Large scale app recommendation in Ant Financial. - Chaochao Chen 001; Xinxing Yang; Li Wang 056; Jun Zhou 011; Xiaolong Li 005 (IEEE BigData, 2017)

POSTER: Actively Detecting Implicit Fraudulent Transactions. - Shaosheng Cao; Xinxing Yang; Jun Zhou 011; Xiaolong Li 005; Yuan (Alan) Qi; Kai Xiao (CCS, 2017)

POSTER: Practical Fraud Transaction Prediction. - Longfei Li; Jun Zhou 011; Xiaolong Li 005; Tao Chen (CCS, 2017)

POSTER: Neural Network-based Graph Embedding for Malicious Accounts Detection. - Ziqi Liu; Chaochao Chen 001; Jun Zhou 011; Xiaolong Li 005; Feng Xu 008; Tao Chen; Le Song (CCS, 2017)

POSTER: A PU Learning based System for Potential Malicious URL Detection. - Ya-Lin Zhang 001; Longfei Li; Jun Zhou 011; Xiaolong Li 005; Yujiang Liu; Yuanchao Zhang; Zhi-Hua Zhou (CCS, 2017)

Locally Linear Factorization Machines. - Chenghao Liu; Teng Zhang; Peilin Zhao; Jun Zhou 011; Jianling Sun (IJCAI, 2017)

KunPeng: Parameter Server based Distributed Learning Systems and Its Applications in Alibaba and Ant Financial. - Jun Zhou 011; Xiaolong Li 005; Peilin Zhao; Chaochao Chen 001; Longfei Li; Xinxing Yang; Qing Cui; Jin Yu; Xu Chen 017; Yi Ding 006; Yuan (Alan) Qi (KDD, 2017)

Investigating Stroke-Level Information for Learning Chinese Word Embeddings. - Shaosheng Cao; Wei Lu 011; Jun Zhou 011; Xiaolong Li 005 (ISWC (Posters, Demos & Industry Tracks), 2017)

Locally Connected Deep Learning Framework for Industrial-scale Recommender Systems. - Cen Chen 001; Peilin Zhao; Longfei Li; Jun Zhou 011; Xiaolong Li 005; Minghui Qiu (WWW (Companion Volume), 2017)

PSMART: Parameter Server based Multiple Additive Regression Trees System. - Jun Zhou 011; Qing Cui; Xiaolong Li 005; Peilin Zhao; Shenquan Qu; Jun Huang 007 (WWW (Companion Volume), 2017)

Small-footprint Keyword Spotting Using Deep Neural Network and Connectionist Temporal Classifier. - Zhiming Wang; Xiaolong Li 005; Jun Zhou 011 (CoRR, 2017)

cw2vec: Learning Chinese Word Embeddings with Stroke n-gram Information. - Shaosheng Cao; Wei Lu 011; Jun Zhou 011; Xiaolong Li 005 (AAAI, 2018)

Privacy Preserving Point-of-Interest Recommendation Using Decentralized Matrix Factorization. - Chaochao Chen 001; Ziqi Liu; Peilin Zhao; Jun Zhou 011; Xiaolong Li 005 (AAAI, 2018)

NetDP: An Industrial-Scale Distributed Network Representation Framework for Default Prediction in Ant Credit Pay. - Jianbin Lin; Zhiqiang Zhang 012; Jun Zhou 011; Xiaolong Li 005; Jingli Fang; Yanming Fang; Quan Yu; Yuan (Alan) Qi (IEEE BigData, 2018)

Heterogeneous Graph Neural Networks for Malicious Account Detection. - Ziqi Liu; Chaochao Chen 001; Xinxing Yang; Jun Zhou 011; Xiaolong Li 005; Le Song (CIKM, 2018)

Unpack Local Model Interpretation for GBDT. - Wenjing Fang; Jun Zhou 011; Xiaolong Li 005; Kenny Q. Zhu (DASFAA (2), 2018)

An Industrial-Scale System for Heterogeneous Information Card Ranking in Alipay. - Zhiqiang Zhang 012; Chaochao Chen 001; Jun Zhou 011; Xiaolong Li 005 (DASFAA (2), 2018)

Distributed Collaborative Hashing and Its Applications in Ant Financial. - Chaochao Chen 001; Ziqi Liu; Peilin Zhao; Longfei Li; Jun Zhou 011; Xiaolong Li 005 (KDD, 2018)

Cross-Domain Review Helpfulness Prediction Based on Convolutional Neural Networks with Auxiliary Domain Discriminators. - Cen Chen 001; Yinfei Yang; Jun Zhou 011; Xiaolong Li 005; Forrest Sheng Bao (NAACL-HLT (2), 2018)

A Local Online Learning Approach for Non-linear Data. - Xinxing Yang; Jun Zhou 011; Peilin Zhao; Cen Chen 001; Chaochao Chen 001; Xiaolong Li 005 (PAKDD (2), 2018)

Anomaly Detection with Partially Observed Anomalies. - Ya-Lin Zhang 001; Longfei Li; Jun Zhou 011; Xiaolong Li 005; Zhi-Hua Zhou (WWW (Companion Volume), 2018)

GeniePath: Graph Neural Networks with Adaptive Receptive Paths. - Ziqi Liu; Chaochao Chen 001; Longfei Li; Jun Zhou 011; Xiaolong Li 005; Le Song (CoRR, 2018)

Time-sensitive Customer Churn Prediction based on PU Learning. - Li Wang 056; Chaochao Chen 001; Jun Zhou 011; Xiaolong Li 005 (CoRR, 2018)

A Boosting Framework of Factorization Machine. - Longfei Li; Peilin Zhao; Jun Zhou 011; Xiaolong Li 005 (CoRR, 2018)

Feature Propagation on Graph: A New Perspective to Graph Representation Learning. - Biao Xiang; Ziqi Liu; Jun Zhou 011; Xiaolong Li 005 (CoRR, 2018)

Distributed Deep Forest and its Application to Automatic Detection of Cash-out Fraud. - Ya-Lin Zhang 001; Jun Zhou 011; Wenhao Zheng 001; Ji Feng; Longfei Li; Ziqi Liu; Ming Li 005; Zhiqiang Zhang 012; Chaochao Chen 001; Xiaolong Li 005; Zhi-Hua Zhou (CoRR, 2018)

Review Helpfulness Prediction with Embedding-Gated CNN. - Cen Chen 001; Minghui Qiu; Yinfei Yang; Jun Zhou 011; Jun Huang 007; Xiaolong Li 005; Forrest Sheng Bao (CoRR, 2018)

Cash-Out User Detection Based on Attributed Heterogeneous Information Network with a Hierarchical Attention Mechanism. - Binbin Hu; Zhiqiang Zhang 012; Chuan Shi 001; Jun Zhou 011; Xiaolong Li 005; Yuan Qi 001 (AAAI, 2019)

GeniePath: Graph Neural Networks with Adaptive Receptive Paths. - Ziqi Liu; Chaochao Chen 001; Longfei Li; Jun Zhou 011; Xiaolong Li 005; Le Song; Yuan Qi 001 (AAAI, 2019)

InfDetect: a Large Scale Graph-based Fraud Detection System for E-Commerce Insurance. - Cen Chen 001; Chen Liang; Jianbin Lin; Li Wang 056; Ziqi Liu; Xinxing Yang; Jun Zhou 011; Shuang Yang; Yuan Qi 001 (IEEE BigData, 2019)

Adapted Tree Boosting for Transfer Learning. - Wenjing Fang; Chaochao Chen 001; Bowen Song; Li Wang 056; Jun Zhou 011; Kenny Q. Zhu (IEEE BigData, 2019)

DSSLP: A Distributed Framework for Semi-supervised Link Prediction. - Dalong Zhang; Xianzheng Song; Ziqi Liu; Zhiqiang Zhang 012; Xin Huang; Lin Wang 098; Jun Zhou 011 (IEEE BigData, 2019)

Graph Representation Learning for Merchant Incentive Optimization in Mobile Payment Marketing. - Ziqi Liu; Dong Wang 062; Qianyu Yu 001; Zhiqiang Zhang 012; Yue Shen; Jian Ma; Wenliang Zhong; Jinjie Gu; Jun Zhou 011; Shuang Yang; Yuan Qi 001 (CIKM, 2019)

A Semi-Supervised Graph Attentive Network for Financial Fraud Detection. - Daixin Wang; Yuan Qi 001; Jianbin Lin; Peng Cui 001; Quanhui Jia; Zhen Wang; Yanming Fang; Quan Yu; Jun Zhou 011; Shuang Yang (ICDM, 2019)

AntProphet: an Intention Mining System behind Alipay's Intelligent Customer Service Bot. - Cen Chen 001; Xiaolu Zhang; Sheng Ju; Chilin Fu; Caizhi Tang; Jun Zhou 011; Xiaolong Li 005 (IJCAI, 2019)

Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection. - Bingzhe Wu; Shiwan Zhao; Chaochao Chen 001; Haoyang Xu; Li Wang 056; Xiaolu Zhang; Guangyu Sun 003; Jun Zhou 011 (NeurIPS, 2019)

How Much Can A Retailer Sell? Sales Forecasting on Tmall. - Chaochao Chen 001; Ziqi Liu; Jun Zhou 011; Xiaolong Li 005; Yuan Qi 001; Yujing Jiao; Xingyu Zhong (PAKDD (2), 2019)

RNE: A Scalable Network Embedding for Billion-Scale Recommendation. - Jianbin Lin; Daixin Wang; Lu Guan; Yin Zhao; Binqiang Zhao; Jun Zhou 011; Xiaolong Li 005; Yuan (Alan) Qi (PAKDD (2), 2019)

Reinforcement Learning for User Intent Prediction in Customer Service Bots. - Cen Chen 001; Chilin Fu; Xu Hu; Xiaolu Zhang; Jun Zhou 011; Xiaolong Li 005; Forrest Sheng Bao (SIGIR, 2019)

Uncovering Insurance Fraud Conspiracy with Network Learning. - Chen Liang; Ziqi Liu; Bin Liu; Jun Zhou 011; Xiaolong Li 005; Shuang Yang; Yuan Qi 001 (SIGIR, 2019)

Multi-Domain Gated CNN for Review Helpfulness Prediction. - Cen Chen 001; Minghui Qiu; Yinfei Yang; Jun Zhou 011; Jun Huang 007; Xiaolong Li 005; Forrest Sheng Bao (WWW, 2019)

A Time Attention based Fraud Transaction Detection Framework. - Longfei Li; Ziqi Liu; Chaochao Chen 001; Ya-Lin Zhang 001; Jun Zhou 011; Xiaolong Li 005 (CoRR, 2019)

TitAnt: Online Real-time Transaction Fraud Detection in Ant Financial. - Shaosheng Cao; Xinxing Yang; Cen Chen 001; Jun Zhou 011; Xiaolong Li 005; Yuan Qi 001 (Proc. VLDB Endow., 2019)

Distributed Deep Forest and its Application to Automatic Detection of Cash-Out Fraud. - Ya-Lin Zhang 001; Jun Zhou 011; Wenhao Zheng 001; Ji Feng; Longfei Li; Ziqi Liu; Ming Li 005; Zhiqiang Zhang 012; Chaochao Chen 001; Xiaolong Li 005; Yuan (Alan) Qi; Zhi-Hua Zhou (ACM Trans. Intell. Syst. Technol., 2019)

Pruning from Scratch. - Yulong Wang; Xiaolu Zhang; Lingxi Xie; Jun Zhou 011; Hang Su 006; Bo Zhang 010; Xiaolin Hu 001 (AAAI, 2020)

Characterizing Membership Privacy in Stochastic Gradient Langevin Dynamics. - Bingzhe Wu; Chaochao Chen 001; Shiwan Zhao; Cen Chen 001; Yuan Yao; Guangyu Sun 003; Li Wang 056; Xiaolu Zhang; Jun Zhou 011 (AAAI, 2020)

Nebula: A Scalable Privacy-Preserving Machine Learning System in Ant Financial. - Cen Chen 001; Bingzhe Wu; Li Wang 056; Chaochao Chen 001; Jin Tan; Lei Wang 152; Jun Zhou 011; Benyu Zhang (CIKM, 2020)

