Jun Zhou

459 papers A* 116A 51B 3C 2Misc 3Journal 214Unranked 70
YearRankTypeTitle / Venue / Authors
2026 J jnl
Deterministic Differentiable Structured Pruning for Large Language Models.
CoRR
Weiyu Huang, Pengle Zhang, Xiaolu Zhang, Jun Zhou, Jun Zhu, Jianfei Chen
2026 J jnl
Exploring and reconstructing latent domains for multi-source domain adaptation.
Signal Process.
Wanjun Liang, Meijuan Tan, Xiangyu Meng, Chengzhe Zhang, Jun Zhou, Chilin Fu, Xiaolu Zhang, Changsheng Li
2026 J jnl
Fine-Grained Zero-Shot Composed Image Retrieval with Complementary Visual-Semantic Integration.
CoRR
Yongcong Ye, Kai Zhang, Yanghai Zhang, Enhong Chen, Longfei Li, Jun Zhou
2026 A* conf
From Entity Reliability to Clean Feedback: An Entity-Aware Denoising Framework Beyond Interaction-Level Signals.
WWW
Ze Liu, Xianquan Wang, Shuochen Liu, Jie Ma, Huibo Xu, Yupeng Han, Kai Zhang, Jun Zhou
2026 J jnl
GRIP: Geometric Refinement and Adaptive Information Potential for Data Efficiency.
CoRR
Changhao Wang, Jiaolong Yang, Xinhao Yao, Yunfei Yu, Peng Jiao, Lu Yu, Junpeng Fang, Riccardo Cantoro, Qing Cui, Jun Zhou
2026 J jnl
LLaDA-o: An Effective and Length-Adaptive Omni Diffusion Model.
CoRR
Zebin You, Xiaolu Zhang, Jun Zhou, Chongxuan Li, Ji-Rong Wen
2026 J jnl
LLaDA2.1: Speeding Up Text Diffusion via Token Editing.
CoRR
Tiwei Bie, Maosong Cao, Xiang Cao, Bingsen Chen, Fuyuan Chen, Kun Chen, Lun Du, Daozhuo Feng, Haibo Feng, Mingliang Gong, Zhuocheng Gong, Yanmei Gu, Jian Guan, Kaiyuan Guan, Hongliang He, Zenan Huang, Juyong Jiang, Zhonghui Jiang, Zhenzhong Lan, Chengxi Li, Jianguo Li, Zehuan Li, Huabin Liu, Lin Liu, Guoshan Lu, Yuan Lu, Yuxin Ma, Xingyu Mou, Zhenxuan Pan, Kaida Qiu, Yuji Ren, Jianfeng Tan, Yiding Tian, Zian Wang, Lanning Wei, Tao Wu, Yipeng Xing, Wentao Ye, Liangyu Zha, Tianze Zhang, Xiaolu Zhang, Junbo Zhao, Da Zheng, Hao Zhong, Wanli Zhong, Jun Zhou, Liwang Zhu, Muzhi Zhu, Yihong Zhuang
2026 A conf
LookAhead Tuning: Safer Language Models via Partial Answer Previews.
WSDM
Kangwei Liu, Mengru Wang, Yujie Luo, Lin Yuan, Mengshu Sun, Lei Liang, Zhiqiang Zhang, Jun Zhou, Bryan Hooi, Shumin Deng
2026 J jnl
MergeMix: Optimizing Mid-Training Data Mixtures via Learnable Model Merging.
CoRR
Jiapeng Wang, Changxin Tian, Kunlong Chen, Ziqi Liu, Jiaxin Mao, Wayne Xin Zhao, Zhiqiang Zhang, Jun Zhou
2026 J jnl
On Representation Redundancy in Large-Scale Instruction Tuning Data Selection.
CoRR
Youwei Shu, Shaomian Zheng, Dingnan Jin, Wenjie Qu, Ziyao Guo, Qing Cui, Jun Zhou, Jiaheng Zhang
2026 — conf
RV-Syn: Rational and Verifiable Mathematical Reasoning Data Synthesis based on Structured Function Library.
EACL (Findings)
Jiapeng Wang, Jinhao Jiang, Zhiqiang Zhang, Jun Zhou, Xin Zhao
2026 A* conf
Taming the Long Tail: Efficient Item-wise Sharpness-Aware Minimization for LLM-based Recommender Systems.
WWW
Jiaming Zhang, Yuyuan Li, Xiaohua Feng, Li Zhang, Longfei Li, Jun Zhou, Chaochao Chen
2026 J jnl
Taming the Long Tail: Efficient Item-wise Sharpness-Aware Minimization for LLM-based Recommender Systems.
CoRR
Jiaming Zhang, Yuyuan Li, Xiaohua Feng, Li Zhang, Longfei Li, Jun Zhou, Chaochao Chen
2026 A* conf
Thinker: Training LLMs in Hierarchical Thinking for Deep Search via Multi-Turn Interaction.
AAAI
Jun Xu, Xinkai Du, Yu Ao, Peilong Zhao, Yang Li, Ling Zhong, Lin Yuan, Zhongpu Bo, Xiaorui Wang, Mengshu Sun, Zhengke Gui, Dalong Zhang, Zhaoyang Wang, QiWei Wang, Yangyang Hou, ZhiYing Yi, Haofen Wang, Huajun Chen, Lei Liang, Jun Zhou
2026 A* conf
Token-level Collaborative Alignment for LLM-based Generative Recommendation.
WWW
Fake Lin, Binbin Hu, Zhi Zheng, Xi Zhu, Ziqi Liu, Zhiqiang Zhang, Jun Zhou, Tong Xu
2026 J jnl
Token-level Collaborative Alignment for LLM-based Generative Recommendation.
CoRR
Fake Lin, Binbin Hu, Zhi Zheng, Xi Zhu, Ziqi Liu, Zhiqiang Zhang, Jun Zhou, Tong Xu
2026 J jnl
Training-Trajectory-Aware Token Selection.
CoRR
Zhanming Shen, Jiaqi Hu, Zeyu Qin, Hao Chen, Wentao Ye, Zenan Huang, Yihong Zhuang, Guoshan Lu, Jun Zhou, Junbo Zhao
2026 J jnl
UniGeM: Unifying Data Mixing and Selection via Geometric Exploration and Mining.
CoRR
Changhao Wang, Yunfei Yu, Xinhao Yao, Jiaolong Yang, Riccardo Cantoro, Chaobo Li, Qing Cui, Jun Zhou
2026 J jnl
When Sharpening Becomes Collapse: Sampling Bias and Semantic Coupling in RL with Verifiable Rewards.
CoRR
Mingyuan Fan, Weiguang Han, Daixin Wang, Cen Chen, Zhiqiang Zhang, Jun Zhou
2025 J jnl
A Euclidean Affinity-Augmented Hyperbolic Neural Network for Semantic Segmentation of Remote Sensing Images.
