; Haozhi Huang 001; Yujin Shi; Hongliang Yuan; Li Shen 008; Jue Wang 001 (CoRR, 2021)

Federated Causal Discovery. - Erdun Gao; Junjia Chen; Li Shen 008; Tongliang Liu; Mingming Gong; Howard D. Bondell (CoRR, 2021)

Spatial-Temporal-Fusion BNN: Variational Bayesian Feature Layer. - Shiye Lei; Zhuozhuo Tu; Leszek Rutkowski; Feng Zhou 011; Li Shen 008; Fengxiang He; Dacheng Tao (CoRR, 2021)

DGL-GAN: Discriminator Guided Learning for GAN Compression. - Yuesong Tian; Li Shen 008; Dacheng Tao; Zhifeng Li 001; Wei Liu 005 (CoRR, 2021)

Knowledge Distillation With Multi-Objective Divergence Learning. - Ye Tian; Meiling Chen; Li Shen 008; Bo Jiang; Zhifeng Li 001 (IEEE Signal Process. Lett., 2021)

UniFaceGAN: A Unified Framework for Temporally Consistent Facial Video Editing. - Meng Cao 002; Haozhi Huang 001; Hao Wang 050; Xuan Wang 009; Li Shen 008; Sheng Wang; Linchao Bao; Zhifeng Li 001; Jiebo Luo 001 (IEEE Trans. Image Process., 2021)

Quantized Adam with Error Feedback. - Congliang Chen; Li Shen 008; Hao-Zhi Huang 001; Wei Liu 005 (ACM Trans. Intell. Syst. Technol., 2021)

On the Complementarity between Pre-Training and Random-Initialization for Resource-Rich Machine Translation. - Changtong Zan; Liang Ding 006; Li Shen 008; Yu Cao 014; Weifeng Liu 001; Dacheng Tao (COLING, 2022)

Learning to Learn and Remember Super Long Multi-Domain Task Sequence. - Zhenyi Wang 001; Li Shen 008; Tiehang Duan; Donglin Zhan; Le Fang; Mingchen Gao (CVPR, 2022)

Fine-tuning Global Model via Data-Free Knowledge Distillation for Non-IID Federated Learning. - Lin Zhang 014; Li Shen 008; Liang Ding 006; Dacheng Tao; Ling-Yu Duan (CVPR, 2022)

Meta-Learning with Less Forgetting on Large-Scale Non-Stationary Task Distributions. - Zhenyi Wang 001; Li Shen 008; Le Fang; Qiuling Suo; Donglin Zhan; Tiehang Duan; Mingchen Gao (ECCV (20), 2022)

Improving Sharpness-Aware Minimization with Fisher Mask for Better Generalization on Language Models. - Qihuang Zhong; Liang Ding 006; Li Shen 008; Peng Mi; Juhua Liu; Bo Du 001; Dacheng Tao (EMNLP (Findings), 2022)

Robust Unlearnable Examples: Protecting Data Privacy Against Adversarial Learning. - Shaopeng Fu; Fengxiang He; Yang Liu 039; Li Shen 008; Dacheng Tao (ICLR, 2022)

The Unreasonable Effectiveness of Random Pruning: Return of the Most Naive Baseline for Sparse Training. - Shiwei Liu 003; Tianlong Chen 001; Xiaohan Chen; Li Shen 008; Decebal Constantin Mocanu; Zhangyang Wang; Mykola Pechenizkiy (ICLR, 2022)

DisPFL: Towards Communication-Efficient Personalized Federated Learning via Decentralized Sparse Training. - Rong Dai; Li Shen 008; Fengxiang He; Xinmei Tian 001; Dacheng Tao (ICML, 2022)

Deep Neural Network Fusion via Graph Matching with Applications to Model Ensemble and Federated Learning. - Chang Liu 021; Chenfei Lou; Runzhong Wang; Alan Yuhan Xi; Li Shen 008; Junchi Yan (ICML, 2022)

Improving Task-free Continual Learning by Distributionally Robust Memory Evolution. - Zhenyi Wang 001; Li Shen 008; Le Fang; Qiuling Suo; Tiehang Duan; Mingchen Gao (ICML, 2022)

Understanding Robust Overfitting of Adversarial Training and Beyond. - Chaojian Yu; Bo Han 003; Li Shen 008; Jun Yu 001; Chen Gong 002; Mingming Gong; Tongliang Liu (ICML, 2022)

Robust Weight Perturbation for Adversarial Training. - Chaojian Yu; Bo Han 003; Mingming Gong; Li Shen 008; Shiming Ge; Du Bo; Tongliang Liu (IJCAI, 2022)

Penalized Proximal Policy Optimization for Safe Reinforcement Learning. - Linrui Zhang; Li Shen 008; Long Yang 004; Shixiang Chen; Xueqian Wang 001; Bo Yuan 003; Dacheng Tao (IJCAI, 2022)

Safety Correction from Baseline: Towards the Risk-aware Policy in Robotics via Dual-agent Reinforcement Learning. - Linrui Zhang; Zichen Yan; Li Shen 008; Shoujie Li; Xueqian Wang 001; Dacheng Tao (IROS, 2022)

DEAL: An Unsupervised Domain Adaptive Framework for Graph-level Classification. - Nan Yin; Li Shen 008; Baopu Li; Mengzhu Wang; Xiao Luo 001; Chong Chen 002; Zhigang Luo; Xian-Sheng Hua 001 (ACM Multimedia, 2022)

MissDAG: Causal Discovery in the Presence of Missing Data with Continuous Additive Noise Models. - Erdun Gao; Ignavier Ng; Mingming Gong; Li Shen 008; Wei Huang; Tongliang Liu; Kun Zhang 001; Howard D. Bondell (NeurIPS, 2022)

Make Sharpness-Aware Minimization Stronger: A Sparsified Perturbation Approach. - Peng Mi; Li Shen 008; Tianhe Ren; Yiyi Zhou; Xiaoshuai Sun; Rongrong Ji; Dacheng Tao (NeurIPS, 2022)

Boosting the Transferability of Adversarial Attacks with Reverse Adversarial Perturbation. - Zeyu Qin; Yanbo Fan; Yi Liu; Li Shen 008; Yong Zhang 034; Jue Wang 001; Baoyuan Wu (NeurIPS, 2022)

Enhancing Top-N Item Recommendations by Peer Collaboration. - Yang Sun; Fajie Yuan; Min Yang 007; Alexandros Karatzoglou; Li Shen 008; Xiaoyan Zhao 005 (SIGIR, 2022)

Meta-learning without data via Wasserstein distributionally-robust model fusion. - Zhenyi Wang 001; Xiaoyang Wang; Li Shen 008; Qiuling Suo; Kaiqiang Song; Dong Yu 001; Yan Shen 002; Mingchen Gao (UAI, 2022)

Achieving Personalized Federated Learning with Sparse Local Models. - Tiansheng Huang; Shiwei Liu 003; Li Shen 008; Fengxiang He; Weiwei Lin 001; Dacheng Tao (CoRR, 2022)

Robust Unlearnable Examples: Protecting Data Against Adversarial Learning. - Shaopeng Fu; Fengxiang He; Yang Liu 039; Li Shen 008; Dacheng Tao (CoRR, 2022)

Bridging Cross-Lingual Gaps During Leveraging the Multilingual Sequence-to-Sequence Pretraining for Text Generation. - Changtong Zan; Liang Ding 006; Li Shen 008; Yu Cao 014; Weifeng Liu 001; Dacheng Tao (CoRR, 2022)

Robust Weight Perturbation for Adversarial Training. - Chaojian Yu; Bo Han 003; Mingming Gong; Li Shen 008; Shiming Ge; Bo Du 001; Tongliang Liu (CoRR, 2022)

SafeRL-Kit: Evaluating Efficient Reinforcement Learning Methods for Safe Autonomous Driving. - Linrui Zhang; Qin Zhang; Li Shen 008; Bo Yuan 003; Xueqian Wang 001 (CoRR, 2022)

Strength-Adaptive Adversarial Training. - Chaojian Yu; Dawei Zhou 004; Li Shen 008; Jun Yu 001; Bo Han 003; Mingming Gong; Nannan Wang 001; Tongliang Liu (CoRR, 2022)

Toward Efficient Language Model Pretraining and Downstream Adaptation via Self-Evolution: A Case Study on SuperGLUE. - Qihuang Zhong; Liang Ding 006; Yibing Zhan; Yu Qiao 001; Yonggang Wen 001; Li Shen 008; Juhua Liu; Baosheng Yu; Bo Du 001; Yixin Chen 001; Xinbo Gao 001; Chunyan Miao; et al. (CoRR, 2022)

On Transforming Reinforcement Learning by Transformer: The Development Trajectory. - Shengchao Hu; Li Shen 008; Ya Zhang 002; Yixin Chen 001; Dacheng Tao (CoRR, 2022)

Stochastic Client Selection for Federated Learning With Volatile Clients. - Tiansheng Huang; Weiwei Lin 001; Li Shen 008; Keqin Li 001; Albert Y. Zomaya (IEEE Internet Things J., 2022)