Loan Default Analysis with Multiplex Graph Learning. - Binbin Hu; Zhiqiang Zhang 012; Jun Zhou 011; Jingli Fang; Quanhui Jia; Yanming Fang; Quan Yu; Yuan Qi 001 (CIKM, 2020)

aDMSCN: A Novel Perspective for User Intent Prediction in Customer Service Bots. - Kuan Xu; Chilin Fu; Xiaolu Zhang; Cen Chen 001; Ya-Lin Zhang 001; Wenge Rong; Zujie Wen; Jun Zhou 011; Xiaolong Li 005; Yu Qiao 001 (CIKM, 2020)

EasyGML: A Fully-functional and Easy-to-use Platform for Industrial Graph Machine Learning. - Zhiqiang Zhang 012; Jun Zhou 011; Chuan Shi 001 (CIKM, 2020)

Secure Social Recommendation Based on Secret Sharing. - Chaochao Chen 001; Liang Li; Bingzhe Wu; Cheng Hong 001; Li Wang 056; Jun Zhou 011 (ECAI, 2020)

Generating Natural Language Adversarial Examples on a Large Scale with Generative Models. - Yankun Ren; Jianbin Lin; Siliang Tang; Jun Zhou 011; Shuang Yang; Yuan Qi 001; Xiang Ren 001 (ECAI, 2020)

SAFE: Scalable Automatic Feature Engineering Framework for Industrial Tasks. - Qitao Shi; Ya-Lin Zhang 001; Longfei Li; Xinxing Yang; Meng Li; Jun Zhou 011 (ICDE, 2020)

Financial Risk Analysis for SMEs with Graph-based Supply Chain Mining. - Shuo Yang; Zhiqiang Zhang 012; Jun Zhou 011; Yang Wang; Wang Sun; Xingyu Zhong; Yanming Fang; Quan Yu; Yuan Qi 001 (IJCAI, 2020)

Hubble: An Industrial System for Audience Expansion in Mobile Marketing. - Chenyi Zhuang; Ziqi Liu; Zhiqiang Zhang 012; Yize Tan; Zhengwei Wu; Zhining Liu 001; Jianping Wei; Jinjie Gu; Guannan Zhang; Jun Zhou 011; Yuan Qi 001 (KDD, 2020)

Bandit Samplers for Training Graph Neural Networks. - Ziqi Liu; Zhengwei Wu; Zhiqiang Zhang 012; Jun Zhou 011; Shuang Yang; Le Song; Yuan Qi 001 (NeurIPS, 2020)

Data-Free Adversarial Perturbations for Practical Black-Box Attack. - Zhaoxin Huan; Yulong Wang; Xiaolu Zhang; Lin Shang 001; Chilin Fu; Jun Zhou 011 (PAKDD (2), 2020)

AutoRec: A Comprehensive Platform for Building Effective and Explainable Recommender Models. - Qing Cui; Qitao Shi; Hao Qian 003; Caizhi Tang; Xixi Li; Yiming Zhao; Tao Jiang; Longfei Li; Jun Zhou 011 (ECML/PKDD (5), 2020)

Automatic Knowledge Fusion in Transferrable Networks for Semantic Text Matching. - Cen Chen 001; Ya-Lin Zhang 001; Minghui Qiu; Bingzhe Wu; Li Wang 056; Longfei Li; Jun Zhou 011 (WWW (Companion Volume), 2020)

Neural Zero-Shot Fine-Grained Entity Typing. - Yankun Ren; Jianbin Lin; Jun Zhou 011 (WWW (Companion Volume), 2020)

Privacy Preserving PCA for Multiparty Modeling. - Yingting Liu; Chaochao Chen 001; Longfei Zheng; Li Wang 056; Jun Zhou 011; Guiquan Liu (CoRR, 2020)

AGL: a Scalable System for Industrial-purpose Graph Machine Learning. - Dalong Zhang; Xin Huang; Ziqi Liu; Zhiyang Hu; Xianzheng Song; Zhibang Ge; Zhiqiang Zhang 012; Lin Wang 098; Jun Zhou 011; Shuang Yang; Yuan Qi 001 (CoRR, 2020)

InfDetect: a Large Scale Graph-based Fraud Detection System for E-Commerce Insurance. - Cen Chen 001; Chen Liang; Jianbin Lin; Li Wang 056; Ziqi Liu; Xinxing Yang; Xiukun Wang; Jun Zhou 011; Shuang Yang; Yuan Qi 001 (CoRR, 2020)

Practical Privacy Preserving POI Recommendation. - Chaochao Chen 001; Bingzhe Wu; Wenjin Fang; Jun Zhou 011; Li Wang 056; Yuan Qi 001; Xiaolin Zheng (CoRR, 2020)

Industrial Scale Privacy Preserving Deep Neural Network. - Longfei Zheng; Chaochao Chen 001; Yingting Liu; Bingzhe Wu; Xibin Wu; Li Wang 056; Lei Wang 152; Jun Zhou 011; Shuang Yang (CoRR, 2020)

Secret Sharing based Secure Regressions with Applications. - Chaochao Chen 001; Liang Li; Wenjing Fang; Jun Zhou 011; Li Wang 056; Lei Wang 152; Shuang Yang; Alex Liu; Hao Wang 007 (CoRR, 2020)

A Hybrid-Domain Framework for Secure Gradient Tree Boosting. - Wenjing Fang; Chaochao Chen 001; Jin Tan; Chaofan Yu; Yufei Lu; Li Wang 056; Lei Wang 152; Jun Zhou 011; Alex X (CoRR, 2020)

Privacy-Preserving Graph Neural Network for Node Classification. - Jun Zhou 011; Chaochao Chen 001; Longfei Zheng; Xiaolin Zheng; Bingzhe Wu; Ziqi Liu; Li Wang 056 (CoRR, 2020)

When Homomorphic Encryption Marries Secret Sharing: Secure Large-Scale Sparse Logistic Regression and Applications in Risk Control. - Chaochao Chen 001; Jun Zhou 011; Li Wang 056; Xibin Wu; Wenjing Fang; Jin Tan; Lei Wang 152; Xiaoxi Ji; Alex Liu; Hao Wang 007; Cheng Hong 001 (CoRR, 2020)

Heterogeneous Graph Neural Network for Recommendation. - Jinghan Shi; Houye Ji; Chuan Shi 001; Xiao Wang 017; Zhiqiang Zhang 012; Jun Zhou 011 (CoRR, 2020)

Self-supervised Smoothing Graph Neural Networks. - Lu Yu 006; Shichao Pei; Chuxu Zhang; Lizhong Ding 001; Jun Zhou 011; Longfei Li; Xiangliang Zhang 001 (CoRR, 2020)

A Comprehensive Analysis of Information Leakage in Deep Transfer Learning. - Cen Chen 001; Bingzhe Wu; Minghui Qiu; Li Wang 057; Jun Zhou 011 (CoRR, 2020)

Towards Scalable and Privacy-Preserving Deep Neural Network via Algorithmic-Cryptographic Co-design. - Chaochao Chen 001; Jun Zhou 011; Longfei Zheng; Yan Wang 002; Xiaolin Zheng; Bingzhe Wu; Cen Chen 001; Li Wang 056; Jianwei Yin (CoRR, 2020)

AGL: A Scalable System for Industrial-purpose Graph Machine Learning. - Dalong Zhang; Xin Huang; Ziqi Liu; Jun Zhou 011; Zhiyang Hu; Xianzheng Song; Zhibang Ge; Lin Wang 098; Zhiqiang Zhang 012; Yuan Qi 001 (Proc. VLDB Endow., 2020)

Practical Privacy Preserving POI Recommendation. - Chaochao Chen 001; Jun Zhou 011; Bingzhe Wu; Wenjing Fang; Li Wang 056; Yuan Qi 001; Xiaolin Zheng (ACM Trans. Intell. Syst. Technol., 2020)

A Graph Attention Network Model for GMV Forecast on Online Shopping Festival. - Qianyu Yu 001; Shuo Yang; Zhiqiang Zhang 012; Ya-Lin Zhang 001; Binbin Hu; Ziqi Liu; Kai Huang; Xingyu Zhong; Jun Zhou 011; Yanming Fang (APWeb/WAIM (1), 2021)

Large-scale Secure XGB for Vertical Federated Learning. - Wenjing Fang; Derun Zhao; Jin Tan; Chaochao Chen 001; Chaofan Yu; Li Wang 056; Lei Wang 152; Jun Zhou 011; Benyu Zhang (CIKM, 2021)

Learning Representations of Inactive Users: A Cross Domain Approach with Graph Neural Networks. - Ziqi Liu; Yue Shen; Xiaocheng Cheng; Qiang Li 022; Jianping Wei; Zhiqiang Zhang 012; Dong Wang 062; Xiaodong Zeng; Jinjie Gu; Jun Zhou 011 (CIKM, 2021)

Conditional Graph Attention Networks for Distilling and Refining Knowledge Graphs in Recommendation. - Ke Tu; Peng Cui 001; Daixin Wang; Zhiqiang Zhang 012; Jun Zhou 011; Yuan Qi 001; Wenwu Zhu 001 (CIKM, 2021)

Low-dimensional Alignment for Cross-Domain Recommendation. - Tianxin Wang; Fuzhen Zhuang; Zhiqiang Zhang 012; Daixin Wang; Jun Zhou 011; Qing He 003 (CIKM, 2021)

Counterfactual Review-based Recommendation. - Kun Xiong; Wenwen Ye; Xu Chen 017; Yongfeng Zhang; Wayne Xin Zhao; Binbin Hu; Zhiqiang Zhang 012; Jun Zhou 011 (CIKM, 2021)

SIFN: A Sentiment-aware Interactive Fusion Network for Review-based Item Recommendation. - Kai Zhang 038; Hao Qian 003; Qi Liu 003; Zhiqiang Zhang 012; Jun Zhou 011; Jianhui Ma; Enhong Chen (CIKM, 2021)

AntOpt: A Multi-functional Large-scale Decision Optimization Platform. - Jun Zhou 011; Yang Bao 008; Hua Wu; Zhigang Hua (CIKM, 2021)

Improving Transferability of Adversarial Patches on Face Recognition With Generative Models. - Zihao Xiao 002; Xianfeng Gao; Chilin Fu; Yinpeng Dong; Wei Gao; Xiaolu Zhang; Jun Zhou 011; Jun Zhu 001 (CVPR, 2021)

Constraint-Adaptive Rule Mining in Large Databases. - Meng Li; Ya-Lin Zhang 001; Qitao Shi; Xinxing Yang; Qing Cui; Longfei Li; Jun Zhou 011 (DASFAA (3), 2021)

IntelliTag: An Intelligent Cloud Customer Service System Based on Tag Recommendation. - Minghui Yang; Shaosheng Cao; Binbin Hu; Xianling Chen; Hengbin Cui; Zhiqiang Zhang 012; Jun Zhou 011; Xiaolong Li 005 (ICDE, 2021)

Simtrojan: Stealthy Backdoor Attack. - Yankun Ren; Longfei Li; Jun Zhou 011 (ICIP, 2021)

Rethinking the Effectiveness of Selective Attention in Neural Networks. - Yulong Wang; Xiaolu Zhang; Jun Zhou 011; Hang Su 006 (ICONIP (3), 2021)

Cross-Domain Recommendation: Challenges, Progress, and Prospects. - Feng Zhu 011; Yan Wang 002; Chaochao Chen 001; Jun Zhou 011; Longfei Li; Guanfeng Liu 001 (IJCAI, 2021)

A Classification Based Ensemble Pruning Framework with Multi-metric Consideration. - Ya-Lin Zhang 001; Qitao Shi; Meng Li; Xinxing Yang; Longfei Li; Jun Zhou 011 (IntelliSys (1), 2021)

When Homomorphic Encryption Marries Secret Sharing: Secure Large-Scale Sparse Logistic Regression and Applications in Risk Control. - Chaochao Chen 001; Jun Zhou 011; Li Wang 056; Xibin Wu; Wenjing Fang; Jin Tan; Lei Wang 152; Alex X. Liu; Hao Wang 007; Cheng Hong 001 (KDD, 2021)