IEEE Trans. Geosci. Remote. Sens.
Xin Li, Feng Xu, Fan Liu, Xin Lyu, Hongmin Gao, Jun Zhou, André Kaup
2025 J jnl
A Simple Data Augmentation for Graph Classification: A Perspective of Equivariance and Invariance.
ACM Trans. Knowl. Discov. Data
Yongduo Sui, Shuyao Wang, Jie Sun, Zhiyuan Liu, Qing Cui, Longfei Li, Jun Zhou, Xiang Wang, Xiangnan He
2025 J jnl
ARGenSeg: Image Segmentation with Autoregressive Image Generation Model.
CoRR
Xiaolong Wang, Lixiang Ru, Ziyuan Huang, Kaixiang Ji, Dandan Zheng, Jingdong Chen, Jun Zhou
2025 J jnl
Adaptive Client Sampling in Federated Learning via Online Learning with Bandit Feedback.
J. Mach. Learn. Res.
Boxin Zhao, Lingxiao Wang, Ziqi Liu, Zhiqiang Zhang, Jun Zhou, Chaochao Chen, Mladen Kolar
2025 — conf
AntAkso: Claims Management System for Health Insurance in Alipay.
KDD (1)
Qitao Shi, Jun Zhou, Ya-Lin Zhang, Longfei Li, Chaoyi Ma, Yifan Wu, Xiaobo Qin
2025 A conf
Arrows of Math Reasoning Data Synthesis for Large Language Models: Diversity, Complexity and Correctness.
CIKM
Sirui Chen, Changxin Tian, Binbin Hu, Kunlong Chen, Ziqi Liu, Zhiqiang Zhang, Jun Zhou
2025 J jnl
Arrows of Math Reasoning Data Synthesis for Large Language Models: Diversity, Complexity and Correctness.
CoRR
Sirui Chen, Changxin Tian, Binbin Hu, Kunlong Chen, Ziqi Liu, Zhiqiang Zhang, Jun Zhou
2025 J jnl
CCJA: Context-Coherent Jailbreak Attack for Aligned Large Language Models.
CoRR
Guanghao Zhou, Panjia Qiu, Mingyuan Fan, Cen Chen, Mingyuan Chu, Xin Zhang, Jun Zhou
2025 — conf
Contrastive Scenario-Aware Meta Prompting for Multi-scenario Recommendation.
DASFAA (6)
Ang Li, Jian Hu, Ke Ding, Xiaolu Zhang, Jun Zhou, Yong He
2025 A* conf
Controllable Unlearning for Image-to-Image Generative Models via ϵ-Constrained Optimization.
ICLR
Xiaohua Feng, Yuyuan Li, Chaochao Chen, Li Zhang, Longfei Li, Jun Zhou, Xiaolin Zheng
2025 A* conf
Effective and Efficient Masked Image Generation Models.
ICML
Zebin You, Jingyang Ou, Xiaolu Zhang, Jun Hu, Jun Zhou, Chongxuan Li
2025 J jnl
Effective and Efficient Masked Image Generation Models.
CoRR
Zebin You, Jingyang Ou, Xiaolu Zhang, Jun Hu, Jun Zhou, Chongxuan Li
2025 A* conf
Effectively PAIRing LLMs with Online Marketing via Progressive Prompting Augmentation.
ICDE
Chunjing Gan, Dan Yang, Binbin Hu, Ziqi Liu, Yue Shen, Zhiqiang Zhang, Jinjie Gu, Jun Zhou, Guannan Zhang
2025 J jnl
Enhancing Cross-task Transfer of Large Language Models via Activation Steering.
CoRR
Xinyu Tang, Zhihao Lv, Xiaoxue Cheng, Junyi Li, Wayne Xin Zhao, Zujie Wen, Zhiqiang Zhang, Jun Zhou
2025 J jnl
Enhancing LLM Tool Use with High-quality Instruction Data from Knowledge Graph.
CoRR
Jingwei Wang, Zai Zhang, Hao Qian, Chunjing Gan, Binbin Hu, Ziqi Liu, Zhiqiang Zhang, Jun Zhou, Bin Shi, Bo Dong
2025 J jnl
Every Attention Matters: An Efficient Hybrid Architecture for Long-Context Reasoning.
CoRR
Ling Team, Bin Han, Caizhi Tang, Chen Liang, Donghao Zhang, Fan Yuan, Feng Zhu, Jie Gao, Jingyu Hu, Longfei Li, Meng Li, Mingyang Zhang, Peijie Jiang, Peng Jiao, Qian Zhao, Qingyuan Yang, Wenbo Shen, Xinxing Yang, Yalin Zhang, Yankun Ren, Yao Zhao, Yibo Cao, Yixuan Sun, Yue Zhang, Yuchen Fang, Zibin Lin, Zixuan Cheng, Jun Zhou
2025 J jnl
Every Sample Matters: Leveraging Mixture-of-Experts and High-Quality Data for Efficient and Accurate Code LLM.
CoRR
Codefuse, Wenting Cai, Yuchen Cao, Chaoyu Chen, Chen Chen, Siba Chen, Qing Cui, Peng Di, Junpeng Fang, Zi Gong, Ting Guo, Zhengyu He, Yang Huang, Cong Li, Jianguo Li, Zheng Li, Shijie Lian, Bingchang Liu, Songshan Luo, Shuo Mao, Min Shen, Jian Wu, Jiaolong Yang, Wenjie Yang, Tong Ye, Hang Yu, Wei Zhang, Zhenduo Zhang, Hailin Zhao, Xunjin Zheng, Jun Zhou
2025 A* conf
Explore What LLM Does Not Know in Complex Question Answering.
AAAI
Xin Lin, Zhenya Huang, Zhiqiang Zhang, Jun Zhou, Enhong Chen
2025 A* conf
Fine-Grained Zero-Shot Composed Image Retrieval with Complementary Visual-Semantic Integration.
ICDM
Yongcong Ye, Kai Zhang, Yanghai Zhang, Enhong Chen, Longfei Li, Jun Zhou
2025 A conf
Graph Disentangle Causal Model: Enhancing Causal Inference in Networked Observational Data.
WSDM
Binbin Hu, Zhicheng An, Zhengwei Wu, Ke Tu, Ziqi Liu, Zhiqiang Zhang, Jun Zhou, Yufei Feng, Jiawei Chen
2025 J jnl
HORAE: Temporal Multi-Interest Pre-training for Sequential Recommendation.
ACM Trans. Inf. Syst.
Shirui Hu, Weichang Wu, Zuoli Tang, Zhaoxin Huan, Lin Wang, Xiaolu Zhang, Jun Zhou, Lixin Zou, Chenliang Li
2025 A* conf
IceBerg: Debiased Self-Training for Class-Imbalanced Node Classification.