Towards harnessing feature embedding for robust learning with noisy labels. - Chuang Zhang; Li Shen 008; Jian Yang 003; Chen Gong 002 (Mach. Learn., 2022)

Informative pairs mining based adaptive metric learning for adversarial domain adaptation. - Mengzhu Wang; Paul Li; Li Shen 008; Ye Wang 023; Shanshan Wang 008; Wei Wang 335; Xiang Zhang 008; Junyang Chen 001; Zhigang Luo (Neural Networks, 2022)

AlphaGAN: Fully Differentiable Architecture Search for Generative Adversarial Networks. - Yuesong Tian; Li Shen 008; Li Shen 005; Guinan Su; Zhifeng Li 001; Wei Liu 005 (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

Offline Quantum Reinforcement Learning in a Conservative Manner. - Zhihao Cheng; Kaining Zhang; Li Shen 008; Dacheng Tao (AAAI, 2023)

FedABC: Targeting Fair Competition in Personalized Federated Learning. - Dui Wang; Li Shen 008; Yong Luo 002; Han Hu 003; Kehua Su; Yonggang Wen 001; Dacheng Tao (AAAI, 2023)

AdaTask: A Task-Aware Adaptive Learning Rate Approach to Multi-Task Learning. - Enneng Yang; Junwei Pan; Ximei Wang; Haibin Yu; Li Shen 008; Xihua Chen; Lei Xiao; Jie Jiang 015; Guibing Guo (AAAI, 2023)

Evaluating Model-Free Reinforcement Learning toward Safety-Critical Tasks. - Linrui Zhang; Qin Zhang; Li Shen 008; Bo Yuan 003; Xueqian Wang 001; Dacheng Tao (AAAI, 2023)

Provably Efficient Convergence of Primal-Dual Actor-Critic with Nonlinear Function Approximation. - Jing Dong 008; Li Shen 008; Yinggan Xu; Baoxiang Wang 001 (AAMAS, 2023)

Learning Meta Representations for Agents in Multi-Agent Reinforcement Learning. - Shenao Zhang; Li Shen 005; Lei Han; Li Shen 008 (CoLLAs, 2023)

Architecture, Dataset and Model-Scale Agnostic Data-free Meta-Learning. - Zixuan Hu; Li Shen 008; Zhenyi Wang 001; Tongliang Liu; Chun Yuan; Dacheng Tao (CVPR, 2023)

Robust Generalization Against Photon-Limited Corruptions via Worst-Case Sharpness Minimization. - Zhuo Huang; Miaoxi Zhu; Xiaobo Xia; Li Shen 008; Jun Yu 001; Chen Gong 002; Bo Han 003; Bo Du 001; Tongliang Liu (CVPR, 2023)

Make Landscape Flatter in Differentially Private Federated Learning. - Yifan Shi; Yingqi Liu; Kang Wei; Li Shen 008; Xueqian Wang 001; Dacheng Tao (CVPR, 2023)

MetaMix: Towards Corruption-Robust Continual Learning with Temporally Self-Adaptive Data Transformation. - Zhenyi Wang 001; Li Shen 008; Donglin Zhan; Qiuling Suo; Yanjun Zhu; Tiehang Duan; Mingchen Gao (CVPR, 2023)

Merging Experts into One: Improving Computational Efficiency of Mixture of Experts. - Shwai He; Run-Ze Fan; Liang Ding 006; Li Shen 008; Tianyi Zhou 001; Dacheng Tao (EMNLP, 2023)

Towards Making the Most of ChatGPT for Machine Translation. - Keqin Peng; Liang Ding 006; Qihuang Zhong; Li Shen 008; Xuebo Liu 002; Min Zhang 005; Yuanxin Ouyang; Dacheng Tao (EMNLP (Findings), 2023)

Zero-shot Sharpness-Aware Quantization for Pre-trained Language Models. - Miaoxi Zhu; Qihuang Zhong; Li Shen 008; Liang Ding 006; Juhua Liu; Bo Du 001; Dacheng Tao (EMNLP, 2023)

Data Augmented Flatness-aware Gradient Projection for Continual Learning. - Enneng Yang; Li Shen 008; Zhenyi Wang 001; Shiwei Liu 003; Guibing Guo; Xingwei Wang 001 (ICCV, 2023)

Global Balanced Experts for Federated Long-Tailed Learning. - Yaopei Zeng; Lei Liu 049; Li Liu 036; Li Shen 008; Shaoguo Liu; Baoyuan Wu (ICCV, 2023)

Enhancing Fine-Tuning based Backdoor Defense with Sharpness-Aware Minimization. - Mingli Zhu; Shaokui Wei; Li Shen 008; Yanbo Fan; Baoyuan Wu (ICCV, 2023)

Harnessing Out-Of-Distribution Examples via Augmenting Content and Style. - Zhuo Huang; Xiaobo Xia; Li Shen 008; Bo Han 003; Mingming Gong; Chen Gong 002; Tongliang Liu (ICLR, 2023)

FedSpeed: Larger Local Interval, Less Communication Round, and Higher Generalization Accuracy. - Yan Sun; Li Shen 008; Tiansheng Huang; Liang Ding 006; Dacheng Tao (ICLR, 2023)

Towards One-shot Neural Combinatorial Solvers: Theoretical and Empirical Notes on the Cardinality-Constrained Case. - Runzhong Wang; Li Shen 008; Yiting Chen 003; Xiaokang Yang 001; Dacheng Tao; Junchi Yan (ICLR, 2023)

Learning to Learn from APIs: Black-Box Data-Free Meta-Learning. - Zixuan Hu; Li Shen 008; Zhenyi Wang 001; Baoyuan Wu; Chun Yuan; Dacheng Tao (ICML, 2023)

Are Large Kernels Better Teachers than Transformers for ConvNets? - Tianjin Huang; Lu Yin 006; Zhenyu Zhang 015; Li Shen 008; Meng Fang; Mykola Pechenizkiy; Zhangyang Wang; Shiwei Liu 003 (ICML, 2023)

Improving the Model Consistency of Decentralized Federated Learning. - Yifan Shi; Li Shen 008; Kang Wei; Yan Sun; Bo Yuan 003; Xueqian Wang 001; Dacheng Tao (ICML, 2023)

Dynamic Regularized Sharpness Aware Minimization in Federated Learning: Approaching Global Consistency and Smooth Landscape. - Yan Sun; Li Shen 008; Shixiang Chen; Liang Ding 006; Dacheng Tao (ICML, 2023)

CoCo: A Coupled Contrastive Framework for Unsupervised Domain Adaptive Graph Classification. - Nan Yin; Li Shen 008; Mengzhu Wang; Long Lan; Zeyu Ma 001; Chong Chen 002; Xian-Sheng Hua 001; Xiao Luo 001 (ICML, 2023)

Off-policy Imitation Learning from Visual Inputs. - Zhihao Cheng; Li Shen 008; Dacheng Tao (ICRA, 2023)

LGViT: Dynamic Early Exiting for Accelerating Vision Transformer. - Guanyu Xu; Jiawei Hao; Li Shen 008; Han Hu 003; Yong Luo 002; Hui Lin; Jialie Shen 001 (ACM Multimedia, 2023)

Dynamic Sparsity Is Channel-Level Sparsity Learner. - Lu Yin 006; Gen Li 012; Meng Fang; Li Shen 008; Tianjin Huang; Zhangyang Wang; Vlado Menkovski; Xiaolong Ma; Mykola Pechenizkiy; Shiwei Liu 003 (NeurIPS, 2023)

Federated Learning with Manifold Regularization and Normalized Update Reaggregation. - Xuming An; Li Shen 008; Han Hu 003; Yong Luo 002 (NeurIPS, 2023)

FlatMatch: Bridging Labeled Data and Unlabeled Data with Cross-Sharpness for Semi-Supervised Learning. - Zhuo Huang; Li Shen 008; Jun Yu 001; Bo Han 003; Tongliang Liu (NeurIPS, 2023)

Learning Better with Less: Effective Augmentation for Sample-Efficient Visual Reinforcement Learning. - Guozheng Ma; Linrui Zhang; Haoyu Wang 003; Lu Li; Zilin Wang; Zhen Wang 030; Li Shen 008; Xueqian Wang 001; Dacheng Tao (NeurIPS, 2023)

Towards Stable Backdoor Purification through Feature Shift Tuning. - Rui Min; Zeyu Qin; Li Shen 008; Minhao Cheng (NeurIPS, 2023)

Understanding How Consistency Works in Federated Learning via Stage-wise Relaxed Initialization. - Yan Sun; Li Shen 008; Dacheng Tao (NeurIPS, 2023)

Defending against Data-Free Model Extraction by Distributionally Robust Defensive Training. - Zhenyi Wang 001; Li Shen 008; Tongliang Liu; Tiehang Duan; Yanjun Zhu; Donglin Zhan; David S. Doermann; Mingchen Gao (NeurIPS, 2023)

An Efficient Dataset Condensation Plugin and Its Application to Continual Learning. - Enneng Yang; Li Shen 008; Zhenyi Wang 001; Tongliang Liu; Guibing Guo (NeurIPS, 2023)

Stability and Generalization of the Decentralized Stochastic Gradient Descent Ascent Algorithm. - Miaoxi Zhu; Li Shen 008; Bo Du 001; Dacheng Tao (NeurIPS, 2023)