A Bi-Level Framework for Learning to Solve Combinatorial Optimization on Graphs. - Runzhong Wang; Zhigang Hua; Gan Liu; Jiayi Zhang 003; Junchi Yan; Feng Qi 005; Shuang Yang; Jun Zhou 011; Xiaokang Yang 001 (NeurIPS, 2021)

MixSeq: Connecting Macroscopic Time Series Forecasting with Microscopic Time Series Data. - Zhibo Zhu; Ziqi Liu; Ge Jin; Zhiqiang Zhang 012; Lei Chen 051; Jun Zhou 011; Jianyong Zhou (NeurIPS, 2021)

Inductive Link Prediction with Interactive Structure Learning on Attributed Graph. - Shuo Yang; Binbin Hu; Zhiqiang Zhang 012; Wang Sun; Yang Wang; Jun Zhou 011; Hongyu Shan; Yuetian Cao; Borui Ye; Yanming Fang; Quan Yu (ECML/PKDD (2), 2021)

Temporal-Aware Graph Neural Network for Credit Risk Prediction. - Daixin Wang; Zhiqiang Zhang 012; Jun Zhou 011; Peng Cui 001; Jingli Fang; Quanhui Jia; Yanming Fang; Yuan Qi 001 (SDM, 2021)

Learning to Select Instance: Simultaneous Transfer Learning and Clustering. - Zhaoxin Huan; Yulong Wang; Yong He 009; Xiaolu Zhang; Chilin Fu; Weichang Wu; Jun Zhou 011; Ke Ding; Liang Zhang; Linjian Mo (SIGIR, 2021)

Multi-Interactive Attention Network for Fine-grained Feature Learning in CTR Prediction. - Kai Zhang 038; Hao Qian 003; Qing Cui; Qi Liu 003; Longfei Li; Jun Zhou 011; Jianhui Ma; Enhong Chen (WSDM, 2021)

PPSGCN: A Privacy-Preserving Subgraph Sampling Based Distributed GCN Training Method. - Binchi Zhang; Minnan Luo; Shangbin Feng; Ziqi Liu; Jun Zhou 011; Qinghua Zheng (CoRR, 2021)

Conditional Attention Networks for Distilling Knowledge Graphs in Recommendation. - Ke Tu; Peng Cui 001; Daixin Wang; Zhiqiang Zhang 012; Jun Zhou 011; Yuan Qi 001; Wenwu Zhu 001 (CoRR, 2021)

Adaptive Client Sampling in Federated Learning via Online Learning with Bandit Feedback. - Boxin Zhao; Ziqi Liu; Chaochao Chen 001; Mladen Kolar; Zhiqiang Zhang 012; Jun Zhou 011 (CoRR, 2021)

A Boosting Framework of Factorization Machine. - Jun Zhou 011; Longfei Li; Ziqi Liu; Chaochao Chen 001 (Int. J. Pattern Recognit. Artif. Intell., 2021)

ASFGNN: Automated separated-federated graph neural network. - Longfei Zheng; Jun Zhou 011; Chaochao Chen 001; Bingzhe Wu; Li Wang 056; Benyu Zhang (Peer-to-Peer Netw. Appl., 2021)

SAIL: Self-Augmented Graph Contrastive Learning. - Lu Yu 006; Shichao Pei; Lizhong Ding 001; Jun Zhou 011; Longfei Li; Chuxu Zhang; Xiangliang Zhang 001 (AAAI, 2022)

Regularizing Graph Neural Networks via Consistency-Diversity Graph Augmentations. - Deyu Bo; Binbin Hu; Xiao Wang 017; Zhiqiang Zhang 012; Chuan Shi 001; Jun Zhou 011 (AAAI, 2022)

Robust Heterogeneous Graph Neural Networks against Adversarial Attacks. - Mengmei Zhang; Xiao Wang 017; Meiqi Zhu; Chuan Shi 001; Zhiqiang Zhang 012; Jun Zhou 011 (AAAI, 2022)

Robust Direct Learning for Causal Data Fusion. - Xinyu Li; Yilin Li; Qing Cui; Longfei Li; Jun Zhou 011 (ACML, 2022)

A Task-Aware Attention-Based Method for Improved Meta-Learning. - Yue Zhang; Xinxing Yang; Feng Zhu 011; Yalin Zhang 001; Meng Li; Qitao Shi; Longfei Li; Jun Zhou 011 (APWeb/WAIM (2), 2022)

A Biased Sampling Method for Imbalanced Personalized Ranking. - Lu Yu 006; Shichao Pei; Feng Zhu 011; Longfei Li; Jun Zhou 011; Chuxu Zhang; Xiangliang Zhang 001 (CIKM, 2022)

Semi-Supervised Learning with Data Augmentation for Tabular Data. - Jun-Peng Fang; Caizhi Tang; Qing Cui; Feng Zhu 011; Longfei Li; Jun Zhou 011; Wei Zhu (CIKM, 2022)

GraTO: Graph Neural Network Framework Tackling Over-smoothing with Neural Architecture Search. - Xinshun Feng; Herun Wan; Shangbin Feng; Hongrui Wang 004; Qinghua Zheng; Jun Zhou 011; Minnan Luo (CIKM, 2022)

A Real-time Post-processing System for Itinerary Recommendation. - Linge Jiang; Guiyang Wang; Zhibo Zhu; Binghao Wang; Runsheng Gan; Ziqi Liu; Jun Zhou 011 (CIKM, 2022)

An Adaptive Framework for Confidence-constraint Rule Set Learning Algorithm in Large Dataset. - Meng Li; Lu Yu 006; Ya-Lin Zhang 001; Xiaoguang Huang; Qitao Shi; Qing Cui; Xinxing Yang; Longfei Li; Wei Zhu; Yanming Fang; Jun Zhou 011 (CIKM, 2022)

FwSeqBlock: A Field-wise Approach for Modeling Behavior Representation in Sequential Recommendation. - Hao Qian 003; Qintong Wu; Minghao Li; Zhengwei Wu; Zhiqiang Zhang 012; Jun Zhou 011; Lihong Gu; Jinjie Gu (CIKM, 2022)

Task Similarity Aware Meta Learning for Cold-Start Recommendation. - Jieyu Yang; Zhaoxin Huan; Yong He 009; Ke Ding; Liang Zhang; Xiaolu Zhang; Jun Zhou 011; Linjian Mo (CIKM, 2022)

MetaRule: A Meta-path Guided Ensemble Rule Set Learning for Explainable Fraud Detection. - Lu Yu 006; Meng Li; Xiaoguang Huang; Wei Zhu; Yanming Fang; Jun Zhou 011; Longfei Li (CIKM, 2022)

A Practical Distributed ADMM Solver for Billion-Scale Generalized Assignment Problems. - Jun Zhou 011; Feng Qi 005; Zhigang Hua; Daohong Jian; Ziqi Liu; Hua Wu (CIKM, 2022)

A Self-adaptive Indicator Selection Approach for Solving Credit Risk Assessment. - Yongfeng Gu; Yue Ning 005; Hao Ding; Kecai Gu; Daohong Jian; Zhou Xu; Hua Wu; Jun Zhou 011 (COMPSAC, 2022)

BadDet: Backdoor Attacks on Object Detection. - Shih-Han Chan; Yinpeng Dong; Jun Zhu 001; Xiaolu Zhang; Jun Zhou 011 (ECCV Workshops (1), 2022)

NL-SOMA-CLP for real parameter single objective bound constrained optimization. - Hao Ding; Yongfeng Gu; Hua Wu; Jun Zhou 011 (GECCO Companion, 2022)

Heuristic strategies for solving the combinatorial optimization problem in real-world credit risk assessment. - Yongfeng Gu; Hao Ding; Kecai Gu; Runsheng Gan; Xiaoguang Huang; Yanming Fang; Zhigang Hua; Hua Wu; Jifeng Xuan; Jun Zhou 011 (GECCO Companion, 2022)

Opposite learning and multi-migrating strategy-based self-organizing migrating algorithm with the convergence monitoring mechanism. - Yongfeng Gu; Hao Ding; Hua Wu; Jun Zhou 011 (GECCO Companion, 2022)

Zeroth-order covariance matrix adaptation evolution strategy for single objective bound constrained numerical optimization competition. - Yue Ning 005; Daohong Jian; Hua Wu; Jun Zhou 011 (GECCO Companion, 2022)

Attribute-Conditioned Face Swapping Network for Low-Resolution Images. - Ang Li; Jian Hu 002; Chilin Fu; Xiaolu Zhang; Jun Zhou 011 (ICASSP, 2022)

Intent Mining: A Social and Semantic Enhanced Topic Model for Operation-Friendly Digital Marketing. - Weifan Wang 005; Xiaocheng Cheng; Ziqi Liu; Yu Lin; Yue Shen; Binbin Hu; Zhiqiang Zhang 012; Xiaodong Zeng; Jun Zhou 011; Jinjie Gu; Minnan Luo (ICDE, 2022)

Gaia: Graph Neural Network with Temporal Shift aware Attention for Gross Merchandise Value Forecast in E-commerce. - Borui Ye; Shuo Yang; Binbin Hu; Zhiqiang Zhang 012; Youqiang He; Kai Huang; Jun Zhou 011; Yanming Fang (ICDE, 2022)

Vertically Federated Graph Neural Network for Privacy-Preserving Node Classification. - Chaochao Chen 001; Jun Zhou 011; Longfei Zheng; Huiwen Wu; Lingjuan Lyu; Jia Wu 001; Bingzhe Wu; Ziqi Liu; Li Wang 056; Xiaolin Zheng (IJCAI, 2022)

MERIT: Learning Multi-level Representations on Temporal Graphs. - Binbin Hu; Zhengwei Wu; Jun Zhou 011; Ziqi Liu; Zhigang Huangfu; Zhiqiang Zhang 012; Chaochao Chen 001 (IJCAI, 2022)

Learning Mixture of Neural Temporal Point Processes for Multi-dimensional Event Sequence Clustering. - Yunhao Zhang; Junchi Yan; Xiaolu Zhang; Jun Zhou 011; Xiaokang Yang 001 (IJCAI, 2022)

A Graph Learning Based Framework for Billion-Scale Offline User Identification. - Daixin Wang; Zujian Weng; Zhengwei Wu; Zhiqiang Zhang 012; Peng Cui 001; Hongwei Zhao; Jun Zhou 011 (KDD, 2022)

Debiased Causal Tree: Heterogeneous Treatment Effects Estimation with Unmeasured Confounding. - Caizhi Tang; Huiyuan Wang; Xinyu Li; Qing Cui; Ya-Lin Zhang 001; Feng Zhu 011; Longfei Li; Jun Zhou 011; Linbo Jiang (NeurIPS, 2022)

AutoTransformer: Automatic Transformer Architecture Design for Time Series Classification. - Yankun Ren; Longfei Li; Xinxing Yang; Jun Zhou 011 (PAKDD (1), 2022)

TAMOR: Tier-Aware Multi-objective Recommendation for Ant Fortune Financial Marketing. - Xu Min; Xiaolu Zhang; Jun Zhou 011; Changxun Fan; Junlin Yu (ECML/PKDD (6), 2022)

Mixture of Graph Enhanced Expert Networks for Multi-task Recommendation. - Binbin Hu; Bin Shen; Ruize Wu; Zhiqiang Zhang 012; Yuetian Cao; Yong He 009; Liang Zhang; Linjian Mo; Jun Zhou 011 (PRICAI (3), 2022)

Neural Graph Matching for Pre-training Graph Neural Networks. - Yupeng Hou; Binbin Hu; Wayne Xin Zhao; Zhiqiang Zhang 012; Jun Zhou 011; Ji-Rong Wen (SDM, 2022)

An Industrial Framework for Cold-Start Recommendation in Zero-Shot Scenarios. - Zhaoxin Huan; Gongduo Zhang; Xiaolu Zhang; Jun Zhou 011; Qintong Wu; Lihong Gu; Jinjie Gu; Yong He 009; Yue Zhu; Linjian Mo (SIGIR, 2022)