WWW
Zhixun Li, Dingshuo Chen, Tong Zhao, Daixin Wang, Hongrui Liu, Zhiqiang Zhang, Jun Zhou, Jeffrey Xu Yu
2025 J jnl
IceBerg: Debiased Self-Training for Class-Imbalanced Node Classification.
CoRR
Zhixun Li, Dingshuo Chen, Tong Zhao, Daixin Wang, Hongrui Liu, Zhiqiang Zhang, Jun Zhou, Jeffrey Xu Yu
2025 J jnl
KAG-Thinker: Interactive Thinking and Deep Reasoning in LLMs via Knowledge-Augmented Generation.
CoRR
Dalong Zhang, Jun Xu, Jun Zhou, Lei Liang, Lin Yuan, Ling Zhong, Mengshu Sun, Peilong Zhao, QiWei Wang, Xiaorui Wang, Xinkai Du, Yangyang Hou, Yu Ao, Zhaoyang Wang, Zhengke Gui, ZhiYing Yi, Zhongpu Bo, Haofen Wang, Huajun Chen
2025 — conf
KAG: Boosting LLMs in Professional Domains via Knowledge Augmented Generation.
WWW (Companion Volume)
Lei Liang, Zhongpu Bo, Zhengke Gui, Zhongshu Zhu, Ling Zhong, Peilong Zhao, Mengshu Sun, Zhiqiang Zhang, Jun Zhou, Wenguang Chen, Wen Zhang, Huajun Chen
2025 J jnl
LLaDA 1.5: Variance-Reduced Preference Optimization for Large Language Diffusion Models.
CoRR
Fengqi Zhu, Rongzhen Wang, Shen Nie, Xiaolu Zhang, Chunwei Wu, Jun Hu, Jun Zhou, Jianfei Chen, Yankai Lin, Ji-Rong Wen, Chongxuan Li
2025 J jnl
LLaDA-MoE: A Sparse MoE Diffusion Language Model.
CoRR
Fengqi Zhu, Zebin You, Yipeng Xing, Zenan Huang, Lin Liu, Yihong Zhuang, Guoshan Lu, Kangyu Wang, Xudong Wang, Lanning Wei, Hongrui Guo, Jiaqi Hu, Wentao Ye, Tieyuan Chen, Chenchen Li, Chengfu Tang, Haibo Feng, Jun Hu, Jun Zhou, Xiaolu Zhang, Zhenzhong Lan, Junbo Zhao, Da Zheng, Chongxuan Li, Jianguo Li, Ji-Rong Wen
2025 J jnl
LLaDA-V: Large Language Diffusion Models with Visual Instruction Tuning.
CoRR
Zebin You, Shen Nie, Xiaolu Zhang, Jun Hu, Jun Zhou, Zhiwu Lu, Ji-Rong Wen, Chongxuan Li
2025 J jnl
LLaDA2.0: Scaling Up Diffusion Language Models to 100B.
CoRR
Tiwei Bie, Maosong Cao, Kun Chen, Lun Du, Mingliang Gong, Zhuochen Gong, Yanmei Gu, Jiaqi Hu, Zenan Huang, Zhenzhong Lan, Chengxi Li, Chongxuan Li, Jianguo Li, Zehuan Li, Huabin Liu, Lin Liu, Guoshan Lu, Xiaocheng Lu, Yuxin Ma, Jianfeng Tan, Lanning Wei, Ji-Rong Wen, Yipeng Xing, Xiaolu Zhang, Junbo Zhao, Da Zheng, Jun Zhou, Junlin Zhou, Zhanchao Zhou, Liwang Zhu, Yihong Zhuang
2025 — conf
LSSF: Safety Alignment for Large Language Models through Low-Rank Safety Subspace Fusion.
ACL (1)
Guanghao Zhou, Panjia Qiu, Cen Chen, Hongyu Li, Jason Chu, Xin Zhang, Jun Zhou
2025 — conf
LaMP-Val: Large Language Models Empower Personalized Valuation in Auction.
EMNLP (Findings)
Jie Sun, Tianyu Zhang, Houcheng Jiang, Kexin Huang, Xiang Shu, Zhibo Zhu, Lintao Ma, Xingyu Lu, Jun Zhou, Junkang Wu, Chi Luo, An Zhang, Jiancan Wu, Xiang Wang
2025 J jnl
Large Language Diffusion Models.
CoRR
Shen Nie, Fengqi Zhu, Zebin You, Xiaolu Zhang, Jingyang Ou, Jun Hu, Jun Zhou, Yankai Lin, Ji-Rong Wen, Chongxuan Li
2025 A* conf
Learning Causal Transition Matrix for Instance-dependent Label Noise.
AAAI
Jiahui Li, Tai-Wei Chang, Kun Kuang, Ximing Li, Long Chen, Jun Zhou
2025 J jnl
LookAhead Tuning: Safer Language Models via Partial Answer Previews.
CoRR
Kangwei Liu, Mengru Wang, Yujie Luo, Lin Yuan, Mengshu Sun, Ningyu Zhang, Lei Liang, Zhiqiang Zhang, Jun Zhou, Huajun Chen
2025 J jnl
M2-Reasoning: Empowering MLLMs with Unified General and Spatial Reasoning.
CoRR
Fudong Wang, Jiajia Liu, Jingdong Chen, Jun Zhou, Kaixiang Ji, Lixiang Ru, Qingpei Guo, Ruobing Zheng, Tianqi Li, Yi Yuan, Yifan Mao, Yuting Xiao, Ziping Ma
2025 J jnl
M2-omni: Advancing Omni-MLLM for Comprehensive Modality Support with Competitive Performance.
CoRR
Qingpei Guo, Kaiyou Song, Zipeng Feng, Ziping Ma, Qinglong Zhang, Sirui Gao, Xuzheng Yu, Yunxiao Sun, Tai-Wei Chang, Jingdong Chen, Ming Yang, Jun Zhou
2025 — conf
MAQInstruct: Instruction-based Unified Event Relation Extraction.
WWW (Companion Volume)
Jun Xu, Mengshu Sun, Zhiqiang Zhang, Jun Zhou
2025 A* conf
MASS: Mathematical Data Selection via Skill Graphs for Pretraining Large Language Models.
ICML
Jiazheng Li, Lu Yu, Qing Cui, Zhiqiang Zhang, Jun Zhou, Yanfang Ye, Chuxu Zhang
2025 J jnl
MASS: Mathematical Data Selection via Skill Graphs for Pretraining Large Language Models.
CoRR
Jiazheng Li, Lu Yu, Qing Cui, Zhiqiang Zhang, Jun Zhou, Yanfang Ye, Chuxu Zhang
2025 J jnl
MaP: A Unified Framework for Reliable Evaluation of Pre-training Dynamics.
CoRR
Jiapeng Wang, Changxin Tian, Kunlong Chen, Ziqi Liu, Jiaxin Mao, Wayne Xin Zhao, Zhiqiang Zhang, Jun Zhou
2025 J jnl
Ming-Lite-Uni: Advancements in Unified Architecture for Natural Multimodal Interaction.