Enhancing Adversarial Training via Reweighting Optimization Trajectory. - Tianjin Huang; Shiwei Liu 003; Tianlong Chen 001; Meng Fang; Li Shen 008; Vlado Menkovski; Lu Yin 006; Yulong Pei; Mykola Pechenizkiy (ECML/PKDD (1), 2023)

SaFormer: A Conditional Sequence Modeling Approach to Offline Safe Reinforcement Learning. - Qin Zhang; Linrui Zhang; Haoran Xu; Li Shen 008; Bowen Wang; Yongzhe Chang; Xueqian Wang 001; Bo Yuan 003; Dacheng Tao (CoRR, 2023)

Enhance Local Consistency in Federated Learning: A Multi-Step Inertial Momentum Approach. - Yixing Liu; Yan Sun; Zhengtao Ding; Li Shen 008; Bo Liu 034; Dacheng Tao (CoRR, 2023)

Bag of Tricks for Effective Language Model Pretraining and Downstream Adaptation: A Case Study on GLUE. - Qihuang Zhong; Liang Ding 006; Keqin Peng; Juhua Liu; Bo Du 001; Li Shen 008; Yibing Zhan; Dacheng Tao (CoRR, 2023)

Subspace based Federated Unlearning. - Guanghao Li; Li Shen 008; Yan Sun; Yue Hu; Han Hu 003; Dacheng Tao (CoRR, 2023)

OmniForce: On Human-Centered, Large Model Empowered and Cloud-Edge Collaborative AutoML System. - Chao Xue; Wei Liu 005; Shuai Xie; Zhenfang Wang; Jiaxing Li; Xuyang Peng; Liang Ding 006; Shanshan Zhao 001; Qiong Cao; Yibo Yang; Fengxiang He; Bohua Cai; et al. (CoRR, 2023)

SGDA: Towards 3D Universal Pulmonary Nodule Detection via Slice Grouped Domain Attention. - Rui Xu 031; Zhi Liu 002; Yong Luo 002; Han Hu 003; Li Shen 008; Bo Du 001; Kaiming Kuang; Jiancheng Yang (CoRR, 2023)

Graph Decision Transformer. - Shengchao Hu; Li Shen 008; Ya Zhang 002; Dacheng Tao (CoRR, 2023)

On Efficient Training of Large-Scale Deep Learning Models: A Literature Review. - Li Shen 008; Yan Sun; Zhiyuan Yu 004; Liang Ding 006; Xinmei Tian 001; Dacheng Tao (CoRR, 2023)

Towards the Flatter Landscape and Better Generalization in Federated Learning under Client-level Differential Privacy. - Yifan Shi; Kang Wei; Li Shen 008; Yingqi Liu; Xueqian Wang 001; Bo Yuan 003; Dacheng Tao (CoRR, 2023)

Prompt-Tuning Decision Transformer with Preference Ranking. - Shengchao Hu; Li Shen 008; Ya Zhang 002; Dacheng Tao (CoRR, 2023)

Towards More Suitable Personalization in Federated Learning via Decentralized Partial Model Training. - Yifan Shi; Yingqi Liu; Yan Sun; Zihao Lin 003; Li Shen 008; Xueqian Wang 001; Dacheng Tao (CoRR, 2023)

Instructed Diffuser with Temporal Condition Guidance for Offline Reinforcement Learning. - Jifeng Hu; Yanchao Sun; Sili Huang; Siyuan Guo; Hechang Chen; Li Shen 008; Lichao Sun 001; Yi Chang 001; Dacheng Tao (CoRR, 2023)

Systematic Investigation of Sparse Perturbed Sharpness-Aware Minimization Optimizer. - Peng Mi; Li Shen 008; Tianhe Ren; Yiyi Zhou; Tianshuo Xu; Xiaoshuai Sun; Tongliang Liu; Rongrong Ji; Dacheng Tao (CoRR, 2023)

Boosting Backdoor Attack with A Learnable Poisoning Sample Selection Strategy. - Zihao Zhu 001; Mingda Zhang; Shaokui Wei; Li Shen 008; Yanbo Fan; Baoyuan Wu (CoRR, 2023)

DFedADMM: Dual Constraints Controlled Model Inconsistency for Decentralized Federated Learning. - Qinglun Li; Li Shen 008; Guanghao Li; Quanjun Yin; Dacheng Tao (CoRR, 2023)

Towards Understanding the Generalizability of Delayed Stochastic Gradient Descent. - Xiaoge Deng; Li Shen 008; Shengwei Li; Tao Sun 005; Dongsheng Li 001; Dacheng Tao (CoRR, 2023)

Master-slave Deep Architecture for Top-K Multi-armed Bandits with Non-linear Bandit Feedback and Diversity Constraints. - Hanchi Huang; Li Shen 008; Deheng Ye; Wei Liu 005 (CoRR, 2023)

MerA: Merging Pretrained Adapters For Few-Shot Learning. - Shwai He; Run-Ze Fan; Liang Ding 006; Li Shen 008; Tianyi Zhou 001; Dacheng Tao (CoRR, 2023)

FedLALR: Client-Specific Adaptive Learning Rates Achieve Linear Speedup for Non-IID Data. - Hao Sun 019; Li Shen 008; Shixiang Chen; Jingwei Sun 001; Jing Li 047; Guangzhong Sun; Dacheng Tao (CoRR, 2023)

Deep Model Fusion: A Survey. - Weishi Li; Yong Peng 006; Miao Zhang; Liang Ding 006; Han Hu 003; Li Shen 008 (CoRR, 2023)

Unlikelihood Tuning on Negative Samples Amazingly Improves Zero-Shot Translation. - Changtong Zan; Liang Ding 006; Li Shen 008; Yibin Lei; Yibing Zhan; Weifeng Liu 001; Dacheng Tao (CoRR, 2023)

Efficient Federated Prompt Tuning for Black-box Large Pre-trained Models. - Zihao Lin 003; Yan Sun; Yifan Shi; Xueqian Wang 001; Lifu Huang; Li Shen 008; Dacheng Tao (CoRR, 2023)

Which mode is better for federated learning? Centralized or Decentralized. - Yan Sun; Li Shen 008; Dacheng Tao (CoRR, 2023)

Asymmetrically Decentralized Federated Learning. - Qinglun Li; Miao Zhang; Nan Yin; Quanjun Yin; Li Shen 008 (CoRR, 2023)

Learn From Model Beyond Fine-Tuning: A Survey. - Hongling Zheng; Li Shen 008; Anke Tang; Yong Luo 002; Han Hu 003; Bo Du 001; Dacheng Tao (CoRR, 2023)

Rethinking SIGN Training: Provable Nonconvex Acceleration without First- and Second-Order Gradient Lipschitz. - Tao Sun 005; Congliang Chen; Peng Qiao; Li Shen 008; Xinwang Liu 002; Dongsheng Li 001 (CoRR, 2023)

Task-Distributionally Robust Data-Free Meta-Learning. - Zixuan Hu; Li Shen 008; Zhenyi Wang 001; Yongxian Wei; Baoyuan Wu; Chun Yuan; Dacheng Tao (CoRR, 2023)

Concrete Subspace Learning based Interference Elimination for Multi-task Model Fusion. - Anke Tang; Li Shen 008; Yong Luo 002; Liang Ding 006; Han Hu 003; Bo Du 001; Dacheng Tao (CoRR, 2023)

FedDAG: Federated DAG Structure Learning. - Erdun Gao; Junjia Chen; Li Shen 008; Tongliang Liu; Mingming Gong; Howard D. Bondell (Trans. Mach. Learn. Res., 2023)

Fusion of Global and Local Knowledge for Personalized Federated Learning. - Tiansheng Huang; Li Shen 008; Yan Sun; Weiwei Lin 001; Dacheng Tao (Trans. Mach. Learn. Res., 2023)

Dynamic Contrastive Distillation for Image-Text Retrieval. - Jun Rao; Liang Ding 006; Shuhan Qi; Meng Fang; Yang Liu 039; Li Shen 008; Dacheng Tao (IEEE Trans. Multim., 2023)

Efficient-Adam: Communication-Efficient Distributed Adam. - Congliang Chen; Li Shen 008; Wei Liu 005; Zhi-Quan Luo (IEEE Trans. Signal Process., 2023)

Reducing bi-level feature redundancy for unsupervised domain adaptation. - Mengzhu Wang; Shanshan Wang 008; Wei Wang 335; Li Shen 008; Xiang Zhang 008; Long Lan; Zhigang Luo (Pattern Recognit., 2023)

Curriculum-Based Asymmetric Multi-Task Reinforcement Learning. - Hanchi Huang; Deheng Ye; Li Shen 008; Wei Liu 005 (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Differentiable Neural Architecture Search for Extremely Lightweight Image Super-Resolution. - Han Huang; Li Shen 008; Chaoyang He 001; Weisheng Dong; Wei Liu 005 (IEEE Trans. Circuits Syst. Video Technol., 2023)

Task-Adaptive Feature Disentanglement and Hallucination for Few-Shot Classification. - Zixuan Hu; Li Shen 008; Shenqi Lai; Chun Yuan (IEEE Trans. Circuits Syst. Video Technol., 2023)