MetaCare++: Meta-Learning with Hierarchical Subtyping for Cold-Start Diagnosis Prediction in Healthcare Data. - Yanchao Tan; Carl Yang 001; Xiangyu Wei; Chaochao Chen 001; Weiming Liu 005; Longfei Li; Jun Zhou 011; Xiaolin Zheng (SIGIR, 2022)

Transfer Attacks Revisited: A Large-Scale Empirical Study in Real Computer Vision Settings. - Yuhao Mao; Chong Fu 002; Saizhuo Wang; Shouling Ji; Xuhong Zhang 002; Zhenguang Liu; Jun Zhou 011; Alex X. Liu; Raheem Beyah; Ting Wang 006 (SP, 2022)

Label Inference Attacks Against Vertical Federated Learning. - Chong Fu 002; Xuhong Zhang 002; Shouling Ji; Jinyin Chen; Jingzheng Wu; Shanqing Guo; Jun Zhou 011; Alex X. Liu; Ting Wang 006 (USENIX Security Symposium, 2022)

Scope-aware Re-ranking with Gated Attention in Feed. - Hao Qian 003; Qintong Wu; Kai Zhang 038; Zhiqiang Zhang 012; Lihong Gu; Xiaodong Zeng; Jun Zhou 011; Jinjie Gu (WSDM, 2022)

A Multi-Task Learning Approach for Delayed Feedback Modeling. - Zhigang Huangfu; Gongduo Zhang; Zhengwei Wu; Qintong Wu; Zhiqiang Zhang 012; Lihong Gu; Jun Zhou 011; Jinjie Gu (WWW (Companion Volume), 2022)

Confidence May Cheat: Self-Training on Graph Neural Networks under Distribution Shift. - Hongrui Liu; Binbin Hu; Xiao Wang 017; Chuan Shi 001; Zhiqiang Zhang 012; Jun Zhou 011 (WWW, 2022)

Robust Unsupervised Graph Representation Learning via Mutual Information Maximization. - Jihong Wang 003; Minnan Luo; Jundong Li; Ziqi Liu; Jun Zhou 011; Qinghua Zheng (CoRR, 2022)

An Effective Graph Learning based Approach for Temporal Link Prediction: The First Place of WSDM Cup 2022. - Qian Zhao; Shuo Yang; Binbin Hu; Zhiqiang Zhang 012; Yakun Wang 001; Yusong Chen; Jun Zhou 011; Chuan Shi 001 (CoRR, 2022)

KGNN: Distributed Framework for Graph Neural Knowledge Representation. - Binbin Hu; Zhiyang Hu; Zhiqiang Zhang 012; Jun Zhou 011; Chuan Shi 001 (CoRR, 2022)

AHEAD: A Triple Attention Based Heterogeneous Graph Anomaly Detection Approach. - Shujie Yang; Binchi Zhang; Shangbin Feng; Zhaoxuan Tan; Qinghua Zheng; Jun Zhou 011; Minnan Luo (CoRR, 2022)

A Practical Distributed ADMM Solver for Billion-Scale Generalized Assignment Problems. - Jun Zhou 011; Feng Qi 005; Zhigang Hua; Daohong Jian; Ziqi Liu; Hua Wu; Xingwen Zhang; Shuang Yang (CoRR, 2022)

Interpreting Model Predictions with Constrained Perturbation and Counterfactual Instances. - Jun-Peng Fang; Jun Zhou 011; Qing Cui; Caizhi Tang; Longfei Li (Int. J. Pattern Recognit. Artif. Intell., 2022)

FinBrain 2.0: when finance meets trustworthy AI. - Jun Zhou 011; Chaochao Chen 001; Longfei Li; Zhiqiang Zhang 012; Xiaolin Zheng (Frontiers Inf. Technol. Electron. Eng., 2022)

Toward Scalable and Privacy-preserving Deep Neural Network via Algorithmic-Cryptographic Co-design. - Jun Zhou 011; Longfei Zheng; Chaochao Chen 001; Yan Wang 002; Xiaolin Zheng; Bingzhe Wu; Cen Chen 001; Li Wang 056; Jianwei Yin (ACM Trans. Intell. Syst. Technol., 2022)

FINRule: Feature Interactive Neural Rule Learning. - Lu Yu 006; Meng Li; Ya-Lin Zhang 001; Longfei Li; Jun Zhou 011 (CIKM, 2023)

Robust User Behavioral Sequence Representation via Multi-scale Stochastic Distribution Prediction. - Chilin Fu; Weichang Wu; Xiaolu Zhang; Jun Hu; Jing Wang; Jun Zhou 011 (CIKM, 2023)

Continual Learning in Predictive Autoscaling. - Hongyan Hao; Zhixuan Chu; Shiyi Zhu; Gangwei Jiang; Yan Wang 002; Caigao Jiang; James Y. Zhang; Wei Jiang; Siqiao Xue; Jun Zhou 011 (CIKM, 2023)

SeqGen: A Sequence Generator via User Side Information for Behavior Sparsity in Recommendation. - Xu Min; Xiaolu Zhang; Bin Shen; Shuhan Wang; Yong He 009; Changsheng Li; Jun Zhou 011 (CIKM, 2023)

Treatment Effect Estimation across Domains. - Yi-Xuan Sun; Ya-Lin Zhang 001; Wei Wang 028; Longfei Li; Jun Zhou 011 (CIKM, 2023)

Periodicity May Be Emanative: Hierarchical Contrastive Learning for Sequential Recommendation. - Changxin Tian; Binbin Hu; Wayne Xin Zhao; Zhiqiang Zhang 012; Jun Zhou 011 (CIKM, 2023)

Disentangled Interest importance aware Knowledge Graph Neural Network for Fund Recommendation. - Ke Tu; Wei Qu; Zhengwei Wu; Zhiqiang Zhang 012; Zhongyi Liu; Yiming Zhao; Le Wu; Jun Zhou 011; Guannan Zhang (CIKM, 2023)

G-Meta: Distributed Meta Learning in GPU Clusters for Large-Scale Recommender Systems. - Youshao Xiao; Shangchun Zhao; Zhenglei Zhou; Zhaoxin Huan; Lin Ju; Xiaolu Zhang; Lin Wang 098; Jun Zhou 011 (CIKM, 2023)

Unsupervised Fraud Transaction Detection on Dynamic Attributed Networks. - Yangyang Hou; Daixin Wang; Binbin Hu; Ruoyu Zhuang; Zhiqiang Zhang 012; Jun Zhou 011; Feng Zhao; Yulin Kang; Zhanwen Qiao (DASFAA (4), 2023)

Global-Aware Model-Free Self-distillation for Recommendation System. - Ang Li; Jian Hu 002; Wei Lu 011; Ke Ding; Xiaolu Zhang; Jun Zhou 011; Yong He 009; Liang Zhang; Lihong Gu (DASFAA (4), 2023)

A Scalable Social Recommendation Framework with Decoupled Graph Neural Network. - Ke Tu; Zhengwei Wu; Binbin Hu; Zhiqiang Zhang 012; Peng Cui 001; Xiaolong Li 005; Jun Zhou 011 (DASFAA (4), 2023)

AntTune: An Efficient Distributed Hyperparameter Optimization System for Large-Scale Data. - Jun Zhou 011; Qitao Shi; Yi Ding 006; Lin Wang 098; Longfei Li; Feng Zhu 011 (DASFAA (4), 2023)

Towards Anytime Fine-tuning: Continually Pre-trained Language Models with Hypernetwork Prompts. - Gangwei Jiang; Caigao Jiang; Siqiao Xue; James Zhang; Jun Zhou 011; Defu Lian; Ying Wei 001 (EMNLP (Findings), 2023)

GARCIA: Powering Representations of Long-tail Query with Multi-granularity Contrastive Learning. - Weifan Wang 005; Binbin Hu; Zhicheng Peng; Mingjie Zhong; Zhiqiang Zhang 012; Zhongyi Liu; Guannan Zhang; Jun Zhou 011 (ICDE, 2023)

A Rule-based Decision System for Financial Applications. - Meng Li; Jun Zhou 011; Lu Yu 006; Xiaoguang Huang; Yongfeng Gu; Yi Ding 006; Hao Ding; Longfei Li (ICDE, 2023)

InferTurbo: A Scalable System for Boosting Full-graph Inference of Graph Neural Network over Huge Graphs. - Dalong Zhang; Xianzheng Song; Zhiyang Hu; Yang Li; Miao Tao; Binbin Hu; Lin Wang 098; Zhiqiang Zhang 012; Jun Zhou 011 (ICDE, 2023)

ALT: An Automatic System for Long Tail Scenario Modeling. - Ya-Lin Zhang 001; Jun Zhou 011; Yankun Ren; Yue Zhang; Xinxing Yang; Meng Li; Qitao Shi; Longfei Li (ICDE, 2023)

DCMT: A Direct Entire-Space Causal Multi-Task Framework for Post-Click Conversion Estimation. - Feng Zhu 011; Mingjie Zhong; Xinxing Yang; Longfei Li; Lu Yu 006; Tiehua Zhang; Jun Zhou 011; Chaochao Chen 001; Fei Wu 001; Guanfeng Liu 001; Yan Wang 002 (ICDE, 2023)

Enhancing Asynchronous Time Series Forecasting with Contrastive Relational Inference. - Yan Wang 002; Zhixuan Chu; Tao Zhou; Caigao Jiang; Hongyan Hao; Minjie Zhu; Xindong Cai; Qing Cui; Longfei Li; James Y. Zhang; Siqiao Xue; Jun Zhou 011 (ICDM (Workshops), 2023)

Towards Open Temporal Graph Neural Networks. - Kaituo Feng; Changsheng Li; Xiaolu Zhang; Jun Zhou 011 (ICLR, 2023)

Difference-in-Differences Meets Tree-based Methods: Heterogeneous Treatment Effects Estimation with Unmeasured Confounding. - Caizhi Tang; Huiyuan Wang; Xinyu Li; Qing Cui; Longfei Li; Jun Zhou 011 (ICML, 2023)

Keep Skills in Mind: Understanding and Implementing Skills in Commonsense Question Answering. - Meikai Bao; Qi Liu 003; Kai Zhang 038; Ye Liu 011; Linan Yue; Longfei Li; Jun Zhou 011 (IJCAI, 2023)

PDAS: A Practical Distributed ADMM System for Large-Scale Linear Programming Problems at Alipay. - Jun Zhou 011; Yang Bao 008; Daohong Jian; Hua Wu (KDD, 2023)

SAMD: An Industrial Framework for Heterogeneous Multi-Scenario Recommendation. - Zhaoxin Huan; Ang Li; Xiaolu Zhang; Xu Min; Jieyu Yang; Yong He 009; Jun Zhou 011 (KDD, 2023)

Financial Default Prediction via Motif-preserving Graph Neural Network with Curriculum Learning. - Daixin Wang; Zhiqiang Zhang 012; Yeyu Zhao; Kai Huang; Yulin Kang; Jun Zhou 011 (KDD, 2023)

Commonsense Knowledge Graph towards Super APP and Its Applications in Alipay. - Xiaoling Zang; Binbin Hu; Jun Chu; Zhiqiang Zhang 012; Guannan Zhang; Jun Zhou 011; Wenliang Zhong (KDD, 2023)

FAST: a Fused and Accurate Shrinkage Tree for Heterogeneous Treatment Effects Estimation. - Jia Gu; Caizhi Tang; Han Yan; Qing Cui; Longfei Li; Jun Zhou 011 (NeurIPS, 2023)

Language Models Can Improve Event Prediction by Few-Shot Abductive Reasoning. - Xiaoming Shi 001; Siqiao Xue; Kangrui Wang; Fan Zhou 012; James Y. Zhang; Jun Zhou 011; Chenhao Tan; Hongyuan Mei (NeurIPS, 2023)

Unleashing the Power of Graph Data Augmentation on Covariate Distribution Shift. - Yongduo Sui; Qitian Wu; Jiancan Wu; Qing Cui; Longfei Li; Jun Zhou 011; Xiang Wang 010; Xiangnan He 001 (NeurIPS, 2023)

