Scaling-Up Item-Based Collaborative Filtering Recommendation Algorithm Based on Hadoop. - Jing Jiang 002; Jie Lu 001; Guangquan Zhang 001; Guodong Long (SERVICES, 2011)

TCSST: transfer classification of short & sparse text using external data. - Guodong Long; Ling Chen 006; Xingquan Zhu 001; Chengqi Zhang (CIKM, 2012)

Graph Based Feature Augmentation for Short and Sparse Text Classification. - Guodong Long; Jing Jiang 002 (ADMA (1), 2013)

Optimal Cloud Resource Auto-Scaling for Web Applications. - Jing Jiang 002; Jie Lu 001; Guangquan Zhang 001; Guodong Long (CCGRID, 2013)

Instance-based and feature-based classification enhancement for short & sparse texts - Guodong Long (2014)

Coupled Collaborative Filtering for Context-aware Recommendation. - Xinxin Jiang; Wei Liu 007; Longbing Cao; Guodong Long (AAAI, 2015)

SocialTrail: Recommending Social Trajectories from Location-Based Social Networks. - Qinzhe Zhang; Litao Yu; Guodong Long (ADC, 2015)

Invariant Event Tracking on Social Networks. - Sayan Unankard; Xue Li 001; Guodong Long (DASFAA (2), 2015)

Towards Mining Trapezoidal Data Streams. - Qin Zhang 011; Peng Zhang 001; Guodong Long; Wei Ding 003; Chengqi Zhang; Xindong Wu 001 (ICDM, 2015)

Discovering Sequential Rental Patterns by Fleet Tracking. - Xinxin Jiang; Xueping Peng; Guodong Long (ICDS, 2015)

Finding the best not the most: regularized loss minimization subgraph selection for graph classification. - Shirui Pan; Jia Wu 001; Xingquan Zhu 001; Guodong Long; Chengqi Zhang (Pattern Recognit., 2015)

Dynamic Concept Composition for Zero-Example Event Detection. - Xiaojun Chang; Yi Yang 001; Guodong Long; Chengqi Zhang; Alexander G. Hauptmann (AAAI, 2016)

Robust Semi-Supervised Learning through Label Aggregation. - Yan Yan 006; Zhongwen Xu; Ivor W. Tsang; Guodong Long; Yi Yang 001 (AAAI, 2016)

Global and Local Influence-based Social Recommendation. - Qinzhe Zhang; Jia Wu 001; Hong Yang 003; Weixue Lu; Guodong Long; Chengqi Zhang (CIKM, 2016)

Inferring Latent Network from Cascade Data for Dynamic Social Recommendation. - Qin Zhang 011; Jia Wu 001; Peng Zhang 001; Guodong Long; Ivor W. Tsang; Chengqi Zhang (ICDM, 2016)

Evolutionary lazy learning for Naive Bayes classification. - Yu Bai; Haishuai Wang; Jia Wu 001; Yun Zhang; Jing Jiang 002; Guodong Long (IJCNN, 2016)

Co-clustering enterprise social networks. - Ruiqi Hu; Shirui Pan; Guodong Long; Xingquan Zhu 001; Jing Jiang 002; Chengqi Zhang (IJCNN, 2016)

Exploring Heterogeneous Product Networks for Discovering Collective Marketing Hyping Behavior. - Qinzhe Zhang; Qin Zhang 011; Guodong Long; Peng Zhang 001; Chengqi Zhang (PAKDD (1), 2016)

Multiple graph unsupervised feature selection. - Xingzhong Du; Yan Yan 006; Pingbo Pan; Guodong Long; Lei Zhao 001 (Signal Process., 2016)

Diagnosis Code Assignment Using Sparsity-Based Disease Correlation Embedding. - Sen Wang 001; Xiaojun Chang; Xue Li 001; Guodong Long; Lina Yao 001; Quan Z. Sheng (IEEE Trans. Knowl. Data Eng., 2016)

Online Learning from Trapezoidal Data Streams. - Qin Zhang 011; Peng Zhang 001; Guodong Long; Wei Ding 003; Chengqi Zhang; Xindong Wu 001 (IEEE Trans. Knowl. Data Eng., 2016)

Towards Anomalous Diffusion Sources Detection in a Large Network. - Peng Zhang 001; Jing He 004; Guodong Long; Guangyan Huang; Chengqi Zhang (ACM Trans. Internet Techn., 2016)

Compact representation for large-scale unconstrained video analysis. - Sen Wang 001; Pingbo Pan; Guodong Long; Weitong Chen 001; Xue Li 001; Quan Z. Sheng (World Wide Web, 2016)

Graph Ladder Networks for Network Classification. - Ruiqi Hu; Shirui Pan; Jing Jiang 002; Guodong Long (CIKM, 2017)

MGAE: Marginalized Graph Autoencoder for Graph Clustering. - Chun Wang; Shirui Pan; Guodong Long; Xingquan Zhu 001; Jing Jiang 002 (CIKM, 2017)

Universal network representation for heterogeneous information networks. - Ruiqi Hu; Celina Ping Yu; Sai-Fu Fung; Shirui Pan; Haishuai Wang; Guodong Long (IJCNN, 2017)

Safe Medicine Recommendation via Medical Knowledge Graph Embedding. - Meng Wang 009; Mengyue Liu; Jun Liu 002; Sen Wang 001; Guodong Long; Buyue Qian (CoRR, 2017)

Collective Hyping Detection System for Identifying Online Spam Activities. - Qinzhe Zhang; Jia Wu 001; Peng Zhang 001; Guodong Long; Chengqi Zhang (IEEE Intell. Syst., 2017)

Boosting for graph classification with universum. - Shirui Pan; Jia Wu 001; Xingquan Zhu 001; Guodong Long; Chengqi Zhang (Knowl. Inf. Syst., 2017)

Task Sensitive Feature Exploration and Learning for Multitask Graph Classification. - Shirui Pan; Jia Wu 001; Xingquan Zhu 001; Guodong Long; Chengqi Zhang (IEEE Trans. Cybern., 2017)

Learning Multiple Diagnosis Codes for ICU Patients with Local Disease Correlation Mining. - Sen Wang 001; Xue Li 001; Xiaojun Chang; Lina Yao 001; Quan Z. Sheng; Guodong Long (ACM Trans. Knowl. Discov. Data, 2017)

Trace Ratio Optimization With Feature Correlation Mining for Multiclass Discriminant Analysis. - Forough Rezaei Boroujeni; Sen Wang 001; Zhihui Li 001; Nicholas West; Bela Stantic; Lina Yao 001; Guodong Long (AAAI, 2018)