CoRR
Inclusion AI, Biao Gong, Cheng Zou, Dandan Zheng, Hu Yu, Jingdong Chen, Jian Sun, Junbo Zhao, Jun Zhou, Kaixiang Ji, Lixiang Ru, Libin Wang, Qingpei Guo, Rui Liu, Weilong Chai, Xinyu Xiao, Ziyuan Huang
2025 J jnl
Ming-Omni: A Unified Multimodal Model for Perception and Generation.
CoRR
Inclusion AI, Biao Gong, Cheng Zou, Chuanyang Zheng, Chunluan Zhou, Canxiang Yan, Chunxiang Jin, Chunjie Shen, Dandan Zheng, Fudong Wang, Furong Xu, Guangming Yao, Jun Zhou, Jingdong Chen, Jianxin Sun, Jiajia Liu, Jianjiang Zhu, Jun Peng, Kaixiang Ji, Kaiyou Song, Kaimeng Ren, Libin Wang, Lixiang Ru, Lele Xie, Longhua Tan, Lyuxin Xue, Lan Wang, Mochen Bai, Ning Gao, Pei Chen, Qingpei Guo, Qinglong Zhang, Qiang Xu, Rui Liu, Ruijie Xiong, Sirui Gao, Tinghao Liu, Taisong Li, Weilong Chai, Xinyu Xiao, Xiaomei Wang, Xiaoxue Chen, Xiao Lu, Xiaoyu Li, Xingning Dong, Xuzheng Yu, Yi Yuan, Yuting Gao, Yunxiao Sun, Yipeng Chen, Yifei Wu, Yongjie Lyu, Ziping Ma, Zipeng Feng, Zhijiang Fang, Zhihao Qiu, Ziyuan Huang, Zhengyu He
2025 J jnl
Ming-UniAudio: Speech LLM for Joint Understanding, Generation and Editing with Unified Representation.
CoRR
Canxiang Yan, Chunxiang Jin, Dawei Huang, Haibing Yu, Han Peng, Hui Zhan, Jie Gao, Jing Peng, Jingdong Chen, Jun Zhou, Kaimeng Ren, Ming Yang, Mingxue Yang, Qiang Xu, Qin Zhao, Ruijie Xiong, Shaoxiong Lin, Xuezhi Wang, Yi Yuan, Yifei Wu, Yongjie Lyu, Zhengyu He, Zhihao Qiu, Zhiqiang Fang, Ziyuan Huang
2025 J jnl
Ming-UniVision: Joint Image Understanding and Generation with a Unified Continuous Tokenizer.
CoRR
Ziyuan Huang, Dandan Zheng, Cheng Zou, Rui Liu, Xiaolong Wang, Kaixiang Ji, Weilong Chai, Jianxin Sun, Libin Wang, Yongjie Lv, Taozhi Huang, Jiajia Liu, Qingpei Guo, Ming Yang, Jingdong Chen, Jun Zhou
2025 J jnl
Mix Data or Merge Models? Balancing the Helpfulness, Honesty, and Harmlessness of Large Language Model via Model Merging.
CoRR
Jinluan Yang, Dingnan Jin, Anke Tang, Li Shen, Didi Zhu, Zhengyu Chen, Daixin Wang, Qing Cui, Zhiqiang Zhang, Jun Zhou, Fei Wu, Kun Kuang
2025 J jnl
Multi-stage Bayesian Prototype Refinement with feature weighting for few-shot classification.
Pattern Anal. Appl.
Wei Xu, Xiaocong Zhou, Shengxiang Xu, Fan Liu, Chuanyi Zhang, Feifan Li, Wenwen Cai, Jun Zhou
2025 J jnl
One Model for All: Large Language Models Are Domain-Agnostic Recommendation Systems.
ACM Trans. Inf. Syst.
Zuoli Tang, Zhaoxin Huan, Zihao Li, Xiaolu Zhang, Jun Hu, Chilin Fu, Jun Zhou, Lixin Zou, Chenliang Li
2025 — conf
OneKE: A Dockerized Schema-Guided LLM Agent-based Knowledge Extraction System.
WWW (Companion Volume)
Yujie Luo, Xiangyuan Ru, Kangwei Liu, Lin Yuan, Mengshu Sun, Ningyu Zhang, Lei Liang, Zhiqiang Zhang, Jun Zhou, Lanning Wei, Da Zheng, Haofen Wang, Huajun Chen
2025 J jnl
POLYRAG: Integrating Polyviews into Retrieval-Augmented Generation for Medical Applications.
CoRR
Chunjing Gan, Dan Yang, Binbin Hu, Ziqi Liu, Yue Shen, Zhiqiang Zhang, Jian Wang, Jun Zhou
2025 Misc conf
Prompting DirectSAM for Semantic Contour Extraction in Remote Sensing Images.
ICASSP
Shiyu Miao, Delong Chen, Fan Liu, Chuanyi Zhang, Yanhui Gu, Shengjie Guo, Jun Zhou
2025 A* conf
RED: Unleashing Token-Level Rewards from Holistic Feedback via Reward Redistribution.
EMNLP
Jiahui Li, Lin Li, Tai-Wei Chang, Kun Kuang, Long Chen, Jun Zhou, Cheng Yang
2025 J jnl
RV-Syn: Rational and Verifiable Mathematical Reasoning Data Synthesis based on Structured Function Library.
CoRR
Jiapeng Wang, Jinhao Jiang, Zhiqiang Zhang, Jun Zhou, Wayne Xin Zhao
2025 J jnl
Recommendations for Inactive Users: a Cross Domain Approach with Graph Neural Networks.
Int. J. Mach. Learn. Cybern.
Jun Zhou, Ziqi Liu, Meijuan Tan, Xiangyu Meng, Xiaocheng Cheng, Jianping Wei, Zhiqiang Zhang, Fengyuan Yu, Chaochao Chen, Jianwei Yin
2025 — conf
Refining Sentence Embedding Model through Ranking Sentences Generation with Large Language Models.
ACL (Findings)
Liyang He, Chenglong Liu, Rui Li, Zhenya Huang, Shulan Ruan, Jun Zhou, Enhong Chen
2025 J jnl
Refining Sentence Embedding Model through Ranking Sentences Generation with Large Language Models.
CoRR
Liyang He, Chenglong Liu, Rui Li, Zhenya Huang, Shulan Ruan, Jun Zhou, Enhong Chen
2025 A* conf
Rethinking Causal Ranking: A Balanced Perspective on Uplift Model Evaluation.
ICML
Minqin Zhu, Zexu Sun, Ruoxuan Xiong, Anpeng Wu, Baohong Li, Caizhi Tang, Jun Zhou, Fei Wu, Kun Kuang
2025 J jnl
Rethinking Sample Polarity in Reinforcement Learning with Verifiable Rewards.