Prompt-augmented Temporal Point Process for Streaming Event Sequence. - Siqiao Xue; Yan Wang 002; Zhixuan Chu; Xiaoming Shi 001; Caigao Jiang; Hongyan Hao; Gangwei Jiang; Xiaoyun Feng; James Zhang; Jun Zhou 011 (NeurIPS, 2023)

BCAD: An Interpretable Anomaly Transaction Detection System Based on Behavior Consistency. - Jun Hu; Xu Min; Xiaolu Zhang; Chilin Fu; Weichang Wu; Jun Zhou 011 (ECML/PKDD (6), 2023)

Boosting Adaptive Graph Augmented MLPs via Customized Knowledge Distillation. - Shaowei Wei; Zhengwei Wu; Zhiqiang Zhang 012; Jun Zhou 011 (ECML/PKDD (3), 2023)

Long-Tail Augmented Graph Contrastive Learning for Recommendation. - Qian Zhao; Zhengwei Wu; Zhiqiang Zhang 012; Jun Zhou 011 (ECML/PKDD (4), 2023)

Alleviating Matching Bias in Marketing Recommendations. - Junpeng Fang; Qing Cui; Gongduo Zhang; Caizhi Tang; Lihong Gu; Longfei Li; Jinjie Gu; Jun Zhou 011; Fei Wu 001 (SIGIR, 2023)

Which Matters Most in Making Fund Investment Decisions? A Multi-granularity Graph Disentangled Learning Framework. - Chunjing Gan; Binbin Hu; Bo Huang; Tianyu Zhao; Yingru Lin; Wenliang Zhong; Zhiqiang Zhang 012; Jun Zhou 011; Chuan Shi 001 (SIGIR, 2023)

A Practical Online Allocation Framework at Industry-scale in Constrained Recommendation. - Daohong Jian; Yang Bao 008; Jun Zhou 011; Hua Wu (SIGIR, 2023)

Uncertainty-based Heterogeneous Privileged Knowledge Distillation for Recommendation System. - Ang Li; Jian Hu 002; Ke Ding; Xiaolu Zhang; Jun Zhou 011; Yong He 009; Xu Min (SIGIR, 2023)

TAML: Time-Aware Meta Learning for Cold-Start Problem in News Recommendation. - Jingyuan Li; Yue Zhang; Xuan Lin; Xinxing Yang; Ge Zhou; Longfei Li; Hong Chen; Jun Zhou 011 (SIGIR, 2023)

GreenSeq: Automatic Design of Green Networks for Sequential Recommendation Systems. - Yankun Ren; Xinxing Yang; Xingyu Lu; Longfei Li; Jun Zhou 011; Jinjie Gu; Guannan Zhang (SIGIR, 2023)

Towards Multi-Interest Pre-training with Sparse Capsule Network. - Zuoli Tang; Lin Wang 098; Lixin Zou; Xiaolu Zhang; Jun Zhou 011; Chenliang Li (SIGIR, 2023)

COUPA: An Industrial Recommender System for Online to Offline Service Platforms. - Sicong Xie; Binbin Hu; Fengze Li; Ziqi Liu; Zhiqiang Zhang 012; Wenliang Zhong; Jun Zhou 011 (SIGIR, 2023)

Generative-Contrastive Graph Learning for Recommendation. - Yonghui Yang; Zhengwei Wu; Le Wu; Kun Zhang 015; Richang Hong; Zhiqiang Zhang 012; Jun Zhou 011; Meng Wang 001 (SIGIR, 2023)

MDI: A Debiasing Method Combining Unbiased and Biased Data. - Han Zhao; Qing Cui; Xinyu Li; Rongzhou Bao; Longfei Li; Jun Zhou 011; Zhehao Liu; Jinghua Feng (SIGIR, 2023)

DistriBayes: A Distributed Platform for Learning, Inference and Attribution on Large Scale Bayesian Network. - Yi Ding 006; Jun Zhou 011; Qing Cui; Lin Wang 098; Mengqi Zhang; Yang Dong (WSDM, 2023)

AntTS: A Toolkit for Time Series Forecasting in Industrial Scenarios. - Jianping Wei; Zhibo Zhu; Ziqi Liu; Zhiqiang Zhang 012; Jun Zhou 011 (WSDM, 2023)

A Framework for Detecting Frauds from Extremely Few Labels. - Ya-Lin Zhang 001; Yi-Xuan Sun; Fangfang Fan; Meng Li; Yeyu Zhao; Wei Wang 028; Longfei Li; Jun Zhou 011; Jinghua Feng (WSDM, 2023)

ElasticDL: A Kubernetes-native Deep Learning Framework with Fault-tolerance and Elastic Scheduling. - Jun Zhou 011; Ke Zhang; Feng Zhu 011; Qitao Shi; Wenjing Fang; Lin Wang 098; Yi Wang 141 (WSDM, 2023)

Multi-Source Domain Adaptation via Latent Domain Reconstruction. - Jun Zhou 011; Chilin Fu; Xiaolu Zhang (WWW (Companion Volume), 2023)

Improving Recommendation Fairness via Data Augmentation. - Lei Chen 051; Le Wu; Kun Zhang 015; Richang Hong; Defu Lian; Zhiqiang Zhang 012; Jun Zhou 011; Meng Wang 001 (WWW, 2023)

Online resource allocation in Markov Chains. - Jianhao Jia; Hao Li 107; Kai Liu; Ziqi Liu; Jun Zhou 011; Nikolai Gravin; Zhihao Gavin Tang (WWW, 2023)

A Practical Rule Learning Framework for Risk Management. - Jun Zhou 011; Meng Li; Lu Yu 006; Longfei Li; Fei Wu 001 (WWW (Companion Volume), 2023)

DGBCT: A Scalable Distributed Gradient Boosting Causal Tree at Alipay. - Jun Zhou 011; Caizhi Tang; Qing Cui; Yi Ding 006; Longfei Li; Fei Wu 001 (WWW (Companion Volume), 2023)

Graph Neural Network with Two Uplift Estimators for Label-Scarcity Individual Uplift Modeling. - Dingyuan Zhu; Daixin Wang; Zhiqiang Zhang 012; Kun Kuang; Yan Zhang; Yulin Kang; Jun Zhou 011 (WWW, 2023)

EasyTPP: Towards Open Benchmarking the Temporal Point Processes. - Siqiao Xue; Xiaoming Shi 001; Zhixuan Chu; Yan Wang 002; Fan Zhou 012; Hongyan Hao; Caigao Jiang; Chen Pan; Yi Xu; James Y. Zhang; Qingsong Wen; Jun Zhou 011; et al. (CoRR, 2023)

Federated Large Language Model: A Position Paper. - Chaochao Chen 001; Xiaohua Feng; Jun Zhou 011; Jianwei Yin; Xiaolin Zheng (CoRR, 2023)

Continual Learning in Predictive Autoscaling. - Hongyan Hao; Zhixuan Chu; Shiyi Zhu; Gangwei Jiang; Yan Wang 002; Caigao Jiang; James Zhang; Wei Jiang; Siqiao Xue; Jun Zhou 011 (CoRR, 2023)

WeaverBird: Empowering Financial Decision-Making with Large Language Model, Knowledge Base, and Search Engine. - Siqiao Xue; Fan Zhou 012; Yi Xu; Hongyu Zhao 006; Shuo Xie; Qingyang Dai; Caigao Jiang; James Y. Zhang; Jun Zhou 011; Dacheng Xiu; Hongyuan Mei (CoRR, 2023)

Enhancing Recommender Systems with Large Language Model Reasoning Graphs. - Yan Wang 002; Zhixuan Chu; Xin Ouyang; Simeng Wang; Hongyan Hao; Yue Shen; Jinjie Gu; Siqiao Xue; James Y. Zhang; Qing Cui; Longfei Li; Jun Zhou 011; et al. (CoRR, 2023)

AntM2C: A Large Scale Dataset For Multi-Scenario Multi-Modal CTR Prediction. - Zhaoxin Huan; Ke Ding; Ang Li; Xiaolu Zhang; Xu Min; Yong He 009; Liang Zhang; Jun Zhou 011; Linjian Mo; Jinjie Gu; Zhongyi Liu; Wenliang Zhong; et al. (CoRR, 2023)

Prompt-augmented Temporal Point Process for Streaming Event Sequence. - Siqiao Xue; Yan Wang 002; Zhixuan Chu; Xiaoming Shi 001; Caigao Jiang; Hongyan Hao; Gangwei Jiang; Xiaoyun Feng; James Y. Zhang; Jun Zhou 011 (CoRR, 2023)

Rethinking Memory and Communication Cost for Efficient Large Language Model Training. - Chan Wu; Hanxiao Zhang; Lin Ju; Jinjing Huang; Youshao Xiao; Zhaoxin Huan; Siyuan Li; Fanzhuang Meng; Lei Liang 001; Xiaolu Zhang; Jun Zhou 011 (CoRR, 2023)

Towards Anytime Fine-tuning: Continually Pre-trained Language Models with Hypernetwork Prompt. - Gangwei Jiang; Caigao Jiang; Siqiao Xue; James Y. Zhang; Jun Zhou 011; Defu Lian; Ying Wei 001 (CoRR, 2023)

One Model for All: Large Language Models are Domain-Agnostic Recommendation Systems. - Zuoli Tang; Zhaoxin Huan; Zihao Li 005; Xiaolu Zhang; Jun Hu; Chilin Fu; Jun Zhou 011; Chenliang Li (CoRR, 2023)

Data-Centric Financial Large Language Models. - Zhixuan Chu; Huaiyu Guo; Xinyuan Zhou; Yijia Wang; Fei Yu; Hong Chen; Wanqing Xu; Xin Lu; Qing Cui; Longfei Li; Jun Zhou 011; Sheng Li 001 (CoRR, 2023)

PEACE: Prototype lEarning Augmented transferable framework for Cross-domain rEcommendation. - Chunjing Gan; Bo Huang; Binbin Hu; Jian Ma; Ziqi Liu; Zhiqiang Zhang 012; Jun Zhou 011; Guannan Zhang; Wenliang Zhong (CoRR, 2023)

Making Large Language Models Better Knowledge Miners for Online Marketing with Progressive Prompting Augmentation. - Chunjing Gan; Dan Yang 004; Binbin Hu; Ziqi Liu; Yue Shen; Zhiqiang Zhang 012; Jinjie Gu; Jun Zhou 011; Guannan Zhang (CoRR, 2023)

An Adaptive Placement and Parallelism Framework for Accelerating RLHF Training. - Youshao Xiao; Weichang Wu; Zhenglei Zhou; Fagui Mao; Shangchun Zhao; Lin Ju; Lei Liang 001; Xiaolu Zhang; Jun Zhou 011 (CoRR, 2023)

Exploring the combination of self and mutual teaching for tabular-data-related semi-supervised regression. - Ya-Lin Zhang 001; Jun Zhou 011; Qitao Shi; Longfei Li (Expert Syst. Appl., 2023)

SQLFlow: An Extensible Toolkit Integrating DB and AI. - Jun Zhou 011; Ke Zhang; Lin Wang 098; Hua Wu; Yi Wang 141; Chaochao Chen 001 (J. Mach. Learn. Res., 2023)

Your Labels are Selling You Out: Relation Leaks in Vertical Federated Learning. - Pengyu Qiu; Xuhong Zhang 002; Shouling Ji; Tianyu Du; Yuwen Pu; Jun Zhou 011; Ting Wang 006 (IEEE Trans. Dependable Secur. Comput., 2023)

Fraud-Agents Detection in Online Microfinance: A Large-Scale Empirical Study. - Yiming Wu; Zhiyuan Xie; Shouling Ji; Zhenguang Liu; Xuhong Zhang 002; Changting Lin; Shuiguang Deng; Jun Zhou 011; Ting Wang 006; Raheem Beyah (IEEE Trans. Dependable Secur. Comput., 2023)

EATN: An Efficient Adaptive Transfer Network for Aspect-Level Sentiment Analysis. - Kai Zhang 038; Qi Liu 003; Hao Qian 003; Biao Xiang; Qing Cui; Jun Zhou 011; Enhong Chen (IEEE Trans. Knowl. Data Eng., 2023)