DiSAN: Directional Self-Attention Network for RNN/CNN-Free Language Understanding. - Tao Shen 001; Tianyi Zhou 001; Guodong Long; Jing Jiang 002; Shirui Pan; Chengqi Zhang (AAAI, 2018)

Dynamic Illness Severity Prediction via Multi-task RNNs for Intensive Care Unit. - Weitong Chen 001; Sen Wang 001; Guodong Long; Lina Yao 001; Quan Z. Sheng; Xue Li 001 (ICDM, 2018)

Bi-Directional Block Self-Attention for Fast and Memory-Efficient Sequence Modeling. - Tao Shen 001; Tianyi Zhou 001; Guodong Long; Jing Jiang 002; Chengqi Zhang (ICLR (Poster), 2018)

Adversarially Regularized Graph Autoencoder for Graph Embedding. - Shirui Pan; Ruiqi Hu; Guodong Long; Jing Jiang 002; Lina Yao 001; Chengqi Zhang (IJCAI, 2018)

Reinforced Self-Attention Network: a Hybrid of Hard and Soft Attention for Sequence Modeling. - Tao Shen 001; Tianyi Zhou 001; Guodong Long; Jing Jiang 002; Sen Wang 001; Chengqi Zhang (IJCAI, 2018)

Multi-modality Sensor Data Classification with Selective Attention. - Xiang Zhang 012; Lina Yao 001; Chaoran Huang 001; Sen Wang 001; Mingkui Tan; Guodong Long; Can Wang 004 (IJCAI, 2018)

NeuRec: On Nonlinear Transformation for Personalized Ranking. - Shuai Zhang 007; Lina Yao 001; Aixin Sun; Sen Wang 001; Guodong Long; Manqing Dong (IJCAI, 2018)

Cross-Domain Deep Learning Approach For Multiple Financial Market Prediction. - Xinxin Jiang; Shirui Pan; Jing Jiang 002; Guodong Long (IJCNN, 2018)

Cost-sensitive Hybrid Neural Networks for Heterogeneous and Imbalanced Data. - Xinxin Jiang; Shirui Pan; Guodong Long; Jiang Chang; Jing Jiang 002; Chengqi Zhang (IJCNN, 2018)

Supervised Learning for Suicidal Ideation Detection in Online User Content. - Shaoxiong Ji; Celina Ping Yu; Sai-Fu Fung; Shirui Pan; Guodong Long (Complex., 2018)

Adversarially Regularized Graph Autoencoder. - Shirui Pan; Ruiqi Hu; Guodong Long; Jing Jiang 002; Lina Yao 001; Chengqi Zhang (CoRR, 2018)

Fast Directional Self-Attention Mechanism. - Tao Shen 001; Tianyi Zhou 001; Guodong Long; Jing Jiang 002; Chengqi Zhang (CoRR, 2018)

Dual influence embedded social recommendation. - Qinzhe Zhang; Jia Wu 001; Qin Zhang 011; Peng Zhang 001; Guodong Long; Chengqi Zhang (World Wide Web, 2018)

Distributionally Robust Semi-Supervised Learning for People-Centric Sensing. - Kaixuan Chen 001; Lina Yao 001; Dalin Zhang 001; Xiaojun Chang; Guodong Long; Sen Wang 001 (AAAI, 2019)

Interactive Deep Metric Learning for Healthcare Cohort Discovery. - Yang Wang 002; Guodong Long; Xueping Peng; Allison Clarke; Robin Stevenson; Leah Gerrard (AusDM, 2019)

Detecting Suicidal Ideation with Data Protection in Online Communities. - Shaoxiong Ji; Guodong Long; Shirui Pan; Tianqing Zhu; Jing Jiang 002; Sen Wang 001 (DASFAA (3), 2019)

Multi-Task Learning for Conversational Question Answering over a Large-Scale Knowledge Base. - Tao Shen 001; Xiubo Geng; Tao Qin 001; Daya Guo; Duyu Tang; Nan Duan; Guodong Long; Daxin Jiang (EMNLP/IJCNLP (1), 2019)

Temporal Self-Attention Network for Medical Concept Embedding. - Xueping Peng; Guodong Long; Tao Shen 001; Sen Wang 001; Jing Jiang 002; Michael Blumenstein (ICDM, 2019)

Collective Protection: Preventing Sensitive Inferences via Integrative Transformation. - Dalin Zhang 001; Lina Yao 001; Kaixuan Chen 001; Guodong Long; Sen Wang 001 (ICDM, 2019)

Prototype Propagation Networks (PPN) for Weakly-supervised Few-shot Learning on Category Graph. - Lu Liu 019; Tianyi Zhou 001; Guodong Long; Jing Jiang 002; Lina Yao 001; Chengqi Zhang (IJCAI, 2019)

Attributed Graph Clustering: A Deep Attentional Embedding Approach. - Chun Wang; Shirui Pan; Ruiqi Hu; Guodong Long; Jing Jiang 002; Chengqi Zhang (IJCAI, 2019)

Graph WaveNet for Deep Spatial-Temporal Graph Modeling. - Zonghan Wu; Shirui Pan; Guodong Long; Jing Jiang 002; Chengqi Zhang (IJCAI, 2019)

DAGCN: Dual Attention Graph Convolutional Networks. - Fengwen Chen; Shirui Pan; Jing Jiang 002; Huan Huo; Guodong Long (IJCNN, 2019)

Learning Private Neural Language Modeling with Attentive Aggregation. - Shaoxiong Ji; Shirui Pan; Guodong Long; Xue Li 001; Jing Jiang 002; Zi Huang (IJCNN, 2019)

Attentive Dual Embedding for Understanding Medical Concepts in Electronic Health Records. - Xueping Peng; Guodong Long; Shirui Pan; Jing Jiang 002; Zhendong Niu (IJCNN, 2019)

Adversarial Action Data Augmentation for Similar Gesture Action Recognition. - Di Wu 050; Junjun Chen; Nabin Sharma; Shirui Pan; Guodong Long; Michael Blumenstein (IJCNN, 2019)

Tensorized Self-Attention: Efficiently Modeling Pairwise and Global Dependencies Together. - Tao Shen 001; Tianyi Zhou 001; Guodong Long; Jing Jiang 002; Chengqi Zhang (NAACL-HLT (1), 2019)

Learning to Propagate for Graph Meta-Learning. - Lu Liu 019; Tianyi Zhou 001; Guodong Long; Jing Jiang 002; Chengqi Zhang (NeurIPS, 2019)