Don't Be So Dense: Sparse-to-Sparse GAN Training Without Sacrificing Performance. - Shiwei Liu 003; Yuesong Tian; Tianlong Chen 001; Li Shen 008 (Int. J. Comput. Vis., 2023)

Prescribed Safety Performance Imitation Learning From a Single Expert Dataset. - Zhihao Cheng; Li Shen 008; Miaoxi Zhu; Jiaxian Guo; Meng Fang; Liu Liu 014; Bo Du 001; Dacheng Tao (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Hierarchical Detailed Intermediate Supervision for Image-to-Image Translation. - Jianbo Wang; Hao-Zhi Huang 001; Li Shen 008; Xuan Wang 009; Toshihiko Yamasaki (IEICE Trans. Inf. Syst., 2023)

Efficient Federated Learning Via Local Adaptive Amended Optimizer With Linear Speedup. - Yan Sun; Li Shen 008; Hao Sun 019; Liang Ding 006; Dacheng Tao (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Distributionally Robust Memory Evolution With Generalized Divergence for Continual Learning. - Zhenyi Wang 001; Li Shen 008; Tiehang Duan; Qiuling Suo; Le Fang; Wei Liu 005; Mingchen Gao (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

OMG: Towards Effective Graph Classification Against Label Noise. - Nan Yin; Li Shen 008; Mengzhu Wang; Xiao Luo 001; Zhigang Luo; Dacheng Tao (IEEE Trans. Knowl. Data Eng., 2023)

Neural Network Approximation for Pessimistic Offline Reinforcement Learning. - Di Wu; Yuling Jiao; Li Shen 008; Haizhao Yang; Xiliang Lu (AAAI, 2024)

OOP: Object-Oriented Programming Evaluation Benchmark for Large Language Models. - Shuai Wang 011; Liang Ding 006; Li Shen 008; Yong Luo 002; Bo Du 001; Dacheng Tao (ACL (Findings), 2024)

Revisiting Knowledge Distillation for Autoregressive Language Models. - Qihuang Zhong; Liang Ding 006; Li Shen 008; Juhua Liu; Bo Du 001; Dacheng Tao (ACL (1), 2024)

POCE: Primal Policy Optimization with Conservative Estimation for Multi-constraint Offline Reinforcement Learning. - Jiayi Guan; Li Shen 008; Ao Zhou 005; Lusong Li; Han Hu 003; Xiaodong He 001; Guang Chen 001; Changjun Jiang (CVPR, 2024)

Your Transferability Barrier is Fragile: Free-Lunch for Transferring the Non-Transferable Learning. - Ziming Hong; Li Shen 008; Tongliang Liu (CVPR, 2024)

Decentralized Directed Collaboration for Personalized Federated Learning. - Yingqi Liu; Yifan Shi; Baoyuan Wu; Qinglun Li; Xueqian Wang 001; Li Shen 008 (CVPR, 2024)

Free: Faster and Better Data-Free Meta-Learning. - Yongxian Wei; Zixuan Hu; Zhenyi Wang 001; Li Shen 008; Chun Yuan; Dacheng Tao (CVPR, 2024)

Embodied Multi-Modal Agent trained by an LLM from a Parallel TextWorld. - Yijun Yang; Tianyi Zhou 001; Kanxue Li; Dapeng Tao; Lusong Li; Li Shen 008; Xiaodong He 001; Jing Jiang 002; Yuhui Shi 001 (CVPR, 2024)

Sheared Backpropagation for Fine-Tuning Foundation Models. - Zhiyuan Yu 004; Li Shen 008; Liang Ding 006; Xinmei Tian 001; Yixin Chen 001; Dacheng Tao (CVPR, 2024)

Diversifying the Mixture-of-Experts Representation for Language Models with Orthogonal Optimizer. - Boan Liu; Liang Ding 006; Li Shen 008; Keqin Peng; Yu Cao 014; Dazhao Cheng; Dacheng Tao (ECAI, 2024)

Training A Secure Model Against Data-Free Model Extraction. - Zhenyi Wang 001; Li Shen 008; Junfeng Guo; Tiehang Duan; Siyu Luan; Tongliang Liu; Mingchen Gao (ECCV (79), 2024)

Is C4 Dataset Optimal for Pruning? An Investigation of Calibration Data for LLM Pruning. - Abhinav Bandari; Lu Yin 006; Cheng-Yu Hsieh; Ajay Jaiswal; Tianlong Chen 001; Li Shen 008; Ranjay Krishna; Shiwei Liu 003 (EMNLP, 2024)

Improving Non-Transferable Representation Learning by Harnessing Content and Style. - Ziming Hong; Zhenyi Wang 001; Li Shen 008; Yu Yao 005; Zhuo Huang; Shiming Chen 002; Chuanwu Yang; Mingming Gong; Tongliang Liu (ICLR, 2024)

Learning Multi-Agent Communication from Graph Modeling Perspective. - Shengchao Hu; Li Shen 008; Ya Zhang 002; Dacheng Tao (ICLR, 2024)

Revisiting Plasticity in Visual Reinforcement Learning: Data, Modules and Training Stages. - Guozheng Ma; Lu Li; Sen Zhang 006; Zixuan Liu 002; Zhen Wang 030; Yixin Chen 001; Li Shen 008; Xueqian Wang 001; Dacheng Tao (ICLR, 2024)

Parameter-Efficient Multi-Task Model Fusion with Partial Linearization. - Anke Tang; Li Shen 008; Yong Luo 002; Yibing Zhan; Han Hu 003; Bo Du 001; Yixin Chen 001; Dacheng Tao (ICLR, 2024)

A Unified and General Framework for Continual Learning. - Zhenyi Wang 001; Yan Li; Li Shen 008; Heng Huang (ICLR, 2024)

AdaMerging: Adaptive Model Merging for Multi-Task Learning. - Enneng Yang; Zhenyi Wang 001; Li Shen 008; Shiwei Liu 003; Guibing Guo; Xingwei Wang 001; Dacheng Tao (ICLR, 2024)

DREAM: Dual Structured Exploration with Mixup for Open-set Graph Domain Adaption. - Nan Yin; Mengzhu Wang; Zhenghan Chen; Li Shen 008; Huan Xiong; Bin Gu 001; Xiao Luo 001 (ICLR, 2024)

HarmoDT: Harmony Multi-Task Decision Transformer for Offline Reinforcement Learning. - Shengchao Hu; Ziqing Fan; Li Shen 008; Ya Zhang 002; Yanfeng Wang 001; Dacheng Tao (ICML, 2024)

Q-value Regularized Transformer for Offline Reinforcement Learning. - Shengchao Hu; Ziqing Fan; Chaoqin Huang; Li Shen 008; Ya Zhang 002; Yanfeng Wang 001; Dacheng Tao (ICML, 2024)

Sparse Model Inversion: Efficient Inversion of Vision Transformers for Data-Free Applications. - Zixuan Hu; Yongxian Wei; Li Shen 008; Zhenyi Wang 001; Lei Li 051; Chun Yuan; Dacheng Tao (ICML, 2024)

Merging Multi-Task Models via Weight-Ensembling Mixture of Experts. - Anke Tang; Li Shen 008; Yong Luo 002; Nan Yin; Lefei Zhang; Dacheng Tao (ICML, 2024)

Generalization Analysis of Stochastic Weight Averaging with General Sampling. - Peng Wang; Li Shen 008; Zerui Tao; Shuaida He; Dacheng Tao (ICML, 2024)

Task Groupings Regularization: Data-Free Meta-Learning with Heterogeneous Pre-trained Models. - Yongxian Wei; Zixuan Hu; Li Shen 008; Zhenyi Wang 001; Yu Li 006; Chun Yuan; Dacheng Tao (ICML, 2024)

Representation Surgery for Multi-Task Model Merging. - Enneng Yang; Li Shen 008; Zhenyi Wang 001; Guibing Guo; Xiaojun Chen 006; Xingwei Wang 001; Dacheng Tao (ICML, 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 008; Lusong Li; et al. (IJCAI, 2024)

PrimKD: Primary Modality Guided Multimodal Fusion for RGB-D Semantic Segmentation. - Zhiwei Hao; Zhongyu Xiao; Yong Luo 002; Jianyuan Guo; Jing Wang 055; Li Shen 008; Han Hu 003 (ACM Multimedia, 2024)

WisdoM: Improving Multimodal Sentiment Analysis by Fusing Contextual World Knowledge. - Wenbin Wang; Liang Ding 006; Li Shen 008; Yong Luo 002; Han Hu 003; Dacheng Tao (ACM Multimedia, 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 001; Li Shen 008 (NeurIPS, 2024)

Uncovering, Explaining, and Mitigating the Superficial Safety of Backdoor Defense. - Rui Min; Zeyu Qin; Nevin L. Zhang; Li Shen 008; Minhao Cheng (NeurIPS, 2024)

A-FedPD: Aligning Dual-Drift is All Federated Primal-Dual Learning Needs. - Yan Sun; Li Shen 008; Dacheng Tao (NeurIPS, 2024)