A Unified Framework for Cross-Domain and Cross-System Recommendations. - Feng Zhu 011; Yan Wang 002; Jun Zhou 011; Chaochao Chen 001; Longfei Li; Guanfeng Liu 001 (IEEE Trans. Knowl. Data Eng., 2023)

GraphTune: An Efficient Dependency-Aware Substrate to Alleviate Irregularity in Concurrent Graph Processing. - Jin Zhao 003; Yu Zhang 027; Ligang He; Qikun Li; Xiang Zhang; Xinyu Jiang; Hui Yu; Xiaofei Liao; Hai Jin 001; Lin Gu 002; Haikun Liu; Bingsheng He; et al. (ACM Trans. Archit. Code Optim., 2023)

Deep Tabular Data Modeling With Dual-Route Structure-Adaptive Graph Networks. - Qinghua Zheng; Zhen Peng 005; Zhuohang Dang; Linchao Zhu; Ziqi Liu; Zhiqiang Zhang 012; Jun Zhou 011 (IEEE Trans. Knowl. Data Eng., 2023)

GINT: A Generative Interpretability method via perturbation in the latent space. - Caizhi Tang; Qing Cui; Longfei Li; Jun Zhou 011 (Expert Syst. Appl., 2023)

Bi-objective evolutionary Bayesian network structure learning via skeleton constraint. - Ting Wu; Hong Qian; Ziqi Liu; Jun Zhou 011; Aimin Zhou (Frontiers Comput. Sci., 2023)

Backdoor Adjustment via Group Adaptation for Debiased Coupon Recommendations. - Junpeng Fang; Gongduo Zhang; Qing Cui; Caizhi Tang; Lihong Gu; Longfei Li; Jinjie Gu; Jun Zhou 011 (AAAI, 2024)

π-Light: Programmatic Interpretable Reinforcement Learning for Resource-Limited Traffic Signal Control. - Yin Gu; Kai Zhang 038; Qi Liu 003; Weibo Gao; Longfei Li; Jun Zhou 011 (AAAI, 2024)

MDGNN: Multi-Relational Dynamic Graph Neural Network for Comprehensive and Dynamic Stock Investment Prediction. - Hao Qian 003; Hongting Zhou; Qian Zhao; Hao Chen; Hongxiang Yao; Jingwei Wang; Ziqi Liu; Fei Yu; Zhiqiang Zhang 012; Jun Zhou 011 (AAAI, 2024)

LLMRG: Improving Recommendations through Large Language Model Reasoning Graphs. - Yan Wang 002; Zhixuan Chu; Xin Ouyang; Simeng Wang; Hongyan Hao; Yue Shen; Jinjie Gu; Siqiao Xue; James Zhang; Qing Cui; Longfei Li; Jun Zhou 011; et al. (AAAI, 2024)

GMP-AR: Granularity Message Passing and Adaptive Reconciliation for Temporal Hierarchy Forecasting. - Fan Zhou 012; Chen Pan; Lintao Ma; Yu Liu 071; Siqiao Xue; James Y. Zhang; Jun Zhou 011; Hongyuan Mei; Weitao Lin; Zi Zhuang; Wenxin Ning; Yunhua Hu (AAAI, 2024)

MIBR: Bridging Domains through Diverse Interests for Cross-Domain Sequential Recommendation. - Chengzhe Zhang; Xu Min; Changsheng Li; Xiaolu Zhang; Weichang Wu; Jun Zhou 011; Ye Yuan 001; Guoren Wang (IEEE Big Data, 2024)

Multiscale Representation Enhanced Temporal Flow Fusion Model for Long-Term Workload Forecasting. - Shiyu Wang 001; Zhixuan Chu; Yinbo Sun; Yu Liu 071; Yuliang Guo; Yang Chen; Huiyang Jian; Lintao Ma; Xingyu Lu; Jun Zhou 011 (CIKM, 2024)

Factor Model-Based Large Covariance Estimation from Streaming Data Using a Knowledge-Based Sketch Matrix. - Xiao Tan 005; Zhaoyang Wang; Hao Qian 003; Jun Zhou 011; Peibo Duan; Dian Shen; Meng Wang 009; Beilun Wang (CIKM, 2024)

TEXT CAN BE FAIR: Mitigating Popularity Bias with PLMs by Learning Relative Preference. - Zuoli Tang; Zhaoxin Huan; Zihao Li 005; Shirui Hu; Xiaolu Zhang; Jun Zhou 011; Lixin Zou; Chenliang Li (CIKM, 2024)

Multi-view Temporal Knowledge Graph Reasoning. - Fuwei Zhang; Zhao Zhang 011; Fuzhen Zhuang; Zhiqiang Zhang 012; Jun Zhou 011; Deqing Wang (CIKM, 2024)

Efficient Model Stealing Defense with Noise Transition Matrix. - Dong-Dong Wu; Chilin Fu; Weichang Wu; Wenwen Xia; Xiaolu Zhang; Jun Zhou 011; Min-Ling Zhang (CVPR, 2024)

Empowering Sequential Recommendation from Collaborative Signals and Semantic Relatedness. - Mingyue Cheng; Hao Zhang 088; Qi Liu 003; Fajie Yuan; Zhi Li 057; Zhenya Huang; Enhong Chen; Jun Zhou 011; Longfei Li (DASFAA (3), 2024)

QoMRC: Query-oriented Machine Reading Comprehension Framework for Aspect Sentiment Triplet Extraction. - Kehang Wang; Ye Liu 011; Kai Zhang 038; Qi Liu 003; Yankun Ren; Xinxing Yang; Longfei Li; Jun Zhou 011 (DASFAA (5), 2024)

Granola: Graph Neural Network Tackling Tabular Data for Online Loan Default Prediction. - Borui Ye; Shuo Yang; Meiqi Zhu; Binbin Hu; Daixin Wang; Zhiqiang Zhang 012; Youqiang He; Zhiyang Hu; Huimei He; Jun Zhou 011 (DASFAA (7), 2024)

Distributed Meta-learning for Large-Scale Multi-institution Credit Default Risk Prediction. - Yue Zhang; Xinxing Yang; Feng Zhu 011; Longfei Li; Linbo Jiang; Jun Zhou 011 (DASFAA (7), 2024)

Optimizing Language Models with Fair and Stable Reward Composition in Reinforcement Learning. - Jiahui Li 003; Hanlin Zhang; Fengda Zhang; Tai-Wei Chang; Kun Kuang; Long Chen 016; Jun Zhou 011 (EMNLP, 2024)

Knowledge-augmented Financial Market Analysis and Report Generation. - Yuemin Chen; Feifan Wu; Jingwei Wang; Hao Qian 003; Ziqi Liu; Zhiqiang Zhang 012; Jun Zhou 011; Meng Wang 009 (EMNLP (Industry Track), 2024)

Learning to Plan for Retrieval-Augmented Large Language Models from Knowledge Graphs. - Junjie Wang; Mingyang Chen; Binbin Hu; Dan Yang 004; Ziqi Liu; Yue Shen; Peng Wei; Zhiqiang Zhang 012; Jinjie Gu; Jun Zhou 011; Jeff Z. Pan; Wen Zhang 015; et al. (EMNLP (Findings), 2024)

OneGen: Efficient One-Pass Unified Generation and Retrieval for LLMs. - Jintian Zhang; Cheng Peng; Mengshu Sun; Xiang Chen 016; Lei Liang 002; Zhiqiang Zhang 012; Jun Zhou 011; Huajun Chen; Ningyu Zhang 001 (EMNLP (Findings), 2024)

Enhancing Event Sequence Modeling with Contrastive Relational Inference. - Yan Wang 002; Zhixuan Chu; Tao Zhou; Caigao Jiang; Hongyan Hao; Minjie Zhu; Xindong Cai; Qing Cui; Longfei Li; James Y. Zhang; Siqiao Xue; Jun Zhou 011 (ICASSP, 2024)

AntDT: A Self-Adaptive Distributed Training Framework for Leader and Straggler Nodes. - Youshao Xiao; Lin Ju; Zhenglei Zhou; Siyuan Li; Zhaoxin Huan; Dalong Zhang; Rujie Jiang; Lin Wang 098; Xiaolu Zhang; Lei Liang 002; Jun Zhou 011 (ICDE, 2024)

TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting. - Shiyu Wang 001; Haixu Wu; Xiaoming Shi 001; Tengge Hu; Huakun Luo; Lintao Ma; James Y. Zhang; Jun Zhou 011 (ICLR, 2024)

EasyTPP: Towards Open Benchmarking Temporal Point Processes. - Siqiao Xue; Xiaoming Shi 001; Zhixuan Chu; Yan Wang 002; Hongyan Hao; Fan Zhou 012; Caigao Jiang; Chen Pan; James Y. Zhang; Qingsong Wen; Jun Zhou 011; Hongyuan Mei (ICLR, 2024)

Keypoint-based Progressive Chain-of-Thought Distillation for LLMs. - Kaituo Feng; Changsheng Li; Xiaolu Zhang; Jun Zhou 011; Ye Yuan 001; Guoren Wang (ICML, 2024)

Self-cognitive Denoising in the Presence of Multiple Noisy Label Sources. - Yi-Xuan Sun; Ya-Lin Zhang 001; Bin Han; Longfei Li; Jun Zhou 011 (ICML, 2024)

Unifying Bayesian Flow Networks and Diffusion Models through Stochastic Differential Equations. - Kaiwen Xue; Yuhao Zhou; Shen Nie; Xu Min; Xiaolu Zhang; Jun Zhou 011; Chongxuan Li (ICML, 2024)

A High-Performance ORB Accelerator with Algorithm and Hardware Co-design for Visual Localization. - Xiuyuan Qi; Ye Liu 011; Shuang Hao 005; Zherong Liu; Kun Huang; Minghui Yang; Liang Zhou; Jun Zhou 011 (ISCAS, 2024)

LASCA: A Large-Scale Stable Customer Segmentation Approach to Credit Risk Assessment. - Yongfeng Gu; Yupeng Wu; Huakang Lu; Xingyu Lu; Hong Qian; Jun Zhou 011; Aimin Zhou (KDD, 2024)

Cost-Efficient Fraud Risk Optimization with Submodularity in Insurance Claim. - Yupeng Wu; Zhibo Zhu; Chaoyi Ma; Hong Qian; Xingyu Lu; Yangwenhui Zhang; Xiaobo Qin; Binjie Fei; Jun Zhou 011; Aimin Zhou (KDD, 2024)

An Active Masked Attention Framework for Many-to-Many Cross-Domain Recommendations. - Feng Zhu 011; Xinxing Yang; Longfei Li; Jun Zhou 011 (ACM Multimedia, 2024)

Collaborative Refining for Learning from Inaccurate Labels. - Bin Han; Yi-Xuan Sun; Ya-Lin Zhang 001; Libang Zhang; Haoran Hu; Longfei Li; Jun Zhou 011; Guo Ye; Huimei He (NeurIPS, 2024)

Rethinking Memory and Communication Costs for Efficient Data Parallel Training of Large Language Models. - Hanxiao Zhang; Lin Ju; Chan Wu; Jinjing Huang; Youshao Xiao; Zhenglei Zhou; Zhiming Fan; Zhaoxin Huan; Siyuan Li; Fanzhuang Meng; Lei Liang 002; Xiaolu Zhang; et al. (NeurIPS, 2024)

Modeling Treatment Effect with Cross-Domain Data. - Bin Han; Ya-Lin Zhang 001; Lu Yu 006; Biying Chen; Longfei Li; Jun Zhou 011 (PAKDD (1), 2024)

Adaptively Denoising Graph Neural Networks for Knowledge Distillation. - Yuxin Guo; Cheng Yang 002; Chuan Shi 001; Ke Tu; Zhengwei Wu; Zhiqiang Zhang 012; Jun Zhou 011 (ECML/PKDD (8), 2024)

ReLand: Integrating Large Language Models' Insights into Industrial Recommenders via a Controllable Reasoning Pool. - Changxin Tian; Binbin Hu; Chunjing Gan; Haoyu Chen; Zhuo Zhang; Li Yu; Ziqi Liu; Zhiqiang Zhang 012; Jun Zhou 011; Jiawei Chen 007 (RecSys, 2024)