Decentralized Learning with Average Difference Aggregation for Proactive Online Social Care. - Shaoxiong Ji; Guodong Long; Shirui Pan; Tianqing Zhu; Jing Jiang 002; Sen Wang 001; Xue Li 001 (CoRR, 2019)

Effective Search of Logical Forms for Weakly Supervised Knowledge-Based Question Answering. - Tao Shen 001; Xiubo Geng; Tao Qin 001; Guodong Long; Jing Jiang 002; Daxin Jiang (CoRR, 2019)

Salient Subsequence Learning for Time Series Clustering. - Qin Zhang 011; Jia Wu 001; Peng Zhang 001; Guodong Long; Chengqi Zhang (IEEE Trans. Pattern Anal. Mach. Intell., 2019)

Cost-Sensitive Parallel Learning Framework for Insurance Intelligence Operation. - Xinxin Jiang; Shirui Pan; Guodong Long; Fei Xiong; Jing Jiang 002; Chengqi Zhang (IEEE Trans. Ind. Electron., 2019)

Going Deep: Graph Convolutional Ladder-Shape Networks. - Ruiqi Hu; Shirui Pan; Guodong Long; Qinghua Lu 001; Liming Zhu 001; Jing Jiang 002 (AAAI, 2020)

Self-Attention Enhanced Selective Gate with Entity-Aware Embedding for Distantly Supervised Relation Extraction. - Yang Li 154; Guodong Long; Tao Shen 001; Tianyi Zhou 001; Lina Yao 001; Huan Huo; Jing Jiang 002 (AAAI, 2020)

Attribute Propagation Network for Graph Zero-Shot Learning. - Lu Liu 019; Tianyi Zhou 001; Guodong Long; Jing Jiang 002; Chengqi Zhang (AAAI, 2020)

One-Shot Learning for Long-Tail Visual Relation Detection. - Weitao Wang; Meng Wang 009; Sen Wang 001; Guodong Long; Lina Yao 001; Guilin Qi; Yang Chen 008 (AAAI, 2020)

Competitive and Cooperative Heterogeneous Deep Reinforcement Learning. - Han Zheng; Jing Jiang 002; Pengfei Wei 001; Guodong Long; Chengqi Zhang (AAMAS, 2020)

RatE: Relation-Adaptive Translating Embedding for Knowledge Graph Completion. - Hao Huang; Guodong Long; Tao Shen 001; Jing Jiang 002; Chengqi Zhang (COLING, 2020)

Improving Long-Tail Relation Extraction with Collaborating Relation-Augmented Attention. - Yang Li 154; Tao Shen 001; Guodong Long; Jing Jiang 002; Tianyi Zhou 001; Chengqi Zhang (COLING, 2020)

Exploiting Structured Knowledge in Text via Graph-Guided Representation Learning. - Tao Shen 001; Yi Mao; Pengcheng He; Guodong Long; Adam Trischler; Weizhu Chen (EMNLP (1), 2020)

BiteNet: Bidirectional Temporal Encoder Network to Predict Medical Outcomes. - Xueping Peng; Guodong Long; Tao Shen 001; Sen Wang 001; Jing Jiang 002; Chengqi Zhang (ICDM, 2020)

Cross-Graph: Robust and Unsupervised Embedding for Attributed Graphs with Corrupted Structure. - Chun Wang; Bo Han 003; Shirui Pan; Jing Jiang 002; Gang Niu 001; Guodong Long (ICDM, 2020)

Effective Search of Logical Forms for Weakly Supervised Knowledge-Based Question Answering. - Tao Shen 001; Xiubo Geng; Guodong Long; Jing Jiang 002; Chengqi Zhang; Daxin Jiang (IJCAI, 2020)

Interpretable Time-series Classification on Few-shot Samples. - Wensi Tang; Lu Liu 019; Guodong Long (IJCNN, 2020)

Connecting the Dots: Multivariate Time Series Forecasting with Graph Neural Networks. - Zonghan Wu; Shirui Pan; Guodong Long; Jing Jiang 002; Xiaojun Chang; Chengqi Zhang (KDD, 2020)

Cooperative Heterogeneous Deep Reinforcement Learning. - Han Zheng; Pengfei Wei 001; Jing Jiang 002; Guodong Long; Qinghua Lu 001; Chengqi Zhang (NeurIPS, 2020)

Confusable Learning for Large-Class Few-Shot Classification. - Bingcong Li; Bo Han 003; Zhuowei Wang 003; Jing Jiang 002; Guodong Long (ECML/PKDD (2), 2020)

Self-attention Enhanced Patient Journey Understanding in Healthcare System. - Xueping Peng; Guodong Long; Tao Shen 001; Sen Wang 001; Jing Jiang 002 (ECML/PKDD (3), 2020)

Measuring Time-Sensitive and Topic-Specific Influence in Social Networks With LSTM and Self-Attention. - Cheng Zheng 004; Qin Zhang 011; Guodong Long; Chengqi Zhang; Sean D. Young; Wei Wang 010 (IEEE Access, 2020)

Rethinking 1D-CNN for Time Series Classification: A Stronger Baseline. - Wensi Tang; Guodong Long; Lu Liu 019; Tianyi Zhou 001; Jing Jiang 002; Michael Blumenstein (CoRR, 2020)

Semantic Triple Encoder for Fast Open-Set Link Prediction. - Bo Wang 069; Tao Shen 001; Guodong Long; Tianyi Zhou 001; Yi Chang 001 (CoRR, 2020)

Multi-Center Federated Learning. - Ming Xie; Guodong Long; Tao Shen 001; Tianyi Zhou 001; Xianzhi Wang 001; Jing Jiang 002 (CoRR, 2020)

Clustering social audiences in business information networks. - Yu Zheng 013; Ruiqi Hu; Sai-Fu Fung; Celina Ping Yu; Guodong Long; Ting Guo; Shirui Pan (Pattern Recognit., 2020)

Learning Graph Embedding With Adversarial Training Methods. - Shirui Pan; Ruiqi Hu; Sai-Fu Fung; Guodong Long; Jing Jiang 002; Chengqi Zhang (IEEE Trans. Cybern., 2020)

AMRNN: attended multi-task recurrent neural networks for dynamic illness severity prediction. - Weitong Chen 001; Guodong Long; Lina Yao 001; Quan Z. Sheng (World Wide Web, 2020)

Decentralized Knowledge Acquisition for Mobile Internet Applications. - Jing Jiang 002; Shaoxiong Ji; Guodong Long (World Wide Web, 2020)