CoRR
Xinyu Tang, Yuliang Zhan, Zhixun Li, Wayne Xin Zhao, Zhenduo Zhang, Zujie Wen, Zhiqiang Zhang, Jun Zhou
2025 — conf
Robust Preference Optimization via Dynamic Target Margins.
ACL (Findings)
Jie Sun, Junkang Wu, Jiancan Wu, Zhibo Zhu, Xingyu Lu, Jun Zhou, Lintao Ma, Xiang Wang
2025 J jnl
Robust Preference Optimization via Dynamic Target Margins.
CoRR
Jie Sun, Junkang Wu, Jiancan Wu, Zhibo Zhu, Xingyu Lu, Jun Zhou, Lintao Ma, Xiang Wang
2025 J jnl
SHARP: Synthesizing High-quality Aligned Reasoning Problems for Large Reasoning Models Reinforcement Learning.
CoRR
Xiong Jun Wu, Zhenduo Zhang, Zujie Wen, Zhiqiang Zhang, Wang Ren, Lei Shi, Cai Chen, Deng Zhao, Qing Wang, Xudong Han, Chengfu Tang, Dingnan Jin, Qing Cui, Jun Zhou
2025 J jnl
Self-attentive Rationalization for Interpretable Graph Contrastive Learning.
ACM Trans. Knowl. Discov. Data
Sihang Li, Yanchen Luo, An Zhang, Xiang Wang, Longfei Li, Jun Zhou, Tat-Seng Chua
2025 — conf
Stable Representation Learning on Graphs from Multiple Environments with Structure Distribution Shift.
KDD (1)
Tong Zhao, Daixin Wang, Zhiqiang Zhang, Yulin Kang, Jun Zhou
2025 J jnl
The Debate on RLVR Reasoning Capability Boundary: Shrinkage, Expansion, or Both? A Two-Stage Dynamic View.
CoRR
Xinhao Yao, Lu Yu, Xiaolin Hu, Fengwei Teng, Qing Cui, Jun Zhou, Yong Liu
2025 J jnl
Thinker: Training LLMs in Hierarchical Thinking for Deep Search via Multi-Turn Interaction.
CoRR
Jun Xu, Xinkai Du, Yu Ao, Peilong Zhao, Yang Li, Ling Zhong, Lin Yuan, Zhongpu Bo, Xiaorui Wang, Mengshu Sun, Zhengke Gui, Dalong Zhang, Zhaoyang Wang, QiWei Wang, Yangyang Hou, ZhiYing Yi, Haofen Wang, Huajun Chen, Lei Liang, Jun Zhou
2025 J jnl
Toward Stable and Consistent Evaluation Results: A New Methodology for Base Model Evaluation.
CoRR
Hongzhi Luan, Changxin Tian, Zhaoxin Huan, Xiaolu Zhang, Kunlong Chen, Zhiqiang Zhang, Jun Zhou
2025 J jnl
Towards Greater Leverage: Scaling Laws for Efficient Mixture-of-Experts Language Models.
CoRR
Changxin Tian, Kunlong Chen, Jia Liu, Ziqi Liu, Zhiqiang Zhang, Jun Zhou
2025 J jnl
Towards High Data Efficiency in Reinforcement Learning with Verifiable Reward.
CoRR
Xinyu Tang, Zhenduo Zhang, Yurou Liu, Wayne Xin Zhao, Zujie Wen, Zhiqiang Zhang, Jun Zhou
2025 A* conf
Understanding and Mitigating Overrefusal in LLMs from an Unveiling Perspective of Safety Decision Boundary.
EMNLP
Licheng Pan, Yongqi Tong, Xin Zhang, Xiaolu Zhang, Jun Zhou, Zhixuan Chu
2025 J jnl
Understanding and Mitigating Overrefusal in LLMs from an Unveiling Perspective of Safety Decision Boundary.
CoRR
Licheng Pan, Yongqi Tong, Xin Zhang, Xiaolu Zhang, Jun Zhou, Zhixuan Chu
2025 A* conf
Unlocking the Power of Function Vectors for Characterizing and Mitigating Catastrophic Forgetting in Continual Instruction Tuning.
ICLR
Gangwei Jiang, Caigao Jiang, Zhaoyi Li, Siqiao Xue, Jun Zhou, Linqi Song, Defu Lian, Ying Wei
2025 J jnl
Unlocking the Power of Function Vectors for Characterizing and Mitigating Catastrophic Forgetting in Continual Instruction Tuning.
CoRR
Gangwei Jiang, Caigao Jiang, Zhaoyi Li, Siqiao Xue, Jun Zhou, Linqi Song, Defu Lian, Ying Wei
2025 J jnl
WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training.
CoRR
Changxin Tian, Jiapeng Wang, Qian Zhao, Kunlong Chen, Jia Liu, Ziqi Liu, Jiaxin Mao, Wayne Xin Zhao, Zhiqiang Zhang, Jun Zhou
2024 J jnl
A Comprehensive Study of Knowledge Editing for Large Language Models.
CoRR
Ningyu Zhang, Yunzhi Yao, Bozhong Tian, Peng Wang, Shumin Deng, Mengru Wang, Zekun Xi, Shengyu Mao, Jintian Zhang, Yuansheng Ni, Siyuan Cheng, Ziwen Xu, Xin Xu, Jia-Chen Gu, Yong Jiang, Pengjun Xie, Fei Huang, Lei Liang, Zhiqiang Zhang, Xiaowei Zhu, Jun Zhou, Huajun Chen
2024 C conf
A High-Performance ORB Accelerator with Algorithm and Hardware Co-design for Visual Localization.
ISCAS
Xiuyuan Qi, Ye Liu, Shuang Hao, Zherong Liu, Kun Huang, Minghui Yang, Liang Zhou, Jun Zhou
2024 J jnl
A distribution-free method for probabilistic prediction.
Expert Syst. Appl.
Qitao Shi, Ya-Lin Zhang, Lu Yu, Feng Zhu, Longfei Li, Jun Zhou, Yanming Fang
2024 — conf
Adaptively Denoising Graph Neural Networks for Knowledge Distillation.
ECML/PKDD (8)
Yuxin Guo, Cheng Yang, Chuan Shi, Ke Tu, Zhengwei Wu, Zhiqiang Zhang, Jun Zhou
2024 — conf
Aligned Side Information Fusion Method for Sequential Recommendation.
WWW (Companion Volume)
Shuhan Wang, Bin Shen, Xu Min, Yong He, Xiaolu Zhang, Liang Zhang, Jun Zhou, Linjian Mo
2024 A* conf
An Active Masked Attention Framework for Many-to-Many Cross-Domain Recommendations.
ACM Multimedia
Feng Zhu, Xinxing Yang, Longfei Li, Jun Zhou
2024 J jnl
AntBatchInfer: Elastic Batch Inference in the Kubernetes Cluster.