A Huber Loss Minimization Approach to Mean Estimation under User-level Differential Privacy. - Puning Zhao; Lifeng Lai; Li Shen 008; Qingming Li; Jiafei Wu; Zhe Liu 001 (NeurIPS, 2024)

Decomposed Prompt Decision Transformer for Efficient Unseen Task Generalization. - Hongling Zheng; Li Shen 008; Yong Luo 002; Tongliang Liu; Jialie Shen 001; Dacheng Tao (NeurIPS, 2024)

Solving Continual Offline Reinforcement Learning with Decision Transformer. - Kaixin Huang; Li Shen 008; Chen Zhao; Chun Yuan; Dacheng Tao (CoRR, 2024)

Step-On-Feet Tuning: Scaling Self-Alignment of LLMs via Bootstrapping. - Haoyu Wang 003; Guozheng Ma; Ziqiao Meng; Zeyu Qin; Li Shen 008; Zhong Zhang; Bingzhe Wu; Liu Liu 014; Yatao Bian; Tingyang Xu; Xueqian Wang 001; Peilin Zhao (CoRR, 2024)

Building Accurate Translation-Tailored LLMs with Language Aware Instruction Tuning. - Changtong Zan; Liang Ding 006; Li Shen 008; Yibing Zhen; Weifeng Liu 001; Dacheng Tao (CoRR, 2024)

A General and Efficient Federated Split Learning with Pre-trained Image Transformers for Heterogeneous Data. - Yifan Shi; Yuhui Zhang; Ziyue Huang; Xiaofeng Yang; Li Shen 008; Wei Chen; Xueqian Wang 001 (CoRR, 2024)

Continuous Spiking Graph Neural Networks. - Nan Yin; Mengzhu Wang; Li Shen 008; Hitesh Laxmichand Patel; Baopu Li; Bin Gu 001; Huan Xiong (CoRR, 2024)

Fast Generalizable Gaussian Splatting Reconstruction from Multi-View Stereo. - Tianqi Liu 003; Guangcong Wang; Shoukang Hu; Li Shen 008; Xinyi Ye; Yuhang Zang; Zhiguo Cao 001; Wei Li 190; Ziwei Liu 002 (CoRR, 2024)

Learning with User-Level Local Differential Privacy. - Puning Zhao; Li Shen 008; Rongfei Fan; Qingming Li; Huiwen Wu; Jiafei Wu; Zhe Liu 001 (CoRR, 2024)

AlignIQL: Policy Alignment in Implicit Q-Learning through Constrained Optimization. - Longxiang He; Li Shen 008; Junbo Tan; Xueqian Wang 001 (CoRR, 2024)

FusionBench: A Comprehensive Benchmark of Deep Model Fusion. - Anke Tang; Li Shen 008; Yong Luo 002; Han Hu 003; Bo Du 001; Dacheng Tao (CoRR, 2024)

Towards Efficient Pareto Set Approximation via Mixture of Experts Based Model Fusion. - Anke Tang; Li Shen 008; Yong Luo 002; Shiwei Liu 003; Han Hu 003; Bo Du 001 (CoRR, 2024)

(PASS) Visual Prompt Locates Good Structure Sparsity through a Recurrent HyperNetwork. - Tianjin Huang; Meng Fang; Li Shen 008; Fan Liu; Yulong Pei; Mykola Pechenizkiy; Shiwei Liu 003; Tianlong Chen 001 (CoRR, 2024)

Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities. - Enneng Yang; Li Shen 008; Guibing Guo; Xingwei Wang 001; Xiaochun Cao; Jie Zhang 002; Dacheng Tao (CoRR, 2024)

Byzantine-resilient Federated Learning Employing Normalized Gradients on Non-IID Datasets. - Shiyuan Zuo; Xingrun Yan; Rongfei Fan; Li Shen 008; Puning Zhao; Jie Xu 002; Han Hu 003 (CoRR, 2024)

Sequential Federated Learning in Hierarchical Architecture on Non-IID Datasets. - Xingrun Yan; Shiyuan Zuo; Rongfei Fan; Han Hu 003; Li Shen 008; Puning Zhao; Yong Luo 002 (CoRR, 2024)

SMILE: Zero-Shot Sparse Mixture of Low-Rank Experts Construction From Pre-Trained Foundation Models. - Anke Tang; Li Shen 008; Yong Luo 002; Shuai Xie; Han Hu 003; Lefei Zhang; Bo Du 001; Dacheng Tao (CoRR, 2024)

Divide, Conquer and Combine: A Training-Free Framework for High-Resolution Image Perception in Multimodal Large Language Models. - Wenbin Wang; Liang Ding 006; Minyan Zeng; Xiabin Zhou; Li Shen 008; Yong Luo 002; Dacheng Tao (CoRR, 2024)

Convergent Differential Privacy Analysis for General Federated Learning: the f-DP Perspective. - Yan Sun; Li Shen 008; Dacheng Tao (CoRR, 2024)

Continual Diffuser (CoD): Mastering Continual Offline Reinforcement Learning with Experience Rehearsal. - Jifeng Hu; Li Shen 008; Sili Huang; Zhejian Yang; Hechang Chen; Lichao Sun 001; Yi Chang 001; Dacheng Tao (CoRR, 2024)

USCD: Improving Code Generation of LLMs by Uncertainty-Aware Selective Contrastive Decoding. - Shuai Wang 011; Liang Ding 006; Li Shen 008; Yong Luo 002; Zheng He; Wei Yu 004; Dacheng Tao (CoRR, 2024)

DreamMover: Leveraging the Prior of Diffusion Models for Image Interpolation with Large Motion. - Li Shen 008; Tianqi Liu 003; Huiqiang Sun; Xinyi Ye; Baopu Li; Jianming Zhang 001; Zhiguo Cao 001 (CoRR, 2024)

OledFL: Unleashing the Potential of Decentralized Federated Learning via Opposite Lookahead Enhancement. - Qinglun Li; Miao Zhang; Mengzhu Wang; Quanjun Yin; Li Shen 008 (CoRR, 2024)

Boosting the Performance of Decentralized Federated Learning via Catalyst Acceleration. - Qinglun Li; Miao Zhang; Yingqi Liu; Quanjun Yin; Li Shen 008; Xiaochun Cao (CoRR, 2024)

Targeted Vaccine: Safety Alignment for Large Language Models against Harmful Fine-Tuning via Layer-wise Perturbation. - Guozhi Liu; Weiwei Lin; Tiansheng Huang; Ruichao Mo; Qi Mu; Li Shen 008 (CoRR, 2024)

Simultaneous Computation and Memory Efficient Zeroth-Order Optimizer for Fine-Tuning Large Language Models. - Fei Wang 032; Li Shen 008; Liang Ding 006; Chao Xue; Ye Liu 014; Changxing Ding (CoRR, 2024)

Mitigating the Backdoor Effect for Multi-Task Model Merging via Safety-Aware Subspace. - Jinluan Yang; Anke Tang; Didi Zhu; Zhengyu Chen 001; Li Shen 008; Fei Wu 001 (CoRR, 2024)

SurgeryV2: Bridging the Gap Between Model Merging and Multi-Task Learning with Deep Representation Surgery. - Enneng Yang; Li Shen 008; Zhenyi Wang 001; Guibing Guo; Xingwei Wang 001; Xiaochun Cao; Jie Zhang 002; Dacheng Tao (CoRR, 2024)

Solving Continual Offline RL through Selective Weights Activation on Aligned Spaces. - Jifeng Hu; Sili Huang; Li Shen 008; Zhejian Yang; Shengchao Hu; Shisong Tang; Hechang Chen; Yi Chang 001; Dacheng Tao; Lichao Sun 001 (CoRR, 2024)

Efficient and Effective Weight-Ensembling Mixture of Experts for Multi-Task Model Merging. - Li Shen 008; Anke Tang; Enneng Yang; Guibing Guo; Yong Luo 002; Lefei Zhang; Xiaochun Cao; Bo Du 001; Dacheng Tao (CoRR, 2024)

Towards Constraint-aware Learning for Resource Allocation in NFV-enabled Networks. - Tianfu Wang 002; Long Yang 004; Chao Wang 086; Chuan Qin 002; Liwei Deng 001; Li Shen 008; Hui Xiong 001 (CoRR, 2024)

Communication Learning in Multi-Agent Systems from Graph Modeling Perspective. - Shengchao Hu; Li Shen 008; Ya Zhang 002; Dacheng Tao (CoRR, 2024)

Task-Aware Harmony Multi-Task Decision Transformer for Offline Reinforcement Learning. - Ziqing Fan; Shengchao Hu; Yuhang Zhou; Li Shen 008; Ya Zhang 002; Yanfeng Wang 001; Dacheng Tao (CoRR, 2024)

Stability and Generalization for Distributed SGDA. - Miaoxi Zhu; Yan Sun; Li Shen 008; Bo Du 001; Dacheng Tao (CoRR, 2024)

Continual Task Learning through Adaptive Policy Self-Composition. - Shengchao Hu; Yuhang Zhou; Ziqing Fan; Jifeng Hu; Li Shen 008; Ya Zhang 002; Dacheng Tao (CoRR, 2024)