Federated Learning for Open Banking. - Guodong Long; Yue Tan; Jing Jiang 002; Chengqi Zhang (Federated Learning, 2020)

Task Aligned Generative Meta-learning for Zero-shot Learning. - Zhe Liu 023; Yun Li; Lina Yao 001; Xianzhi Wang 001; Guodong Long (AAAI, 2021)

Reasoning over Entity-Action-Location Graph for Procedural Text Understanding. - Hao Huang; Xiubo Geng; Jian Pei 001; Guodong Long; Daxin Jiang (ACL/IJCNLP (1), 2021)

Eliminating Sentiment Bias for Aspect-Level Sentiment Classification with Unsupervised Opinion Extraction. - Bo Wang 069; Tao Shen 001; Guodong Long; Tianyi Zhou 001; Yi Chang 001 (EMNLP (Findings), 2021)

Sequential Diagnosis Prediction with Transformer and Ontological Representation. - Xueping Peng; Guodong Long; Tao Shen 001; Sen Wang 001; Jing Jiang 002 (ICDM, 2021)

A Universal Representation Transformer Layer for Few-Shot Image Classification. - Lu Liu 019; William L. Hamilton; Guodong Long; Jing Jiang 002; Hugo Larochelle (ICLR, 2021)

Isometric Propagation Network for Generalized Zero-shot Learning. - Lu Liu 019; Tianyi Zhou 001; Guodong Long; Jing Jiang 002; Xuanyi Dong; Chengqi Zhang (ICLR, 2021)

Hierarchical Features Integration and Attention Iteration Network for Juvenile Refractive Power Prediction. - Yang Zhang; Risa Higashita; Guodong Long; Rong Li; Daisuke Santo; Jiang Liu 001 (ICONIP (2), 2021)

Juvenile Refractive Power Prediction Based on Corneal Curvature and Axial Length via a Domain Knowledge Embedding Network. - Yang Zhang; Risa Higashita; Yanwu Xu 001; Daisuke Santo; Yan Hu; Guodong Long; Jiang Liu 001 (OMIA@MICCAI, 2021)

CO-PILOT: COllaborative Planning and reInforcement Learning On sub-Task curriculum. - Shuang Ao; Tianyi Zhou 001; Guodong Long; Qinghua Lu 001; Liming Zhu 001; Jing Jiang 002 (NeurIPS, 2021)

Structure-Augmented Text Representation Learning for Efficient Knowledge Graph Completion. - Bo Wang 069; Tao Shen 001; Guodong Long; Tianyi Zhou 001; Ying Wang 009; Yi Chang 001 (WWW, 2021)

Emerging Trends in Federated Learning: From Model Fusion to Federated X Learning. - Shaoxiong Ji; Teemu Saravirta; Shirui Pan; Guodong Long; Anwar Walid (CoRR, 2021)

FedProto: Federated Prototype Learning over Heterogeneous Devices. - Yue Tan; Guodong Long; Lu Liu 019; Tianyi Zhou 001; Jing Jiang 002 (CoRR, 2021)

MIMO: Mutual Integration of Patient Journey and Medical Ontology for Healthcare Representation Learning. - Xueping Peng; Guodong Long; Tao Shen 001; Sen Wang 001; Zhendong Niu; Chengqi Zhang (CoRR, 2021)

Federated Learning for Open Banking. - Guodong Long; Yue Tan; Jing Jiang 002; Chengqi Zhang (CoRR, 2021)

Federated Learning for Privacy-Preserving Open Innovation Future on Digital Health. - Guodong Long; Tao Shen 001; Yue Tan; Leah Gerrard; Allison Clarke; Jing Jiang 002 (CoRR, 2021)

TraverseNet: Unifying Space and Time in Message Passing. - Zonghan Wu; Da Zheng; Shirui Pan; Quan Gan; Guodong Long; George Karypis (CoRR, 2021)

MHieR-encoder: Modelling the high-frequency changes across stocks. - Zhineng Fu; Weijun Xu; Ruiqi Hu; Guodong Long; Jing Jiang 002 (Knowl. Based Syst., 2021)

Episodic memory governs choices: An RNN-based reinforcement learning model for decision-making task. - Xiaohan Zhang; Lu Liu 019; Guodong Long; Jing Jiang 002; Shenquan Liu (Neural Networks, 2021)

Suicidal Ideation Detection: A Review of Machine Learning Methods and Applications. - Shaoxiong Ji; Shirui Pan; Xue Li 001; Erik Cambria; Guodong Long; Zi Huang (IEEE Trans. Comput. Soc. Syst., 2021)

Exploring BCI Control in Smart Environments: Intention Recognition Via EEG Representation Enhancement Learning. - Lin Yue; Hao Shen; Sen Wang 001; Robert Boots; Guodong Long; Weitong Chen 001; Xiaowei Zhao 004 (ACM Trans. Knowl. Discov. Data, 2021)

A Comprehensive Survey on Graph Neural Networks. - Zonghan Wu; Shirui Pan; Fengwen Chen; Guodong Long; Chengqi Zhang; Philip S. Yu (IEEE Trans. Neural Networks Learn. Syst., 2021)

FedProto: Federated Prototype Learning across Heterogeneous Clients. - Yue Tan; Guodong Long; Lu Liu 019; Tianyi Zhou 001; Qinghua Lu 001; Jing Jiang 002; Chengqi Zhang (AAAI, 2022)

ClarET: Pre-training a Correlation-Aware Context-To-Event Transformer for Event-Centric Generation and Classification. - Yucheng Zhou 001; Tao Shen 001; Xiubo Geng; Guodong Long; Daxin Jiang (ACL (1), 2022)

Personalized Federated Learning with Robust Clustering Against Model Poisoning. - Jie Ma; Ming Xie; Guodong Long (ADMA (2), 2022)

Positive Unlabeled Learning by Sample Selection and Prototype Refinement. - Zhuowei Wang 003; Guodong Long (ADMA (1), 2022)

Robust Clustered Federated Learning with Bootstrap Median-of-Means. - Ming Xie; Jie Ma; Guodong Long; Chengqi Zhang (APWeb/WAIM (1), 2022)

Positive Unlabeled Learning by Semi-Supervised Learning. - Zhuowei Wang 003; Jing Jiang 002; Guodong Long (ICIP, 2022)

Omni-Scale CNNs: a simple and effective kernel size configuration for time series classification. - Wensi Tang; Guodong Long; Lu Liu 019; Tianyi Zhou 001; Michael Blumenstein; Jing Jiang 002 (ICLR, 2022)