CoRR
Siyuan Li, Youshao Xiao, Fanzhuang Meng, Lin Ju, Lei Liang, Lin Wang, Jun Zhou
2024 A* conf
AntDT: A Self-Adaptive Distributed Training Framework for Leader and Straggler Nodes.
ICDE
Youshao Xiao, Lin Ju, Zhenglei Zhou, Siyuan Li, Zhaoxin Huan, Dalong Zhang, Rujie Jiang, Lin Wang, Xiaolu Zhang, Lei Liang, Jun Zhou
2024 J jnl
AntDT: A Self-Adaptive Distributed Training Framework for Leader and Straggler Nodes.
CoRR
Youshao Xiao, Lin Ju, Zhenglei Zhou, Siyuan Li, Zhaoxin Huan, Dalong Zhang, Rujie Jiang, Lin Wang, Xiaolu Zhang, Lei Liang, Jun Zhou
2024 A* conf
Backdoor Adjustment via Group Adaptation for Debiased Coupon Recommendations.
AAAI
Junpeng Fang, Gongduo Zhang, Qing Cui, Caizhi Tang, Lihong Gu, Longfei Li, Jinjie Gu, Jun Zhou
2024 A* conf
Breaking the Length Barrier: LLM-Enhanced CTR Prediction in Long Textual User Behaviors.
SIGIR
Binzong Geng, Zhaoxin Huan, Xiaolu Zhang, Yong He, Liang Zhang, Fajie Yuan, Jun Zhou, Linjian Mo
2024 J jnl
Breaking the Length Barrier: LLM-Enhanced CTR Prediction in Long Textual User Behaviors.
CoRR
Binzong Geng, Zhaoxin Huan, Xiaolu Zhang, Yong He, Liang Zhang, Fajie Yuan, Jun Zhou, Linjian Mo
2024 A* conf
Calibrating Graph Neural Networks from a Data-centric Perspective.
WWW
Cheng Yang, Chengdong Yang, Chuan Shi, Yawen Li, Zhiqiang Zhang, Jun Zhou
2024 A* conf
Can Small Language Models be Good Reasoners for Sequential Recommendation?
WWW
Yuling Wang, Changxin Tian, Binbin Hu, Yanhua Yu, Ziqi Liu, Zhiqiang Zhang, Jun Zhou, Liang Pang, Xiao Wang
2024 J jnl
Can Small Language Models be Good Reasoners for Sequential Recommendation?
CoRR
Yuling Wang, Changxin Tian, Binbin Hu, Yanhua Yu, Ziqi Liu, Zhiqiang Zhang, Jun Zhou, Liang Pang, Xiao Wang
2024 A* conf
Collaborative Refining for Learning from Inaccurate Labels.
NeurIPS
Bin Han, Yi-Xuan Sun, Ya-Lin Zhang, Libang Zhang, Haoran Hu, Longfei Li, Jun Zhou, Guo Ye, Huimei He
2024 A* conf
Cost-Efficient Fraud Risk Optimization with Submodularity in Insurance Claim.
KDD
Yupeng Wu, Zhibo Zhu, Chaoyi Ma, Hong Qian, Xingyu Lu, Yangwenhui Zhang, Xiaobo Qin, Binjie Fei, Jun Zhou, Aimin Zhou
2024 — conf
Counterfactual Data Augmentation for Debiased Coupon Recommendations Based on Potential Knowledge.
WWW (Companion Volume)
Junpeng Fang, Gongduo Zhang, Qing Cui, Lihong Gu, Longfei Li, Jinjie Gu, Jun Zhou
2024 J jnl
Description-Enhanced Label Embedding Contrastive Learning for Text Classification.
IEEE Trans. Neural Networks Learn. Syst.
Kun Zhang, Le Wu, Guangyi Lv, Enhong Chen, Shulan Ruan, Jing Liu, Zhiqiang Zhang, Jun Zhou, Meng Wang
2024 — conf
Distributed Meta-learning for Large-Scale Multi-institution Credit Default Risk Prediction.
DASFAA (7)
Yue Zhang, Xinxing Yang, Feng Zhu, Longfei Li, Linbo Jiang, Jun Zhou
2024 A conf
Domain Level Interpretability: Interpreting Black-box Model with Domain-specific Embedding.
WSDM
Ya-Lin Zhang, Caizhi Tang, Lu Yu, Jun Zhou, Longfei Li, Qing Cui, Fangfang Fan, Linbo Jiang, Xiaosong Zhao
2024 A* conf
EasyTPP: Towards Open Benchmarking Temporal Point Processes.
ICLR
Siqiao Xue, Xiaoming Shi, Zhixuan Chu, Yan Wang, Hongyan Hao, Fan Zhou, Caigao Jiang, Chen Pan, James Y. Zhang, Qingsong Wen, Jun Zhou, Hongyuan Mei
2024 A* conf
Efficient Model Stealing Defense with Noise Transition Matrix.
CVPR
Dong-Dong Wu, Chilin Fu, Weichang Wu, Wenwen Xia, Xiaolu Zhang, Jun Zhou, Min-Ling Zhang
2024 — conf
Empowering Sequential Recommendation from Collaborative Signals and Semantic Relatedness.
DASFAA (3)
Mingyue Cheng, Hao Zhang, Qi Liu, Fajie Yuan, Zhi Li, Zhenya Huang, Enhong Chen, Jun Zhou, Longfei Li
2024 J jnl
Empowering Sequential Recommendation from Collaborative Signals and Semantic Relatedness.
CoRR
Mingyue Cheng, Hao Zhang, Qi Liu, Fajie Yuan, Zhi Li, Zhenya Huang, Enhong Chen, Jun Zhou, Longfei Li
2024 Misc conf
Enhancing Event Sequence Modeling with Contrastive Relational Inference.
ICASSP
Yan Wang, Zhixuan Chu, Tao Zhou, Caigao Jiang, Hongyan Hao, Minjie Zhu, Xindong Cai, Qing Cui, Longfei Li, James Y. Zhang, Siqiao Xue, Jun Zhou
2024 — conf
Enhancing Sequential Recommendation via LLM-based Semantic Embedding Learning.
WWW (Companion Volume)
Jun Hu, Wenwen Xia, Xiaolu Zhang, Chilin Fu, Weichang Wu, Zhaoxin Huan, Ang Li, Zuoli Tang, Jun Zhou
2024 A* conf
Enhancing Sequential Recommenders with Augmented Knowledge from Aligned Large Language Models.
SIGIR
Yankun Ren, Zhongde Chen, Xinxing Yang, Longfei Li, Cong Jiang, Lei Cheng, Bo Zhang, Linjian Mo, Jun Zhou
2024 A* conf
Exploring Multi-Scenario Multi-Modal CTR Prediction with a Large Scale Dataset.