Aligning Few-Step Diffusion Models with Dense Reward Difference Learning. - Ziyi Zhang 001; Li Shen 008; Sen Zhang 006; Deheng Ye; Yong Luo 002; Miaojing Shi; Bo Du 001; Dacheng Tao (CoRR, 2024)

DiM: f-Divergence Minimization Guided Sharpness-Aware Optimization for Semi-supervised Medical Image Segmentation. - Bingli Wang; Houcheng Su; Nan Yin; Mengzhu Wang; Li Shen 008 (CoRR, 2024)

AGLP: A Graph Learning Perspective for Semi-supervised Domain Adaptation. - Houcheng Su; Mengzhu Wang; Jiao Li; Nan Yin; Liang Yang 002; Li Shen 008 (CoRR, 2024)

A Unified Analysis for Finite Weight Averaging. - Peng Wang; Li Shen 008; Zerui Tao; Yan Sun; Guodong Zheng; Dacheng Tao (CoRR, 2024)

Exploring the Generalization Capabilities of AID-based Bi-level Optimization. - Congliang Chen; Li Shen 008; Zhiqiang Xu 003; Wei Liu 005; Zhi-Quan Luo; Peilin Zhao (CoRR, 2024)

Unlocking Tuning-Free Few-Shot Adaptability in Visual Foundation Models by Recycling Pre-Tuned LoRAs. - Zixuan Hu; Yongxian Wei; Li Shen 008; Chun Yuan; Dacheng Tao (CoRR, 2024)

DynamicKV: Task-Aware Adaptive KV Cache Compression for Long Context LLMs. - Xiabin Zhou; Wenbin Wang; Minyan Zeng; Jiaxian Guo; Xuebo Liu 002; Li Shen 008; Min Zhang 005; Liang Ding 006 (CoRR, 2024)

Mulberry: Empowering MLLM with o1-like Reasoning and Reflection via Collective Monte Carlo Tree Search. - Huanjin Yao; Jiaxing Huang 001; Wenhao Wu; Jingyi Zhang 005; Yibo Wang; Shunyu Liu 001; Yingjie Wang 007; Yuxin Song; Haocheng Feng; Li Shen 008; Dacheng Tao (CoRR, 2024)

Dynamic PDGAN: discriminator-boosted knowledge distillation for StyleGANs. - Yuesong Tian; Li Shen 008; Xiang Tian 002; Zhifeng Li 001; Yaowu Chen (Adv. Math. Commun., 2024)

Visual Prompt Based Personalized Federated Learning. - Guanghao Li; Wansen Wu; Yan Sun; Li Shen 008; Baoyuan Wu; Dacheng Tao (Trans. Mach. Learn. Res., 2024)

Revisiting Discrete Soft Actor-Critic. - Haibin Zhou; Tong Wei; Zichuan Lin; Junyou Li; Junliang Xing; Yuanchun Shi; Li Shen 008; Chao Yu 004; Deheng Ye (Trans. Mach. Learn. Res., 2024)

Joint Admission Control and Resource Allocation of Virtual Network Embedding via Hierarchical Deep Reinforcement Learning. - Tianfu Wang 002; Li Shen 008; Qilin Fan; Tong Xu 001; Tongliang Liu; Hui Xiong 001 (IEEE Trans. Serv. Comput., 2024)

AdaSAM: Boosting sharpness-aware minimization with adaptive learning rate and momentum for training deep neural networks. - Hao Sun 019; Li Shen 008; Qihuang Zhong; Liang Ding 006; Shixiang Chen; Jingwei Sun 001; Jing Li 047; Guangzhong Sun; Dacheng Tao (Neural Networks, 2024)

Local AdaGrad-type algorithm for stochastic convex-concave optimization. - Luofeng Liao; Li Shen 008; Jia Duan; Mladen Kolar; Dacheng Tao (Mach. Learn., 2024)

Messages are Never Propagated Alone: Collaborative Hypergraph Neural Network for Time-Series Forecasting. - Nan Yin; Li Shen 008; Huan Xiong; Bin Gu 001; Chong Chen 002; Xian-Sheng Hua 001; Siwei Liu 001; Xiao Luo 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

Generalized Embedding Machines for Recommender Systems. - Enneng Yang; Xin Xin 007; Li Shen 008; Yudong Luo; Guibing Guo (Mach. Intell. Res., 2024)

Multi-Scenario and Multi-Task Aware Feature Interaction for Recommendation System. - Derun Song; Enneng Yang; Guibing Guo; Li Shen 008; Linying Jiang; Xingwei Wang 001 (ACM Trans. Knowl. Discov. Data, 2024)

Retain and Adapt: Online Sequential EEG Classification With Subject Shift. - Tiehang Duan; Zhenyi Wang 001; Li Shen 008; Gianfranco Doretto; Donald A. Adjeroh; Fang Li 011; Cui Tao (IEEE Trans. Artif. Intell., 2024)

Efficient Federated Learning With Enhanced Privacy via Lottery Ticket Pruning in Edge Computing. - Yifan Shi; Kang Wei; Li Shen 008; Jun Li 004; Xueqian Wang 001; Bo Yuan 003; Song Guo 001 (IEEE Trans. Mob. Comput., 2024)

Quantum Imitation Learning. - Zhihao Cheng; Kaining Zhang; Li Shen 008; Dacheng Tao (IEEE Trans. Neural Networks Learn. Syst., 2024)

A Unified Analysis of AdaGrad With Weighted Aggregation and Momentum Acceleration. - Li Shen 008; Congliang Chen; Fangyu Zou; Zequn Jie; Ju Sun; Wei Liu 005 (IEEE Trans. Neural Networks Learn. Syst., 2024)

Meta-Learning Without Data via Unconditional Diffusion Models. - Yongxian Wei; Zixuan Hu; Li Shen 008; Zhenyi Wang 001; Lei Li 051; Yu Li 006; Chun Yuan (IEEE Trans. Circuits Syst. Video Technol., 2024)

SPORT: A Subgraph Perspective on Graph Classification with Label Noise. - Nan Yin; Li Shen 008; Chong Chen 002; XianSheng Hua 001; Xiao Luo 001 (ACM Trans. Knowl. Discov. Data, 2024)

Neural-aware Decoupling Fusion based Personalized Federated Learning for Intelligent Sensing. - Yujia Gao; Li Shen 008; Liang Liu 001; Zijian Cao 002; Dacheng Tao; Huadong Ma; Nei Kato (ACM Trans. Sens. Networks, 2024)

On Transforming Reinforcement Learning With Transformers: The Development Trajectory. - Shengchao Hu; Li Shen 008; Ya Zhang 002; Yixin Chen 001; Dacheng Tao (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

Continual Learning From a Stream of APIs. - Enneng Yang; Zhenyi Wang 001; Li Shen 008; Nan Yin; Tongliang Liu; Guibing Guo; Xingwei Wang 001; Dacheng Tao (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

FedGAMMA: Federated Learning With Global Sharpness-Aware Minimization. - Rong Dai; Xun Yang 001; Yan Sun; Li Shen 008; Xinmei Tian 001; Meng Wang 001; Yongdong Zhang 001 (IEEE Trans. Neural Networks Learn. Syst., 2024)

Master-Slave Deep Architecture for Top-K Multiarmed Bandits With Nonlinear Bandit Feedback and Diversity Constraints. - Hanchi Huang; Li Shen 008; Deheng Ye; Wei Liu 005 (IEEE Trans. Neural Networks Learn. Syst., 2024)

Can Linguistic Knowledge Improve Multimodal Alignment in Vision-Language Pretraining? - Fei Wang 032; Liang Ding 006; Jun Rao; Ye Liu 014; Li Shen 008; Changxing Ding (ACM Trans. Multim. Comput. Commun. Appl., 2024)

Divide, Conquer and Combine: A Training-Free Framework for High-Resolution Image Perception in Multimodal Large Language Models. - Wenbin Wang; Liang Ding 006; Minyan Zeng; Xiabin Zhou; Li Shen 008; Yong Luo 002; Wei Yu 004; Dacheng Tao (AAAI, 2025)

Edit Once, Update Everywhere: A Simple Framework for Cross-Lingual Knowledge Synchronization in LLMs. - Yuchen Wu; Liang Ding 006; Li Shen 008; Dacheng Tao (ACL (Findings), 2025)

LoRA Recycle: Unlocking Tuning-Free Few-Shot Adaptability in Visual Foundation Models by Recycling Pre-Tuned LoRAs. - Zixuan Hu; Yongxian Wei; Li Shen 008; Chun Yuan; Dacheng Tao (CVPR, 2025)

PEARL: Towards Permutation-Resilient LLMs. - Liang Chen 001; Li Shen 008; Yang Deng 002; Xiaoyan Zhao 005; Bin Liang 004; Kam-Fai Wong (ICLR, 2025)

Combatting Dimensional Collapse in LLM Pre-Training Data via Submodular File Selection. - Ziqing Fan; Siyuan Du; Shengchao Hu; Pingjie Wang; Li Shen 008; Ya Zhang 002; Dacheng Tao; Yanfeng Wang 001 (ICLR, 2025)

Understanding the Stability-based Generalization of Personalized Federated Learning. - Yingqi Liu; Qinglun Li; Jie Tang 001; Yifan Shi; Li Shen 008; Xiaochun Cao (ICLR, 2025)