Breaking the Length Barrier: LLM-Enhanced CTR Prediction in Long Textual User Behaviors. - Binzong Geng; Zhaoxin Huan; Xiaolu Zhang; Yong He 009; Liang Zhang; Fajie Yuan; Jun Zhou 011; Linjian Mo (SIGIR, 2024)

Exploring Multi-Scenario Multi-Modal CTR Prediction with a Large Scale Dataset. - Zhaoxin Huan; Ke Ding; Ang Li; Xiaolu Zhang; Xu Min; Yong He 009; Liang Zhang; Jun Zhou 011; Linjian Mo; Jinjie Gu; Zhongyi Liu; Wenliang Zhong; et al. (SIGIR, 2024)

GATS: Generative Audience Targeting System for Online Advertising. - Cong Jiang; Zhongde Chen; Bo Zhang 010; Yankun Ren; Xin Dong 012; Lei Cheng 005; Xinxing Yang; Longfei Li; Jun Zhou 011; Linjian Mo (SIGIR, 2024)

Enhancing Sequential Recommenders with Augmented Knowledge from Aligned Large Language Models. - Yankun Ren; Zhongde Chen; Xinxing Yang; Longfei Li; Cong Jiang; Lei Cheng 005; Bo Zhang 010; Linjian Mo; Jun Zhou 011 (SIGIR, 2024)

OneEdit: A Neural-Symbolic Collaboratively Knowledge Editing System. - Ningyu Zhang 001; Zekun Xi; Yujie Luo; Peng Wang 104; Bozhong Tian; Yunzhi Yao; Jintian Zhang; Shumin Deng; Mengshu Sun; Lei Liang 002; Zhiqiang Zhang 012; Xiaowei Zhu; et al. (VLDB Workshops, 2024)

Domain Level Interpretability: Interpreting Black-box Model with Domain-specific Embedding. - Ya-Lin Zhang 001; Caizhi Tang; Lu Yu 006; Jun Zhou 011; Longfei Li; Qing Cui; Fangfang Fan; Linbo Jiang; Xiaosong Zhao (WSDM, 2024)

PEACE: Prototype lEarning Augmented transferable framework for Cross-domain rEcommendation. - Chunjing Gan; Bo Huang; Binbin Hu; Jian Ma; Zhiqiang Zhang 012; Jun Zhou 011; Guannan Zhang; Wenliang Zhong (WSDM, 2024)

Not All Negatives Are Worth Attending to: Meta-Bootstrapping Negative Sampling Framework for Link Prediction. - Yakun Wang 001; Binbin Hu; Shuo Yang; Meiqi Zhu; Zhiqiang Zhang 012; Qiyang Zhang; Jun Zhou 011; Guo Ye; Huimei He (WSDM, 2024)

Counterfactual Data Augmentation for Debiased Coupon Recommendations Based on Potential Knowledge. - Junpeng Fang; Gongduo Zhang; Qing Cui; Lihong Gu; Longfei Li; Jinjie Gu; Jun Zhou 011 (WWW (Companion Volume), 2024)

Enhancing Sequential Recommendation via LLM-based Semantic Embedding Learning. - Jun Hu; Wenwen Xia; Xiaolu Zhang; Chilin Fu; Weichang Wu; Zhaoxin Huan; Ang Li; Zuoli Tang; Jun Zhou 011 (WWW (Companion Volume), 2024)

Invariant Graph Learning for Causal Effect Estimation. - Yongduo Sui; Caizhi Tang; Zhixuan Chu; Junfeng Fang; Yuan Gao 020; Qing Cui; Longfei Li; Jun Zhou 011; Xiang Wang 010 (WWW, 2024)

Aligned Side Information Fusion Method for Sequential Recommendation. - Shuhan Wang; Bin Shen; Xu Min; Yong He 009; Xiaolu Zhang; Liang Zhang; Jun Zhou 011; Linjian Mo (WWW (Companion Volume), 2024)

Can Small Language Models be Good Reasoners for Sequential Recommendation? - Yuling Wang; Changxin Tian; Binbin Hu; Yanhua Yu; Ziqi Liu; Zhiqiang Zhang 012; Jun Zhou 011; Liang Pang; Xiao Wang 017 (WWW, 2024)

Leave No One Behind: Online Self-Supervised Self-Distillation for Sequential Recommendation. - Shaowei Wei; Zhengwei Wu; Xin Li 090; Qintong Wu; Zhiqiang Zhang 012; Jun Zhou 011; Lihong Gu; Jinjie Gu (WWW, 2024)

Calibrating Graph Neural Networks from a Data-centric Perspective. - Cheng Yang 002; Chengdong Yang; Chuan Shi 001; Yawen Li 001; Zhiqiang Zhang 012; Jun Zhou 011 (WWW, 2024)

A Comprehensive Study of Knowledge Editing for Large Language Models. - Ningyu Zhang 001; Yunzhi Yao; Bozhong Tian; Peng Wang 104; Shumin Deng; Mengru Wang; Zekun Xi; Shengyu Mao; Jintian Zhang; Yuansheng Ni; Siyuan Cheng 008; Ziwen Xu; et al. (CoRR, 2024)

GLISP: A Scalable GNN Learning System by Exploiting Inherent Structural Properties of Graphs. - Zhongshu Zhu; Bin Jing; Xiaopei Wan; Zhizhen Liu; Lei Liang 002; Jun Zhou 011 (CoRR, 2024)

AntDT: A Self-Adaptive Distributed Training Framework for Leader and Straggler Nodes. - Youshao Xiao; Lin Ju; Zhenglei Zhou; Siyuan Li; Zhaoxin Huan; Dalong Zhang; Rujie Jiang; Lin Wang 098; Xiaolu Zhang; Lei Liang 001; Jun Zhou 011 (CoRR, 2024)

AntBatchInfer: Elastic Batch Inference in the Kubernetes Cluster. - Siyuan Li; Youshao Xiao; Fanzhuang Meng; Lin Ju; Lei Liang 002; Lin Wang 098; Jun Zhou 011 (CoRR, 2024)

Scale-Invariant Feature Disentanglement via Adversarial Learning for UAV-based Object Detection. - Fan Liu 003; Liang Yao; Chuanyi Zhang; Ting Wu; Xinlei Zhang; Xiruo Jiang; Jun Zhou 011 (CoRR, 2024)

Your decision path does matter in pre-training industrial recommenders with multi-source behaviors. - Chunjing Gan; Binbin Hu; Bo Huang; Ziqi Liu; Jian Ma; Zhiqiang Zhang 012; Wenliang Zhong; Jun Zhou 011 (CoRR, 2024)

Similarity is Not All You Need: Endowing Retrieval Augmented Generation with Multi Layered Thoughts. - Chunjing Gan; Dan Yang 004; Binbin Hu; Hanxiao Zhang; Siyuan Li; Ziqi Liu; Yue Shen; Lin Ju; Zhiqiang Zhang 012; Jinjie Gu; Lei Liang 001; Jun Zhou 011 (CoRR, 2024)

Personalized Binomial DAGs Learning with Network Structured Covariates. - Boxin Zhao; Weishi Wang; Dingyuan Zhu; Ziqi Liu; Dong Wang 062; Zhiqiang Zhang 012; Jun Zhou 011; Mladen Kolar (CoRR, 2024)

Interpretable Catastrophic Forgetting of Large Language Model Fine-tuning via Instruction Vector. - Gangwei Jiang; Caigao Jiang; Zhaoyi Li; Siqiao Xue; Jun Zhou 011; Linqi Song; Defu Lian; Ying Wei 001 (CoRR, 2024)

Making Large Vision Language Models to be Good Few-shot Learners. - Fan Liu 003; Wenwen Cai; Jian Huo; Chuanyi Zhang; Delong Chen; Jun Zhou 011 (CoRR, 2024)

KAG: Boosting LLMs in Professional Domains via Knowledge Augmented Generation. - Lei Liang 002; Mengshu Sun; Zhengke Gui; Zhongshu Zhu; Zhouyu Jiang; Ling Zhong; Yuan Qu; Peilong Zhao; Zhongpu Bo; Jin Yang; Huaidong Xiong; Lin Yuan; et al. (CoRR, 2024)

LLMOPT: Learning to Define and Solve General Optimization Problems from Scratch. - Caigao Jiang; Xiang Shu; Hong Qian; Xingyu Lu; Jun Zhou 011; Aimin Zhou; Yang Yu (CoRR, 2024)

RemoteTrimmer: Adaptive Structural Pruning for Remote Sensing Image Classification. - Guangwenjie Zou; Liang Yao; Fan Liu 003; Chuanyi Zhang; Xin Li 090; Ning Chen; Shengxiang Xu; Jun Zhou 011 (CoRR, 2024)

Finite Element Method on locally refined composite meshes for Dirichlet fractional Laplacian. - Jun Zhou 011; Hongbin Chen (J. Comput. Sci., 2024)

Integration of large language models and federated learning. - Chaochao Chen 001; Xiaohua Feng; Yuyuan Li; Lingjuan Lyu; Jun Zhou 011; Xiaolin Zheng; Jianwei Yin (Patterns, 2024)

Towards Practical Backdoor Attacks on Federated Learning Systems. - Chenghui Shi; Shouling Ji; Xudong Pan; Xuhong Zhang 002; Mi Zhang 001; Min Yang 002; Jun Zhou 011; Jianwei Yin; Ting Wang 006 (IEEE Trans. Dependable Secur. Comput., 2024)

Toward Enhanced Robustness in Unsupervised Graph Representation Learning: A Graph Information Bottleneck Perspective. - Jihong Wang 003; Minnan Luo; Jundong Li; Ziqi Liu; Jun Zhou 011; Qinghua Zheng (IEEE Trans. Knowl. Data Eng., 2024)

A distribution-free method for probabilistic prediction. - Qitao Shi; Ya-Lin Zhang 001; Lu Yu 006; Feng Zhu 011; Longfei Li; Jun Zhou 011; Yanming Fang (Expert Syst. Appl., 2024)

Multi-Task Decouple Learning With Hierarchical Attentive Point Process. - Weichang Wu; Xiaolu Zhang; Shiwan Zhao; Chilin Fu; Jun Zhou 011 (IEEE Trans. Knowl. Data Eng., 2024)

Survey and open problems in privacy-preserving knowledge graph: merging, query, representation, completion, and applications. - Chao-Chao Chen 001; Fei Zheng; Jamie Cui; Yuwei Cao; Guanfeng Liu 001; Jia Wu 001; Jun Zhou 011 (Int. J. Mach. Learn. Cybern., 2024)

KGFabric: A Scalable Knowledge Graph Warehouse for Enterprise Data Interconnection. - Peng Yi; Lei Liang 002; Zhang Da; Chen Yong; Jinye Zhu; Xiangyu Liu; Kun Tang; Jialin Chen; Hao Lin; Leijie Qiu; Jun Zhou 011 (Proc. VLDB Endow., 2024)

Description-Enhanced Label Embedding Contrastive Learning for Text Classification. - Kun Zhang 015; Le Wu; Guangyi Lv; Enhong Chen; Shulan Ruan; Jing Liu 001; Zhiqiang Zhang 012; Jun Zhou 011; Meng Wang 001 (IEEE Trans. Neural Networks Learn. Syst., 2024)

Hyperbolic Graph Learning for Social Recommendation. - Yonghui Yang; Le Wu; Kun Zhang 015; Richang Hong; Hailin Zhou; Zhiqiang Zhang 012; Jun Zhou 011; Meng Wang 001 (IEEE Trans. Knowl. Data Eng., 2024)

Learning Causal Transition Matrix for Instance-dependent Label Noise. - Jiahui Li 003; Tai-Wei Chang; Kun Kuang; Ximing Li; Long Chen 016; Jun Zhou 011 (AAAI, 2025)

Explore What LLM Does Not Know in Complex Question Answering. - Xin Lin 005; Zhenya Huang; Zhiqiang Zhang 012; Jun Zhou 011; Enhong Chen (AAAI, 2025)

Refining Sentence Embedding Model through Ranking Sentences Generation with Large Language Models. - Liyang He; Chenglong Liu; Rui Li 093; Zhenya Huang; Shulan Ruan; Jun Zhou 011; Enhong Chen (ACL (Findings), 2025)