SIGIR
Zhaoxin Huan, Ke Ding, Ang Li, Xiaolu Zhang, Xu Min, Yong He, Liang Zhang, Jun Zhou, Linjian Mo, Jinjie Gu, Zhongyi Liu, Wenliang Zhong, Guannan Zhang, Chenliang Li, Fajie Yuan
2024 A conf
Factor Model-Based Large Covariance Estimation from Streaming Data Using a Knowledge-Based Sketch Matrix.
CIKM
Xiao Tan, Zhaoyang Wang, Hao Qian, Jun Zhou, Peibo Duan, Dian Shen, Meng Wang, Beilun Wang
2024 J jnl
Finite Element Method on locally refined composite meshes for Dirichlet fractional Laplacian.
J. Comput. Sci.
Jun Zhou, Hongbin Chen
2024 J jnl
G-Meta: Distributed Meta Learning in GPU Clusters for Large-Scale Recommender Systems.
CoRR
Youshao Xiao, Shangchun Zhao, Zhenglei Zhou, Zhaoxin Huan, Lin Ju, Xiaolu Zhang, Lin Wang, Jun Zhou
2024 A* conf
GATS: Generative Audience Targeting System for Online Advertising.
SIGIR
Cong Jiang, Zhongde Chen, Bo Zhang, Yankun Ren, Xin Dong, Lei Cheng, Xinxing Yang, Longfei Li, Jun Zhou, Linjian Mo
2024 J jnl
GLISP: A Scalable GNN Learning System by Exploiting Inherent Structural Properties of Graphs.
CoRR
Zhongshu Zhu, Bin Jing, Xiaopei Wan, Zhizhen Liu, Lei Liang, Jun Zhou
2024 A* conf
GMP-AR: Granularity Message Passing and Adaptive Reconciliation for Temporal Hierarchy Forecasting.
AAAI
Fan Zhou, Chen Pan, Lintao Ma, Yu Liu, Siqiao Xue, James Y. Zhang, Jun Zhou, Hongyuan Mei, Weitao Lin, Zi Zhuang, Wenxin Ning, Yunhua Hu
2024 J jnl
GMP-AR: Granularity Message Passing and Adaptive Reconciliation for Temporal Hierarchy Forecasting.
CoRR
Fan Zhou, Chen Pan, Lintao Ma, Yu Liu, James Y. Zhang, Jun Zhou, Hongyuan Mei, Weitao Lin, Zi Zhuang, Wenxin Ning, Yunhua Hu, Siqiao Xue
2024 — conf
Granola: Graph Neural Network Tackling Tabular Data for Online Loan Default Prediction.
DASFAA (7)
Borui Ye, Shuo Yang, Meiqi Zhu, Binbin Hu, Daixin Wang, Zhiqiang Zhang, Youqiang He, Zhiyang Hu, Huimei He, Jun Zhou
2024 J jnl
Graph Disentangle Causal Model: Enhancing Causal Inference in Networked Observational Data.
CoRR
Binbin Hu, Zhicheng An, Zhengwei Wu, Ke Tu, Ziqi Liu, Zhiqiang Zhang, Jun Zhou, Yufei Feng, Jiawei Chen
2024 J jnl
Graph Neural Network with Two Uplift Estimators for Label-Scarcity Individual Uplift Modeling.
CoRR
Dingyuan Zhu, Daixin Wang, Zhiqiang Zhang, Kun Kuang, Yan Zhang, Yulin Kang, Jun Zhou
2024 J jnl
Hyperbolic Graph Learning for Social Recommendation.
IEEE Trans. Knowl. Data Eng.
Yonghui Yang, Le Wu, Kun Zhang, Richang Hong, Hailin Zhou, Zhiqiang Zhang, Jun Zhou, Meng Wang
2024 J jnl
Integration of large language models and federated learning.
Patterns
Chaochao Chen, Xiaohua Feng, Yuyuan Li, Lingjuan Lyu, Jun Zhou, Xiaolin Zheng, Jianwei Yin
2024 J jnl
Interpretable Catastrophic Forgetting of Large Language Model Fine-tuning via Instruction Vector.
CoRR
Gangwei Jiang, Caigao Jiang, Zhaoyi Li, Siqiao Xue, Jun Zhou, Linqi Song, Defu Lian, Ying Wei
2024 A* conf
Invariant Graph Learning for Causal Effect Estimation.
WWW
Yongduo Sui, Caizhi Tang, Zhixuan Chu, Junfeng Fang, Yuan Gao, Qing Cui, Longfei Li, Jun Zhou, Xiang Wang
2024 J jnl
KAG: Boosting LLMs in Professional Domains via Knowledge Augmented Generation.
CoRR
Lei Liang, Mengshu Sun, Zhengke Gui, Zhongshu Zhu, Zhouyu Jiang, Ling Zhong, Yuan Qu, Peilong Zhao, Zhongpu Bo, Jin Yang, Huaidong Xiong, Lin Yuan, Jun Xu, Zaoyang Wang, Zhiqiang Zhang, Wen Zhang, Huajun Chen, Wenguang Chen, Jun Zhou
2024 J jnl
KGFabric: A Scalable Knowledge Graph Warehouse for Enterprise Data Interconnection.
Proc. VLDB Endow.
Peng Yi, Lei Liang, Da Zhang, Yong Chen, Jinye Zhu, Xiangyu Liu, Kun Tang, Jialin Chen, Hao Lin, Leijie Qiu, Jun Zhou
2024 A* conf
Keypoint-based Progressive Chain-of-Thought Distillation for LLMs.
ICML
Kaituo Feng, Changsheng Li, Xiaolu Zhang, Jun Zhou, Ye Yuan, Guoren Wang
2024 J jnl
Keypoint-based Progressive Chain-of-Thought Distillation for LLMs.
CoRR
Kaituo Feng, Changsheng Li, Xiaolu Zhang, Jun Zhou, Ye Yuan, Guoren Wang
2024 — conf
Knowledge-augmented Financial Market Analysis and Report Generation.
EMNLP (Industry Track)
Yuemin Chen, Feifan Wu, Jingwei Wang, Hao Qian, Ziqi Liu, Zhiqiang Zhang, Jun Zhou, Meng Wang
2024 A* conf
LASCA: A Large-Scale Stable Customer Segmentation Approach to Credit Risk Assessment.
KDD
Yongfeng Gu, Yupeng Wu, Huakang Lu, Xingyu Lu, Hong Qian, Jun Zhou, Aimin Zhou
2024 J jnl
LLMOPT: Learning to Define and Solve General Optimization Problems from Scratch.
CoRR
Caigao Jiang, Xiang Shu, Hong Qian, Xingyu Lu, Jun Zhou, Aimin Zhou, Yang Yu
2024 A* conf
LLMRG: Improving Recommendations through Large Language Model Reasoning Graphs.