Dynamic Neural Fortresses: An Adaptive Shield for Model Extraction Defense. - Siyu Luan; Zhenyi Wang 001; Li Shen 008; Zonghua Gu 001; Chao Wu; Dacheng Tao (ICLR, 2025)

Open-Vocabulary Customization from CLIP via Data-Free Knowledge Distillation. - Yongxian Wei; Zixuan Hu; Li Shen 008; Zhenyi Wang 001; Chun Yuan; Dacheng Tao (ICLR, 2025)

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency. - Qixin Zhang 001; Zongqi Wan; Yu Yang 001; Li Shen 008; Dacheng Tao (ICLR, 2025)

Enhancing Learning with Label Differential Privacy by Vector Approximation. - Puning Zhao; Jiafei Wu; Zhe Liu 001; Li Shen 008; Zhikun Zhang 001; Rongfei Fan; Le Sun; Qingming Li (ICLR, 2025)

Prompt Tuning with Diffusion for Few-Shot Pre-trained Policy Generalization. - Shengchao Hu; Wanru Zhao; Weixiong Lin; Li Shen 008; Ya Zhang 002; Dacheng Tao (AAMAS, 2025)

Enhancing column generation by reinforcement learning-based hyper-heuristic for vehicle routing and scheduling problems. - Kuan Xu; Li Shen 008; Lindong Liu 001 (Comput. Ind. Eng., 2025)

Code-switching finetuning: Bridging multilingual pretrained language models for enhanced cross-lingual performance. - Changtong Zan; Liang Ding 006; Li Shen 008; Yu Cao 014; Weifeng Liu 001 (Eng. Appl. Artif. Intell., 2025)

Learning from models beyond fine-tuning. - Hongling Zheng; Li Shen 008; Anke Tang; Yong Luo 002; Han Hu 003; Bo Du 001; Yonggang Wen 001; Dacheng Tao (Nat. Mac. Intell., 2025)

Communication-efficient distributed learning with Local Immediate Error Compensation. - Yifei Cheng 002; Li Shen 008; Linli Xu; Xun Qian; Shiwei Wu; Yiming Zhou; Tie Zhang; Dacheng Tao; Enhong Chen (Neural Networks, 2025)

DFedGFM: Pursuing global consistency for Decentralized Federated Learning via global flatness and global momentum. - Qinglun Li; Miao Zhang; Tao Sun 005; Quanjun Yin; Li Shen 008 (Neural Networks, 2025)

A Pyramid Fusion MLP for Dense Prediction. - Qiuyu Huang; Zequn Jie; Lin Ma 002; Li Shen 008; Shenqi Lai (IEEE Trans. Image Process., 2025)

Cross-Domain Diffusion With Progressive Alignment for Efficient Adaptive Retrieval. - Junyu Luo 002; Yusheng Zhao; Xiao Luo 001; Zhiping Xiao 001; Wei Ju 001; Li Shen 008; Dacheng Tao; Ming Zhang 004 (IEEE Trans. Image Process., 2025)

Are Large Language Models Really Robust to Word-Level Perturbations? - Haoyu Wang 003; Guozheng Ma; Cong Yu 018; Ning Gui; Linrui Zhang; Zhiqi Huang 005; Suwei Ma; Yongzhe Chang; Sen Zhang 006; Li Shen 008; Xueqian Wang 001; Peilin Zhao; et al. (Trans. Mach. Learn. Res., 2025)

QPO: Query-dependent Prompt Optimization via Multi-Loop Offline Reinforcement Learning. - Yilun Kong; Hangyu Mao; Qi Zhao; Bin Zhang 052; Jingqing Ruan; Li Shen 008; Yongzhe Chang; Xueqian Wang 001; Rui Zhao 001; Dacheng Tao (Trans. Mach. Learn. Res., 2025)

Modeling Multi-Task Model Merging as Adaptive Projective Gradient Descent. - Yongxian Wei; Anke Tang; Li Shen 008; Chun Yuan; Xiaochun Cao (CoRR, 2025)

Merging Models on the Fly Without Retraining: A Sequential Approach to Scalable Continual Model Merging. - Anke Tang; Enneng Yang; Li Shen 008; Yong Luo 002; Han Hu 003; Bo Du 001; Dacheng Tao (CoRR, 2025)

O1-Pruner: Length-Harmonizing Fine-Tuning for O1-Like Reasoning Pruning. - Haotian Luo; Li Shen 008; Haiying He; Yibo Wang; Shiwei Liu 003; Wei Li 190; Naiqiang Tan; Xiaochun Cao; Dacheng Tao (CoRR, 2025)

Panacea: Mitigating Harmful Fine-tuning for Large Language Models via Post-fine-tuning Perturbation. - Yibo Wang; Tiansheng Huang; Li Shen 008; Huanjin Yao; Haotian Luo; Rui Liu; Naiqiang Tan; Jiaxing Huang 001; Dacheng Tao (CoRR, 2025)

TeZO: Empowering the Low-Rankness on the Temporal Dimension in the Zeroth-Order Optimization for Fine-tuning LLMs. - Yan Sun; Tiansheng Huang; Liang Ding 006; Li Shen 008; Dacheng Tao (CoRR, 2025)

Winning Prize Comes from Losing Tickets: Improve Invariant Learning by Exploring Variant Parameters for Out-of-Distribution Generalization. - Zhuo Huang; Muyang Li; Li Shen 008; Jun Yu 001; Chen Gong 002; Bo Han 003; Tongliang Liu (Int. J. Comput. Vis., 2025)

Leveraging Reasoning with Guidelines to Elicit and Utilize Knowledge for Enhancing Safety Alignment. - Haoyu Wang 003; Zeyu Qin; Li Shen 008; Xueqian Wang 001; Minhao Cheng; Dacheng Tao (CoRR, 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 008; Didi Zhu; Zhengyu Chen 001; Daixin Wang; Qing Cui; Zhiqiang Zhang 012; Jun Zhou 011; Fei Wu 001; Kun Kuang (CoRR, 2025)

Mask-Enhanced Autoregressive Prediction: Pay Less Attention to Learn More. - Xialie Zhuang; Zhikai Jia; Jianjin Li; Zhenyu Zhang 015; Li Shen 008; Zheng Cao; Shiwei Liu 003 (CoRR, 2025)

HRP: High-Rank Preheating for Superior LoRA Initialization. - Yuzhu Chen; Yingjie Wang 007; Shi Fu; Li Shen 008; Yongcheng Jing; Xinmei Tian 001; Dacheng Tao (CoRR, 2025)

SeWA: Selective Weight Average via Probabilistic Masking. - Peng Wang; Shengchao Hu; Zerui Tao; Guoxia Wang; Dianhai Yu; Li Shen 008; Quan Zheng; Dacheng Tao (CoRR, 2025)

On Theoretical Limits of Learning with Label Differential Privacy. - Puning Zhao; Chuan Ma; Li Shen 008; Shaowei Wang; Rongfei Fan (CoRR, 2025)

Stable-SPAM: How to Train in 4-Bit More Stably than 16-Bit Adam. - Tianjin Huang; Haotian Hu; Zhenyu Zhang 015; Gaojie Jin; Xiang Li 001; Li Shen 008; Tianlong Chen 001; Lu Liu; Qingsong Wen; Zhangyang Wang; Shiwei Liu 003 (CoRR, 2025)

A Survey on Mechanistic Interpretability for Multi-Modal Foundation Models. - Zihao Lin 003; Samyadeep Basu; Mohammad Beigi; Varun Manjunatha; Ryan A. Rossi; Zichao Wang 001; Yufan Zhou 001; Sriram Balasubramanian; Arman Zarei; Keivan Rezaei; Ying Shen 006; Barry Menglong Yao; et al. (CoRR, 2025)

Retrieval-Augmented Perception: High-Resolution Image Perception Meets Visual RAG. - Wenbin Wang; Yongcheng Jing; Liang Ding 006; Yingjie Wang; Li Shen 008; Yong Luo 002; Bo Du 001; Dacheng Tao (CoRR, 2025)

On Efficient Training of Large-Scale Deep Learning Models. - Li Shen 008; Yan Sun; Zhiyuan Yu 004; Liang Ding 006; Xinmei Tian 001; Dacheng Tao (ACM Comput. Surv., 2025)

A Comprehensive Survey of Forgetting in Deep Learning Beyond Continual Learning. - Zhenyi Wang 001; Enneng Yang; Li Shen 008; Heng Huang (IEEE Trans. Pattern Anal. Mach. Intell., 2025)

Neuron-level Balance between Stability and Plasticity in Deep Reinforcement Learning. - Jiahua Lan; Sen Zhang 006; Haixia Pan; Ruijun Liu; Li Shen 008; Dacheng Tao (CoRR, 2025)

Combatting Dimensional Collapse in LLM Pre-Training Data via Diversified File Selection. - Ziqing Fan; Siyuan Du; Shengchao Hu; Pingjie Wang; Li Shen 008; Ya Zhang 002; Dacheng Tao; Yanfeng Wang 001 (CoRR, 2025)

AdaR1: From Long-CoT to 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 008 (CoRR, 2025)