Robust Preference Optimization via Dynamic Target Margins. - Jie Sun 030; Junkang Wu; Jiancan Wu; Zhibo Zhu; Xingyu Lu; Jun Zhou 011; Lintao Ma; Xiang Wang 010 (ACL (Findings), 2025)

LSSF: Safety Alignment for Large Language Models through Low-Rank Safety Subspace Fusion. - Guanghao Zhou; Panjia Qiu; Cen Chen 001; Hongyu Li; Jason Chu; Xin Zhang; Jun Zhou 011 (ACL (1), 2025)

Prompting DirectSAM for Semantic Contour Extraction in Remote Sensing Images. - Shiyu Miao; Delong Chen; Fan Liu 003; Chuanyi Zhang; Yanhui Gu; Shengjie Guo; Jun Zhou 011 (ICASSP, 2025)

Effectively PAIRing LLMs with Online Marketing via Progressive Prompting Augmentation. - Chunjing Gan; Dan Yang 004; Binbin Hu; Ziqi Liu; Yue Shen; Zhiqiang Zhang 012; Jinjie Gu; Jun Zhou 011; Guannan Zhang (ICDE, 2025)

Controllable Unlearning for Image-to-Image Generative Models via ϵ-Constrained Optimization. - Xiaohua Feng; Yuyuan Li; Chaochao Chen 001; Li Zhang; Longfei Li; Jun Zhou 011; Xiaolin Zheng (ICLR, 2025)

Unlocking the Power of Function Vectors for Characterizing and Mitigating Catastrophic Forgetting in Continual Instruction Tuning. - Gangwei Jiang; Caigao Jiang; Zhaoyi Li; Siqiao Xue; Jun Zhou 011; Linqi Song; Defu Lian; Ying Wei 001 (ICLR, 2025)

AntAkso: Claims Management System for Health Insurance in Alipay. - Qitao Shi; Jun Zhou 011; Ya-Lin Zhang 001; Longfei Li; Chaoyi Ma; Yifan Wu; Xiaobo Qin (KDD (1), 2025)

Stable Representation Learning on Graphs from Multiple Environments with Structure Distribution Shift. - Tong Zhao; Daixin Wang; Zhiqiang Zhang 012; Yulin Kang; Jun Zhou 011 (KDD (1), 2025)

Graph Disentangle Causal Model: Enhancing Causal Inference in Networked Observational Data. - Binbin Hu; Zhicheng An; Zhengwei Wu; Ke Tu; Ziqi Liu; Zhiqiang Zhang 012; Jun Zhou 011; Yufei Feng; Jiawei Chen 007 (WSDM, 2025)

IceBerg: Debiased Self-Training for Class-Imbalanced Node Classification. - Zhixun Li; Dingshuo Chen; Tong Zhao; Daixin Wang; Hongrui Liu; Zhiqiang Zhang 012; Jun Zhou 011; Jeffrey Xu Yu (WWW, 2025)

KAG: Boosting LLMs in Professional Domains via Knowledge Augmented Generation. - Lei Liang 002; Zhongpu Bo; Zhengke Gui; Zhongshu Zhu; Ling Zhong; Peilong Zhao; Mengshu Sun; Zhiqiang Zhang 012; Jun Zhou 011; Wenguang Chen; Wen Zhang 015; Huajun Chen (WWW (Companion Volume), 2025)

OneKE: A Dockerized Schema-Guided LLM Agent-based Knowledge Extraction System. - Yujie Luo; Xiangyuan Ru; Kangwei Liu; Lin Yuan; Mengshu Sun; Ningyu Zhang 001; Lei Liang 002; Zhiqiang Zhang 012; Jun Zhou 011; Lanning Wei; Da Zheng; Haofen Wang; et al. (WWW (Companion Volume), 2025)

MAQInstruct: Instruction-based Unified Event Relation Extraction. - Jun Xu 030; Mengshu Sun; Zhiqiang Zhang 012; Jun Zhou 011 (WWW (Companion Volume), 2025)

A Euclidean Affinity-Augmented Hyperbolic Neural Network for Semantic Segmentation of Remote Sensing Images. - Xin Li 090; Feng Xu 008; Fan Liu 003; Xin Lyu 001; Hongmin Gao 001; Jun Zhou 011; André Kaup (IEEE Trans. Geosci. Remote. Sens., 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)

Large Language Diffusion Models. - Shen Nie; Fengqi Zhu; Zebin You; Xiaolu Zhang; Jingyang Ou; Jun Hu; Jun Zhou 011; Yankai Lin; Ji-Rong Wen; Chongxuan Li (CoRR, 2025)

CCJA: Context-Coherent Jailbreak Attack for Aligned Large Language Models. - Guanghao Zhou; Panjia Qiu; Mingyuan Fan 003; Cen Chen 001; Mingyuan Chu; Xin Zhang; Jun Zhou 011 (CoRR, 2025)

SuperGPQA: Scaling LLM Evaluation across 285 Graduate Disciplines. - M.-A-P. Team; Xinrun Du; Yifan Yao; Kaijing Ma; Bingli Wang; Tianyu Zheng; Kang Zhu; Minghao Liu; Yiming Liang; Xiaolong Jin; Zhenlin Wei; Chujie Zheng; et al. (CoRR, 2025)

Self-attentive Rationalization for Interpretable Graph Contrastive Learning. - Sihang Li 002; Yanchen Luo; An Zhang 003; Xiang Wang 010; Longfei Li; Jun Zhou 011; Tat-Seng Chua (ACM Trans. Knowl. Discov. Data, 2025)

A Simple Data Augmentation for Graph Classification: A Perspective of Equivariance and Invariance. - Yongduo Sui; Shuyao Wang; Jie Sun 030; Zhiyuan Liu 010; Qing Cui; Longfei Li; Jun Zhou 011; Xiang Wang 010; Xiangnan He 001 (ACM Trans. Knowl. Discov. Data, 2025)

Toward Stable and Consistent Evaluation Results: A New Methodology for Base Model Evaluation. - Hongzhi Luan; Changxin Tian; Zhaoxin Huan; Xiaolu Zhang; Kunlong Chen; Zhiqiang Zhang 012; Jun Zhou 011 (CoRR, 2025)

Effective and Efficient Masked Image Generation Models. - Zebin You; Jingyang Ou; Xiaolu Zhang; Jun Hu; Jun Zhou 011; Chongxuan Li (CoRR, 2025)

MASS: Mathematical Data Selection via Skill Graphs for Pretraining Large Language Models. - Jiazheng Li 012; Lu Yu 006; Qing Cui; Zhiqiang Zhang 012; Jun Zhou 011; Yanfang Ye 001; Chuxu Zhang (CoRR, 2025)

LookAhead Tuning: Safer Language Models via Partial Answer Previews. - Kangwei Liu; Mengru Wang; Yujie Luo; Lin Yuan; Mengshu Sun; Ningyu Zhang 001; Lei Liang 002; Zhiqiang Zhang 012; Jun Zhou 011; Huajun Chen (CoRR, 2025)

POLYRAG: Integrating Polyviews into Retrieval-Augmented Generation for Medical Applications. - Chunjing Gan; Dan Yang 004; Binbin Hu; Ziqi Liu; Yue Shen; Zhiqiang Zhang 012; Jian Wang; Jun Zhou 011 (CoRR, 2025)

RV-Syn: Rational and Verifiable Mathematical Reasoning Data Synthesis based on Structured Function Library. - Jiapeng Wang; Jinhao Jiang; Zhiqiang Zhang 012; Jun Zhou 011; Wayne Xin Zhao (CoRR, 2025)

Ming-Lite-Uni: Advancements in Unified Architecture for Natural Multimodal Interaction. - Inclusion AI; Biao Gong; Cheng Zou; Dandan Zheng; Hu Yu; Jingdong Chen; Jian Sun 001; Junbo Zhao; Jun Zhou 011; Kaixiang Ji; Lixiang Ru; Libin Wang; et al. (CoRR, 2025)

SHARP: Synthesizing High-quality Aligned Reasoning Problems for Large Reasoning Models Reinforcement Learning. - Xiong Jun Wu; Zhenduo Zhang; Zujie Wen; Zhiqiang Zhang 012; Wang Ren; Lei Shi; Cai Chen; Deng Zhao; Qing Wang; Xudong Han; Chengfu Tang; Dingnan Jin; et al. (CoRR, 2025)

LLaDA-V: Large Language Diffusion Models with Visual Instruction Tuning. - Zebin You; Shen Nie; Xiaolu Zhang; Jun Hu; Jun Zhou 011; Zhiwu Lu 001; Ji-Rong Wen; Chongxuan Li (CoRR, 2025)

Understanding and Mitigating Overrefusal in LLMs from an Unveiling Perspective of Safety Decision Boundary. - Licheng Pan; Yongqi Tong; Xin Zhang; Xiaolu Zhang; Jun Zhou 011; Zhixuan Chu (CoRR, 2025)

LLaDA 1.5: Variance-Reduced Preference Optimization for Large Language Diffusion Models. - Fengqi Zhu; Rongzhen Wang; Shen Nie; Xiaolu Zhang; Chunwei Wu; Jun Hu; Jun Zhou 011; Jianfei Chen; Yankai Lin; Ji-Rong Wen; Chongxuan Li (CoRR, 2025)

KAG-Thinker: Interactive Thinking and Deep Reasoning in LLMs via Knowledge-Augmented Generation. - Dalong Zhang; Jun Xu 030; Jun Zhou 011; Lei Liang 002; Lin Yuan; Ling Zhong; Mengshu Sun; Peilong Zhao; QiWei Wang; Xiaorui Wang; Xinkai Du; Yangyang Hou; et al. (CoRR, 2025)

Enhancing LLM Tool Use with High-quality Instruction Data from Knowledge Graph. - Jingwei Wang; Zai Zhang 002; Hao Qian 003; Chunjing Gan; Binbin Hu; Ziqi Liu; Zhiqiang Zhang 012; Jun Zhou 011; Bin Shi; Bo Dong 001 (CoRR, 2025)

Enhancing Cross-task Transfer of Large Language Models via Activation Steering. - Xinyu Tang 004; Zhihao Lv; Xiaoxue Cheng; Junyi Li; Wayne Xin Zhao; Zujie Wen; Zhiqiang Zhang 012; Jun Zhou 011 (CoRR, 2025)

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training. - Changxin Tian; Jiapeng Wang; Qian Zhao; Kunlong Chen; Jia Liu; Ziqi Liu; Jiaxin Mao; Wayne Xin Zhao; Zhiqiang Zhang 012; Jun Zhou 011 (CoRR, 2025)

Towards Greater Leverage: Scaling Laws for Efficient Mixture-of-Experts Language Models. - Changxin Tian; Kunlong Chen; Jia Liu; Ziqi Liu; Zhiqiang Zhang 012; Jun Zhou 011 (CoRR, 2025)

HORAE: Temporal Multi-Interest Pre-training for Sequential Recommendation. - Shirui Hu; Weichang Wu; Zuoli Tang; Zhaoxin Huan; Lin Wang 098; Xiaolu Zhang; Jun Zhou 011; Lixin Zou; Chenliang Li (ACM Trans. Inf. Syst., 2025)

Multi-stage Bayesian Prototype Refinement with feature weighting for few-shot classification. - Wei Xu; Xiaocong Zhou; Shengxiang Xu; Fan Liu 003; Chuanyi Zhang; Feifan Li; Wenwen Cai; Jun Zhou 011 (Pattern Anal. Appl., 2025)

One Model for All: Large Language Models Are Domain-Agnostic Recommendation Systems. - Zuoli Tang; Zhaoxin Huan; Zihao Li 005; Xiaolu Zhang; Jun Hu; Chilin Fu; Jun Zhou 011; Lixin Zou; Chenliang Li (ACM Trans. Inf. Syst., 2025)

Exploring and reconstructing latent domains for multi-source domain adaptation. - Wanjun Liang; Meijuan Tan; Xiangyu Meng; Chengzhe Zhang; Jun Zhou 011; Chilin Fu; Xiaolu Zhang; Changsheng Li (Signal Process., 2026)