EAT-C: Environment-Adversarial sub-Task Curriculum for Efficient Reinforcement Learning. - Shuang Ao; Tianyi Zhou 001; Jing Jiang 002; Guodong Long; Xuan Song 001; Chengqi Zhang (ICML, 2022)

Adaptive Graph Recurrent Network for Multivariate Time Series Imputation. - Yakun Chen; Zihao Li 005; Chao Yang 024; Xianzhi Wang 001; Guodong Long; Guandong Xu (ICONIP (5), 2022)

Personalized Federated Learning With a Graph. - Fengwen Chen; Guodong Long; Zonghan Wu; Tianyi Zhou 001; Jing Jiang 002 (IJCAI, 2022)

Understand before Answer: Improve Temporal Reading Comprehension via Precise Question Understanding. - Hao Huang; Xiubo Geng; Guodong Long; Daxin Jiang (NAACL-HLT, 2022)

Hierarchical Relation-Guided Type-Sentence Alignment for Long-Tail Relation Extraction with Distant Supervision. - Yang Li 154; Guodong Long; Tao Shen 001; Jing Jiang 002 (NAACL-HLT (Findings), 2022)

Federated Learning from Pre-Trained Models: A Contrastive Learning Approach. - Yue Tan; Guodong Long; Jie Ma; Lu Liu 019; Tianyi Zhou 001; Jing Jiang 002 (NeurIPS, 2022)

Federated Learning Operations (FLOps): Challenges, Lifecycle and Approaches. - Qi Cheng; Guodong Long (TAAI, 2022)

EventBERT: A Pre-Trained Model for Event Correlation Reasoning. - Yucheng Zhou 001; Xiubo Geng; Tao Shen 001; Guodong Long; Daxin Jiang (WWW, 2022)

On the Convergence of Clustered Federated Learning. - Jie Ma; Guodong Long; Tianyi Zhou 001; Jing Jiang 002; Chengqi Zhang (CoRR, 2022)

Personalized Federated Learning With Structure. - Fengwen Chen; Guodong Long; Zonghan Wu; Tianyi Zhou 001; Jing Jiang 002 (CoRR, 2022)

FedNoiL: A Simple Two-Level Sampling Method for Federated Learning with Noisy Labels. - Zhuowei Wang 003; Tianyi Zhou 001; Guodong Long; Bo Han 003; Jing Jiang 002 (CoRR, 2022)

Unsupervised Knowledge Graph Construction and Event-centric Knowledge Infusion for Scientific NLI. - Chenglin Wang 008; Yucheng Zhou 001; Guodong Long; Xiaodong Wang 006; Xiaowei Xu 005 (CoRR, 2022)

CCPrompt: Counterfactual Contrastive Prompt-Tuning for Many-Class Classification. - Yang Li 154; Canran Xu; Tao Shen 001; Jing Jiang 002; Guodong Long (CoRR, 2022)

Fine-Grained Distillation for Long Document Retrieval. - Yucheng Zhou 001; Tao Shen 001; Xiubo Geng; Chongyang Tao; Guodong Long; Can Xu; Daxin Jiang (CoRR, 2022)

Deep neighbor-aware embedding for node clustering in attributed graphs. - Chun Wang; Shirui Pan; Celina Ping Yu; Ruiqi Hu; Guodong Long; Chengqi Zhang (Pattern Recognit., 2022)

Many-Class Few-Shot Learning on Multi-Granularity Class Hierarchy. - Lu Liu 019; Tianyi Zhou 001; Guodong Long; Jing Jiang 002; Chengqi Zhang (IEEE Trans. Knowl. Data Eng., 2022)

SemiNLL: A Framework of Noisy-Label Learning by Semi-Supervised Learning. - Zhuowei Wang 003; Jing Jiang 002; Bo Han 003; Lei Feng 006; Bo An 001; Gang Niu 001; Guodong Long (Trans. Mach. Learn. Res., 2022)

Extracting Local Reasoning Chains of Deep Neural Networks. - Haiyan Zhao; Tianyi Zhou 001; Guodong Long; Jing Jiang 002; Chengqi Zhang (Trans. Mach. Learn. Res., 2022)

Federated Learning on Non-IID Graphs via Structural Knowledge Sharing. - Yue Tan; Yixin Liu 001; Guodong Long; Jing Jiang 002; Qinghua Lu 001; Chengqi Zhang (AAAI, 2023)

Improving the Robustness of Summarization Systems with Dual Augmentation. - Xiuying Chen; Guodong Long; Chongyang Tao; Mingzhe Li 001; Xin Gao 001; Chengqi Zhang; Xiangliang Zhang 001 (ACL (1), 2023)

Towards Robust Ranker for Text Retrieval. - Yucheng Zhou 001; Tao Shen 001; Xiubo Geng; Chongyang Tao; Can Xu; Guodong Long; Binxing Jiao; Daxin Jiang (ACL (Findings), 2023)

Multi-level Transformer for Cancer Outcome Prediction in Large-Scale Claims Data. - Leah Gerrard; Xueping Peng; Allison Clarke; Guodong Long (ADMA (3), 2023)

Soft Prompt Transfer for Zero-Shot and Few-Shot Learning in EHR Understanding. - Yang Wang 002; Xueping Peng; Tao Shen 001; Allison Clarke; Clement Schlegel; Paul Martin 014; Guodong Long (ADMA (3), 2023)

Improving Open-Domain Answer Sentence Selection by Distributed Clients with Privacy Preservation. - Weikuan Wang; Tao Shen 001; Michael Blumenstein; Guodong Long (ADMA (5), 2023)

From Time Series to Multi-modality: Classifying Multivariate Time Series via Both 1D and 2D Representations. - Chao Yang 024; Xianzhi Wang 001; Lina Yao 001; Guodong Long; Guandong Xu (ADMA (1), 2023)

WeightRelay: Efficient Heterogeneous Federated Learning on Time Series. - Wensi Tang; Guodong Long (AI (1), 2023)

Concept-Guided Interpretable Federated Learning. - Jianan Yang; Guodong Long (AI (2), 2023)

Style-Aware Contrastive Learning for Multi-Style Image Captioning. - Yucheng Zhou 001; Guodong Long (EACL (Findings), 2023)

Multimodal Event Transformer for Image-guided Story Ending Generation. - Yucheng Zhou 001; Guodong Long (EACL, 2023)

Improving Cross-modal Alignment for Text-Guided Image Inpainting. - Yucheng Zhou 001; Guodong Long (EACL, 2023)