Federated Learning With Only Positive Labels by Exploring Label Correlations. - Xuming An; Dui Wang; Li Shen 008; Yong Luo 002; Han Hu 003; Bo Du 001; Yonggang Wen 001; Dacheng Tao (IEEE Trans. Neural Networks Learn. Syst., 2025)

Low-Precision Training of Large Language Models: Methods, Challenges, and Opportunities. - Zhiwei Hao; Jianyuan Guo; Li Shen 008; Yong Luo 002; Han Hu 003; Guoxia Wang; Dianhai Yu; Yonggang Wen 001; Dacheng Tao (CoRR, 2025)

Analytic Energy-Guided Policy Optimization for Offline Reinforcement Learning. - Jifeng Hu; Sili Huang; Zhejian Yang; Shengchao Hu; Li Shen 008; Hechang Chen; Lichao Sun 001; Yi Chang 001; Dacheng Tao (CoRR, 2025)

CTRAP: Embedding Collapse Trap to Safeguard Large Language Models from Harmful Fine-Tuning. - Biao Yi; Tiansheng Huang; Baolei Zhang; Tong Li 011; Lihai Nie; Zheli Liu; Li Shen 008 (CoRR, 2025)

R1-ShareVL: Incentivizing Reasoning Capability of Multimodal Large Language Models via Share-GRPO. - Huanjin Yao; Qixiang Yin; Jingyi Zhang 005; Min Yang 007; Yibo Wang; Wenhao Wu; Fei Su; Li Shen 008; Minghui Qiu; Dacheng Tao; Jiaxing Huang 001 (CoRR, 2025)

R1-Compress: Long Chain-of-Thought Compression via Chunk Compression and Search. - Yibo Wang; Li Shen 008; Huanjin Yao; Tiansheng Huang; Rui Liu; Naiqiang Tan; Jiaxing Huang 001; Kai Zhang 008; Dacheng Tao (CoRR, 2025)

MLLM-Guided VLM Fine-Tuning with Joint Inference for Zero-Shot Composed Image Retrieval. - Rong-Cheng Tu; Zhao Jin; Jingyi Liao; Xiao Luo 001; Yingjie Wang; Li Shen 008; Dacheng Tao (CoRR, 2025)

Vad-R1: Towards Video Anomaly Reasoning via Perception-to-Cognition Chain-of-Thought. - Chao Huang 008; Benfeng Wang; Jie Wen 001; Chengliang Liu 003; Wei Wang 335; Li Shen 008; Xiaochun Cao (CoRR, 2025)

Unifying Multimodal Large Language Model Capabilities and Modalities via Model Merging. - Yongxian Wei; Runxi Cheng; Weike Jin; Enneng Yang; Li Shen 008; Lu Hou; Sinan Du; Chun Yuan; Xiaochun Cao; Dacheng Tao (CoRR, 2025)

Multimodal Reasoning Agent for Zero-Shot Composed Image Retrieval. - Rong-Cheng Tu; Wenhao Sun; Hanzhe You; Yingjie Wang; Jiaxing Huang 001; Li Shen 008; Dacheng Tao (CoRR, 2025)

Refining Few-Step Text-to-Multiview Diffusion via Reinforcement Learning. - Ziyi Zhang 001; Li Shen 008; Deheng Ye; Yong Luo 002; Huangxuan Zhao; Lefei Zhang (CoRR, 2025)

Decision Flow Policy Optimization. - Jifeng Hu; Sili Huang; Siyuan Guo; Zhaogeng Liu; Li Shen 008; Lichao Sun 001; Hechang Chen; Yi Chang 001; Dacheng Tao (CoRR, 2025)

Mastering Massive Multi-Task Reinforcement Learning via Mixture-of-Expert Decision Transformer. - Yilun Kong; Guozheng Ma; Qi Zhao; Haoyu Wang 003; Li Shen 008; Xueqian Wang 001; Dacheng Tao (CoRR, 2025)

LightSAM: Parameter-Agnostic Sharpness-Aware Minimization. - Yifei Cheng 002; Li Shen 008; Hao Sun 019; Nan Yin; Xiaochun Cao; Enhong Chen (CoRR, 2025)

Revisiting Flatness-Aware Optimization in Continual Learning With Orthogonal Gradient Projection. - Enneng Yang; Li Shen 008; Zhenyi Wang 001; Shiwei Liu 003; Guibing Guo; Xing-wei Wang 001; Dacheng Tao (IEEE Trans. Pattern Anal. Mach. Intell., 2025)

DGL-GAN: discriminator-guided GAN compression. - Yuesong Tian; Li Shen 008; Xiang Tian 002; Dacheng Tao; Zhifeng Li 001; Wei Liu 005; Yaowu Chen (Vis. Comput., 2025)

Vulnerability-Aware Alignment: Mitigating Uneven Forgetting in Harmful Fine-Tuning. - Liang Chen 001; Xueting Han; Li Shen 008; Jing Bai; Kam-Fai Wong (CoRR, 2025)

TrojanTO: Action-Level Backdoor Attacks against Trajectory Optimization Models. - Yang Dai; Oubo Ma; Longfei Zhang; Xingxing Liang; Xiaochun Cao; Shouling Ji; Jiaheng Zhang; Jin-Cai Huang 001; Li Shen 008 (CoRR, 2025)

MaskPro: Linear-Space Probabilistic Learning for Strict (N:M)-Sparsity on Large Language Models. - Yan Sun; Qixin Zhang 001; Zhiyuan Yu 004; Xikun Zhang 007; Li Shen 008; Dacheng Tao (CoRR, 2025)

AlphaDecay: Module-wise Weight Decay for Heavy-Tailed Balancing in LLMs. - Di He; Ajay Jaiswal; Songjun Tu; Li Shen 008; Ganzhao Yuan; Shiwei Liu 003; Lu Yin 006 (CoRR, 2025)

Network Sparsity Unlocks the Scaling Potential of Deep Reinforcement Learning. - Guozheng Ma; Lu Li; Zilin Wang; Li Shen 008; Pierre-Luc Bacon; Dacheng Tao (CoRR, 2025)

GPTailor: Large Language Model Pruning Through Layer Cutting and Stitching. - Guinan Su; Li Shen 008; Lu Yin 006; Shiwei Liu 003; Yanwu Yang; Jonas Geiping (CoRR, 2025)

Hyper-modal Imputation Diffusion Embedding with Dual-Distillation for Federated Multimodal Knowledge Graph Completion. - Ying Zhang 015; Yu Zhao 043; Xuhui Sui; Baohang Zhou; Xiangrui Cai; Li Shen 008; Xiaojie Yuan; Dacheng Tao (CoRR, 2025)

DFedADMM: Dual Constraint Controlled Model Inconsistency for Decentralize Federated Learning. - Qinglun Li; Li Shen 008; Guanghao Li; Quanjun Yin; Dacheng Tao (IEEE Trans. Pattern Anal. Mach. Intell., 2025)

Graph Convolutional Mixture-of-Experts Learner Network for Long-Tailed Domain Generalization. - Mengzhu Wang; Houcheng Su; Sijia Wang; Shanshan Wang 008; Nan Yin; Li Shen 008; Long Lan; Liang Yang 002; Xiaochun Cao (IEEE Trans. Circuits Syst. Video Technol., 2025)

LOST: Low-rank and Sparse Pre-training for Large Language Models. - Jiaxi Li; Lu Yin 006; Li Shen 008; Jinjin Xu; Liwu Xu; Tianjin Huang; Wenwu Wang 001; Shiwei Liu 003; Xilu Wang 001 (CoRR, 2025)

ADEM-VL: Adaptive and Embedded Fusion for Efficient Vision-Language Tuning. - Zhiwei Hao; Jianyuan Guo; Li Shen 008; Yong Luo 002; Han Hu 003; Yonggang Wen 001 (Int. J. Comput. Vis., 2025)

Data-Adaptive Weight-Ensembling for Multi-task Model Fusion. - Anke Tang; Li Shen 008; Yong Luo 002; Shiwei Liu 003; Han Hu 003; Bo Du 001; Dacheng Tao (Int. J. Comput. Vis., 2025)

On Nonconvex SGD Under Unbounded Noise With Weak Gradient Lipschitz and Delayed Stochastic Gradient. - Tao Sun 005; Li Shen 008; Xinwang Liu 002 (IEEE Trans. Pattern Anal. Mach. Intell., 2025)

Constraint Boundary Wandering Framework: Enhancing Constrained Optimization With Deep Neural Networks. - Shuang Wu; Shixiang Chen; Li Shen 008; Lefei Zhang; Dacheng Tao (IEEE Trans. Pattern Anal. Mach. Intell., 2025)

Asymmetrically Decentralized Federated Learning. - Qinglun Li; Miao Zhang; Nan Yin; Quanjun Yin; Li Shen 008; Xiaochun Cao (IEEE Trans. Computers, 2025)

Toward Understanding the Generalizability of Delayed Stochastic Gradient Descent. - Xiaoge Deng; Li Shen 008; Shengwei Li; Tao Sun 005; Dongsheng Li 001; Dacheng Tao (IEEE Trans. Pattern Anal. Mach. Intell., 2025)