Personalization Disentanglement for Federated Learning. - Peng Yan 002; Guodong Long (ICME, 2023)

Continual Task Allocation in Meta-Policy Network via Sparse Prompting. - Yijun Yang; Tianyi Zhou 001; Jing Jiang 002; Guodong Long; Yuhui Shi 001 (ICML, 2023)

Does Continual Learning Equally Forget All Parameters? - Haiyan Zhao; Tianyi Zhou 001; Guodong Long; Jing Jiang 002; Chengqi Zhang (ICML, 2023)

Prompt Federated Learning for Weather Forecasting: Toward Foundation Models on Meteorological Data. - Shengchao Chen; Guodong Long; Tao Shen 001; Jing Jiang 002 (IJCAI, 2023)

Dual Personalization on Federated Recommendation. - Chunxu Zhang; Guodong Long; Tianyi Zhou 001; Peng Yan 002; Zijian Zhang 009; Chengqi Zhang; Bo Yang 002 (IJCAI, 2023)

UnifieR: A Unified Retriever for Large-Scale Retrieval. - Tao Shen 001; Xiubo Geng; Chongyang Tao; Can Xu; Guodong Long; Kai Zhang 033; Daxin Jiang (KDD, 2023)

Structured Federated Learning through Clustered Additive Modeling. - Jie Ma; Tianyi Zhou 001; Guodong Long; Jing Jiang 002; Chengqi Zhang (NeurIPS, 2023)

Is Heterogeneity Notorious? Taming Heterogeneity to Handle Test-Time Shift in Federated Learning. - Yue Tan; Chen Chen 043; Weiming Zhuang; Xin Dong 009; Lingjuan Lyu; Guodong Long (NeurIPS, 2023)

Voting from Nearest Tasks: Meta-Vote Pruning of Pre-trained Models for Downstream Tasks. - Haiyan Zhao; Tianyi Zhou 001; Guodong Long; Jing Jiang 002; Chengqi Zhang (ECML/PKDD (2), 2023)

Neural Time Series Analysis with Fourier Transform: A Survey. - Kun Yi 001; Qi Zhang 020; Shoujin Wang; Hui He; Guodong Long; Zhendong Niu (CoRR, 2023)

Large Language Models are Strong Zero-Shot Retriever. - Tao Shen 001; Guodong Long; Xiubo Geng; Chongyang Tao; Tianyi Zhou 001; Daxin Jiang (CoRR, 2023)

Knowledge Refinement via Interaction Between Search Engines and Large Language Models. - Jiazhan Feng; Chongyang Tao; Xiubo Geng; Tao Shen 001; Can Xu; Guodong Long; Dongyan Zhao 001; Daxin Jiang (CoRR, 2023)

Graph-guided Personalization for Federated Recommendation. - Chunxu Zhang; Guodong Long; Tianyi Zhou 001; Peng Yan 002; Zijian Zhang 009; Bo Yang 002 (CoRR, 2023)

IFedRec: Item-Guided Federated Aggregation for Cold-Start. - Chunxu Zhang; Guodong Long; Tianyi Zhou 001; Xiangyu Zhao 001; Zijian Zhang 009; Bo Yang 002 (CoRR, 2023)

Spatial-temporal Prompt Learning for Federated Weather Forecasting. - Shengchao Chen; Guodong Long; Tao Shen 001; Tianyi Zhou 001; Jing Jiang 002 (CoRR, 2023)

Causal Reinforcement Learning: A Survey. - Zhihong Deng 001; Jing Jiang 002; Guodong Long; Chengqi Zhang (CoRR, 2023)

One-Shot Pruning for Fast-adapting Pre-trained Models on Devices. - Haiyan Zhao; Guodong Long (CoRR, 2023)

Re-Reading Improves Reasoning in Language Models. - Xiaohan Xu; Chongyang Tao; Tao Shen 001; Can Xu; Hongbo Xu; Guodong Long; Jianguang Lou (CoRR, 2023)

Curriculum Reinforcement Learning via Morphology-Environment Co-Evolution. - Shuang Ao; Tianyi Zhou 001; Guodong Long; Xuan Song 001; Jing Jiang 002 (CoRR, 2023)

Thread of Thought Unraveling Chaotic Contexts. - Yucheng Zhou 001; Xiubo Geng; Tao Shen 001; Chongyang Tao; Guodong Long; Jian-Guang Lou; Jianbing Shen (CoRR, 2023)

Foundation Models for Weather and Climate Data Understanding: A Comprehensive Survey. - Shengchao Chen; Guodong Long; Jing Jiang 002; Dikai Liu; Chengqi Zhang (CoRR, 2023)

UbiMeta: A Ubiquitous Operating System Model for Metaverse. - Yiqiang Chen 001; Wuliang Huang; Xinlong Jiang; Teng Zhang; Yi Wang; Bingjie Yan; Zhirui Wang; Qian Chen; Yunbing Xing; Dong Li; Guodong Long (Int. J. Crowd Sci., 2023)

Causal Reinforcement Learning: A Survey. - Zhihong Deng; Jing Jiang 002; Guodong Long; Chengqi Zhang (Trans. Mach. Learn. Res., 2023)

Multi-center federated learning: clients clustering for better personalization. - Guodong Long; Ming Xie; Tao Shen 001; Tianyi Zhou 001; Xianzhi Wang 001; Jing Jiang 002 (World Wide Web (WWW), 2023)

Attentional Gated Res2Net for Multivariate Time Series Classification. - Chao Yang 024; Xianzhi Wang 001; Lina Yao 001; Guodong Long; Jing Jiang 002; Guandong Xu (Neural Process. Lett., 2023)

Beyond Low-Pass Filtering: Graph Convolutional Networks With Automatic Filtering. - Zonghan Wu; Shirui Pan; Guodong Long; Jing Jiang 002; Chengqi Zhang (IEEE Trans. Knowl. Data Eng., 2023)

Fine-Grained Distillation for Long Document Retrieval. - Yucheng Zhou 001; Tao Shen 001; Xiubo Geng; Chongyang Tao; Jianbing Shen; Guodong Long; Can Xu; Daxin Jiang (AAAI, 2024)

Retrieval-Augmented Retrieval: Large Language Models are Strong Zero-Shot Retriever. - Tao Shen 001; Guodong Long; Xiubo Geng; Chongyang Tao; Yibin Lei; Tianyi Zhou 001; Michael Blumenstein; Daxin Jiang (ACL (Findings), 2024)

Synergistic Interplay between Search and Large Language Models for Information Retrieval. - Jiazhan Feng; Chongyang Tao; Xiubo Geng; Tao Shen 001; Can Xu; Guodong Long; Dongyan Zhao 001; Daxin Jiang (ACL (1), 2024)

Claimsformer: Pretrained Transformer for Administrative Claims Data to Predict Chronic Conditions. - Leah Gerrard; Xueping Peng; Allison Clarke; Guodong Long (AI (2), 2024)

Pre-training Cross-Modal Retrieval by Expansive Lexicon-Patch Alignment. - Yiyuan Yang; Guodong Long; Michael Blumenstein; Xiubo Geng; Chongyang Tao; Tao Shen 001; Daxin Jiang (LREC/COLING, 2024)

CCPrefix: Counterfactual Contrastive Prefix-Tuning for Many-Class Classification. - Yang Li 154; Canran Xu; Guodong Long; Tao Shen 001; Chongyang Tao; Jing Jiang 002 (EACL (1), 2024)

Re-Reading Improves Reasoning in Large Language Models. - Xiaohan Xu; Chongyang Tao; Tao Shen 001; Can Xu; Hongbo Xu; Guodong Long; Jian-Guang Lou; Shuai Ma 001 (EMNLP, 2024)

Extractive Medical Entity Disambiguation with Memory Mechanism and Memorized Entity Information. - Guobiao Zhang; Xueping Peng; Tao Shen 001; Guodong Long; Jiasheng Si; Libo Qin 001; Wenpeng Lu (EMNLP (Findings), 2024)

Federated Recommendation with Additive Personalization. - Zhiwei Li 007; Guodong Long; Tianyi Zhou 001 (ICLR, 2024)

Client-Supervised Federated Learning: Towards One-Model-for-All Personalization. - Peng Yan 002; Guodong Long (ICME, 2024)

Federated Prompt Learning for Weather Foundation Models on Devices. - Shengchao Chen; Guodong Long; Tao Shen 001; Jing Jiang 002; Chengqi Zhang (IJCAI, 2024)

What Hides behind Unfairness? Exploring Dynamics Fairness in Reinforcement Learning. - Zhihong Deng; Jing Jiang 002; Guodong Long; Chengqi Zhang (IJCAI, 2024)

The Rise of Federated Intelligence: From Federated Foundation Models Toward Collective Intelligence. - Guodong Long (IJCAI, 2024)

Federated Adaptation for Foundation Model-based Recommendations. - Chunxu Zhang; Guodong Long; Hongkuan Guo; Xiao Fang; Yang Song; Zhaojie Liu; Guorui Zhou; Zijian Zhang 009; Yang Liu 165; Bo Yang 002 (IJCAI, 2024)

BADFSS: Backdoor Attacks on Federated Self-Supervised Learning. - Jiale Zhang 001; Chengcheng Zhu; Di Wu 050; Xiaobing Sun 001; Jianming Yong; Guodong Long (IJCAI, 2024)

GPFedRec: Graph-Guided Personalization for Federated Recommendation. - Chunxu Zhang; Guodong Long; Tianyi Zhou 001; Zijian Zhang 009; Peng Yan 002; Bo Yang 002 (KDD, 2024)

Personalized Adapter for Large Meteorology Model on Devices: Towards Weather Foundation Models. - Shengchao Chen; Guodong Long; Jing Jiang 002; Chengqi Zhang (NeurIPS, 2024)

Dual-Personalizing Adapter for Federated Foundation Models. - Yiyuan Yang; Guodong Long; Tao Shen 001; Jing Jiang 002; Michael Blumenstein (NeurIPS, 2024)

Boosting Patient Representation Learning via Graph Contrastive Learning. - Zhenhao Zhang; Yuxi Liu; Jiang Bian; Antonio Jimeno-Yepes; Jun Shen 001; Fuyi Li; Guodong Long; Flora D. Salim (ECML/PKDD (9), 2024)

FL@FM-TheWebConf'24: International Workshop on Federated Foundation Models for the Web. - Irwin King; Guodong Long; Zenglin Xu; Han Yu 001 (WWW (Companion Volume), 2024)

When Federated Recommendation Meets Cold-Start Problem: Separating Item Attributes and User Interactions. - Chunxu Zhang; Guodong Long; Tianyi Zhou 001; Zijian Zhang 009; Peng Yan 002; Bo Yang 002 (WWW, 2024)

Multi-Level Additive Modeling for Structured Non-IID Federated Learning. - Shutong Chen; Tianyi Zhou 001; Guodong Long; Jie Ma; Jing Jiang 002; Chengqi Zhang (CoRR, 2024)

Navigating the Future of Federated Recommendation Systems with Foundation Models. - Zhiwei Li 007; Guodong Long (CoRR, 2024)

Personalized Interpretation on Federated Learning: A Virtual Concepts approach. - Peng Yan 002; Guodong Long; Jing Jiang 002; Michael Blumenstein (CoRR, 2024)

Influence-oriented Personalized Federated Learning. - Yue Tan; Guodong Long; Jing Jiang 002; Chengqi Zhang (CoRR, 2024)

WALL-E: World Alignment by Rule Learning Improves World Model-based LLM Agents. - Siyu Zhou; Tianyi Zhou 001; Yijun Yang; Guodong Long; Deheng Ye; Jing Jiang 002; Chengqi Zhang (CoRR, 2024)

Personalized Item Representations in Federated Multimodal Recommendation. - Zhiwei Li 007; Guodong Long; Jing Jiang 002; Chengqi Zhang (CoRR, 2024)

DMGNN: Detecting and Mitigating Backdoor Attacks in Graph Neural Networks. - Hao Sui; Bing Chen 002; Jiale Zhang 001; Chengcheng Zhu; Di Wu 050; Qinghua Lu 001; Guodong Long (CoRR, 2024)

Towards Next-Generation LLM-based Recommender Systems: A Survey and Beyond. - Qi Wang 078; Jindong Li 002; Shiqi Wang 006; Qianli Xing 002; Runliang Niu; He Kong; Rui Li 049; Guodong Long; Yi Chang 001; Chengqi Zhang (CoRR, 2024)

A fine-grained self-adapting prompt learning approach for few-shot learning with pre-trained language models. - Xiaojun Chen 006; Ting Liu; Philippe Fournier-Viger; Bowen Zhang 005; Guodong Long; Qin Zhang 011 (Knowl. Based Syst., 2024)

Exploring explicit and implicit graph learning for multivariate time series imputation. - Yakun Chen; Ruotong Hu; Zihao Li 005; Chao Yang 024; Xianzhi Wang 001; Guodong Long; Guandong Xu (Eng. Appl. Artif. Intell., 2024)

Dyformer: A dynamic transformer-based architecture for multivariate time series classification. - Chao Yang 024; Xianzhi Wang 001; Lina Yao 001; Guodong Long; Guandong Xu (Inf. Sci., 2024)

TraverseNet: Unifying Space and Time in Message Passing for Traffic Forecasting. - Zonghan Wu; Da Zheng; Shirui Pan; Quan Gan; Guodong Long; George Karypis (IEEE Trans. Neural Networks Learn. Syst., 2024)

Emerging trends in federated learning: from model fusion to federated X learning. - Shaoxiong Ji; Yue Tan; Teemu Saravirta; Zhiqin Yang; Yixin Liu 001; Lauri Vasankari; Shirui Pan; Guodong Long; Anwar Walid (Int. J. Mach. Learn. Cybern., 2024)

FedGE: Break the Scalability Limitation of Graph Neural Network With Federated Graph Embedding. - Fengwen Chen; Guodong Long (IEEE Trans. Big Data, 2024)

Federated Foundation Models on Heterogeneous Time Series. - Shengchao Chen; Guodong Long; Jing Jiang 002; Chengqi Zhang (AAAI, 2025)

Personalized Federated Collaborative Filtering: A Variational AutoEncoder Approach. - Zhiwei Li 007; Guodong Long; Tianyi Zhou 001; Jing Jiang 002; Chengqi Zhang (AAAI, 2025)

Multifaceted User Modeling in Recommendation: A Federated Foundation Models Approach. - Chunxu Zhang; Guodong Long; Hongkuan Guo; Zhaojie Liu; Guorui Zhou; Zijian Zhang 009; Yang Liu 165; Bo Yang 002 (AAAI, 2025)

DPC: Dual-Prompt Collaboration for Tuning Vision-Language Models. - Haoyang Li; Liang Wang; Chao Wang; Jing Jiang 002; Yan Peng; Guodong Long (CVPR, 2025)

AI for Women's Health: Framework and Focus Areas. - Jie Lu 001; Angela Dawson; Kairui Guo; Deborah Fox; Fahimeh Ramezani 001; Susan Morton; Kathleen Baird; Zelia Soo; Kezhi Lu; Guodong Long; Debra Anderson (WWW (Companion Volume), 2025)

Beyond Dataset Watermarking: Model-Level Copyright Protection for Code Summarization Models. - Jiale Zhang 001; Haoxuan Li; Di Wu 050; Xiaobing Sun 001; Qinghua Lu 001; Guodong Long (WWW, 2025)

eBaaS: AIoT-Enabled eBike Battery-Swap as a Service for Last-Mile Delivery. - Donghui Ding; Zhao Li 007; Jiarun Zhang; Xuanwu Liu; Ji Zhang 001; Yuchen Li 001; Peng Cai; JianXun Liu 001; Guodong Long (WWW, 2025)

FL@FM-TheWebConf'25: International Workshop on Federated Foundation Models for the Web 2025. - Irwin King; Guodong Long; Zenglin Xu; Yifei Zhang; Han Yu 001 (WWW (Companion Volume), 2025)

MedShort: Medicine Shortage Detection on Social Media with Privacy Preservation. - Xueping Peng; Peng Yan 002; Tao Shen 001; Ming Xie; Guodong Long (WWW (Companion Volume), 2025)

Federated Intelligence in Web: A Tutorial. - Peng Yan 002; Shengchao Chen; Guodong Long (WWW (Companion Volume), 2025)

Guest Editorial: Special Issue on Trustworthy Federated Learning. - Qiang Yang 001; Han Yu 001; Sin G. Teo; Bo Li 001; Guodong Long; Chao Jin; Lixin Fan; Yang Liu 165; Le Zhang 001 (IEEE Trans. Neural Networks Learn. Syst., 2025)

MAO: Efficient Model-Agnostic Optimization of Prompt Tuning for Vision-Language Models. - Haoyang Li; Siyu Zhou; Liang Wang; Guodong Long (CoRR, 2025)

FedMerge: Federated Personalization via Model Merging. - Shutong Chen; Tianyi Zhou 001; Guodong Long; Jing Jiang 002; Chengqi Zhang (CoRR, 2025)

Personalized Recommendation Models in Federated Settings: A Survey. - Chunxu Zhang; Guodong Long; Zijian Zhang 009; Zhiwei Li 007; Honglei Zhang; Qiang Yang 001; Bo Yang 002 (CoRR, 2025)

WALL-E 2.0: World Alignment by NeuroSymbolic Learning improves World Model-based LLM Agents. - Siyu Zhou; Tianyi Zhou 001; Yijun Yang; Guodong Long; Deheng Ye; Jing Jiang 002; Chengqi Zhang (CoRR, 2025)

Federated Adapter on Foundation Models: An Out-Of-Distribution Approach. - Yiyuan Yang; Guodong Long; Tianyi Zhou 001; Qinghua Lu 001; Shanshan Ye; Jing Jiang 002 (CoRR, 2025)

Federated Low-Rank Adaptation for Foundation Models: A Survey. - Yiyuan Yang; Guodong Long; Qinghua Lu 001; Liming Zhu 001; Jing Jiang 002; Chengqi Zhang (CoRR, 2025)

Learn to Preserve Personality: Federated Foundation Models in Recommendations. - Zhiwei Li 007; Guodong Long; Chunxu Zhang; Honglei Zhang; Jing Jiang 002; Chengqi Zhang (CoRR, 2025)

Distilling A Universal Expert from Clustered Federated Learning. - Zeqi Leng; Chunxu Zhang; Guodong Long; Riting Xia; Bo Yang 002 (CoRR, 2025)

Raw Data Matters: Enhancing Prompt Tuning by Internal Augmentation on Vision-Language Models. - Haoyang Li; Liang Wang; Chao Wang; Siyu Zhou; Jing Jiang 002; Yan Peng; Guodong Long (CoRR, 2025)

FeDaL: Federated Dataset Learning for Time Series Foundation Models. - Shengchao Chen; Guodong Long; Jing Jiang 002 (CoRR, 2025)

Adaptive Traffic Forecasting on Daily Basis: A Spatio-Temporal Context Learning Approach. - Xiaoyu Li; Yitian Zhang; Guodong Long; Yupeng Hu; Wenpeng Lu; Meng Chen 003; Chengqi Zhang; Yongshun Gong (IEEE Trans. Knowl. Data Eng., 2025)