AAAI
Yan Wang, Zhixuan Chu, Xin Ouyang, Simeng Wang, Hongyan Hao, Yue Shen, Jinjie Gu, Siqiao Xue, James Zhang, Qing Cui, Longfei Li, Jun Zhou, Sheng Li
2024 J jnl
Learning Causal Transition Matrix for Instance-dependent Label Noise.
CoRR
Jiahui Li, Tai-Wei Chang, Kun Kuang, Ximing Li, Long Chen, Jun Zhou
2024 — conf
Learning to Plan for Retrieval-Augmented Large Language Models from Knowledge Graphs.
EMNLP (Findings)
Junjie Wang, Mingyang Chen, Binbin Hu, Dan Yang, Ziqi Liu, Yue Shen, Peng Wei, Zhiqiang Zhang, Jinjie Gu, Jun Zhou, Jeff Z. Pan, Wen Zhang, Huajun Chen
2024 J jnl
Learning to Plan for Retrieval-Augmented Large Language Models from Knowledge Graphs.
CoRR
Junjie Wang, Mingyang Chen, Binbin Hu, Dan Yang, Ziqi Liu, Yue Shen, Peng Wei, Zhiqiang Zhang, Jinjie Gu, Jun Zhou, Jeff Z. Pan, Wen Zhang, Huajun Chen
2024 A* conf
Leave No One Behind: Online Self-Supervised Self-Distillation for Sequential Recommendation.
WWW
Shaowei Wei, Zhengwei Wu, Xin Li, Qintong Wu, Zhiqiang Zhang, Jun Zhou, Lihong Gu, Jinjie Gu
2024 J jnl
Leave No One Behind: Online Self-Supervised Self-Distillation for Sequential Recommendation.
CoRR
Shaowei Wei, Zhengwei Wu, Xin Li, Qintong Wu, Zhiqiang Zhang, Jun Zhou, Lihong Gu, Jinjie Gu
2024 A* conf
MDGNN: Multi-Relational Dynamic Graph Neural Network for Comprehensive and Dynamic Stock Investment Prediction.
AAAI
Hao Qian, Hongting Zhou, Qian Zhao, Hao Chen, Hongxiang Yao, Jingwei Wang, Ziqi Liu, Fei Yu, Zhiqiang Zhang, Jun Zhou
2024 J jnl
MDGNN: Multi-Relational Dynamic Graph Neural Network for Comprehensive and Dynamic Stock Investment Prediction.
CoRR
Hao Qian, Hongting Zhou, Qian Zhao, Hao Chen, Hongxiang Yao, Jingwei Wang, Ziqi Liu, Fei Yu, Zhiqiang Zhang, Jun Zhou
2024 B conf
MIBR: Bridging Domains through Diverse Interests for Cross-Domain Sequential Recommendation.
IEEE Big Data
Chengzhe Zhang, Xu Min, Changsheng Li, Xiaolu Zhang, Weichang Wu, Jun Zhou, Ye Yuan, Guoren Wang
2024 J jnl
Making Large Vision Language Models to be Good Few-shot Learners.
CoRR
Fan Liu, Wenwen Cai, Jian Huo, Chuanyi Zhang, Delong Chen, Jun Zhou
2024 — conf
Modeling Treatment Effect with Cross-Domain Data.
PAKDD (1)
Bin Han, Ya-Lin Zhang, Lu Yu, Biying Chen, Longfei Li, Jun Zhou
2024 J jnl
Multi-Task Decouple Learning With Hierarchical Attentive Point Process.
IEEE Trans. Knowl. Data Eng.
Weichang Wu, Xiaolu Zhang, Shiwan Zhao, Chilin Fu, Jun Zhou
2024 A conf
Multi-view Temporal Knowledge Graph Reasoning.
CIKM
Fuwei Zhang, Zhao Zhang, Fuzhen Zhuang, Zhiqiang Zhang, Jun Zhou, Deqing Wang
2024 A conf
Multiscale Representation Enhanced Temporal Flow Fusion Model for Long-Term Workload Forecasting.
CIKM
Shiyu Wang, Zhixuan Chu, Yinbo Sun, Yu Liu, Yuliang Guo, Yang Chen, Huiyang Jian, Lintao Ma, Xingyu Lu, Jun Zhou
2024 J jnl
Multiscale Representation Enhanced Temporal Flow Fusion Model for Long-Term Workload Forecasting.
CoRR
Shiyu Wang, Zhixuan Chu, Yinbo Sun, Yu Liu, Yuliang Guo, Yang Chen, Huiyang Jian, Lintao Ma, Xingyu Lu, Jun Zhou
2024 A conf
Not All Negatives Are Worth Attending to: Meta-Bootstrapping Negative Sampling Framework for Link Prediction.
WSDM
Yakun Wang, Binbin Hu, Shuo Yang, Meiqi Zhu, Zhiqiang Zhang, Qiyang Zhang, Jun Zhou, Guo Ye, Huimei He
2024 — conf
OneEdit: A Neural-Symbolic Collaboratively Knowledge Editing System.
VLDB Workshops
Ningyu Zhang, Zekun Xi, Yujie Luo, Peng Wang, Bozhong Tian, Yunzhi Yao, Jintian Zhang, Shumin Deng, Mengshu Sun, Lei Liang, Zhiqiang Zhang, Xiaowei Zhu, Jun Zhou, Huajun Chen
2024 J jnl
OneEdit: A Neural-Symbolic Collaboratively Knowledge Editing System.
CoRR
Ningyu Zhang, Zekun Xi, Yujie Luo, Peng Wang, Bozhong Tian, Yunzhi Yao, Jintian Zhang, Shumin Deng, Mengshu Sun, Lei Liang, Zhiqiang Zhang, Xiaowei Zhu, Jun Zhou, Huajun Chen
2024 — conf
OneGen: Efficient One-Pass Unified Generation and Retrieval for LLMs.
EMNLP (Findings)
Jintian Zhang, Cheng Peng, Mengshu Sun, Xiang Chen, Lei Liang, Zhiqiang Zhang, Jun Zhou, Huajun Chen, Ningyu Zhang
2024 J jnl
OneGen: Efficient One-Pass Unified Generation and Retrieval for LLMs.
CoRR
Jintian Zhang, Cheng Peng, Mengshu Sun, Xiang Chen, Lei Liang, Zhiqiang Zhang, Jun Zhou, Huajun Chen, Ningyu Zhang
2024 J jnl
OneKE: A Dockerized Schema-Guided LLM Agent-based Knowledge Extraction System.
CoRR
Yujie Luo, Xiangyuan Ru, Kangwei Liu, Lin Yuan, Mengshu Sun, Ningyu Zhang, Lei Liang, Zhiqiang Zhang, Jun Zhou, Lanning Wei, Da Zheng, Haofen Wang, Huajun Chen
2024 A* conf
Optimizing Language Models with Fair and Stable Reward Composition in Reinforcement Learning.
EMNLP
Jiahui Li, Hanlin Zhang, Fengda Zhang, Tai-Wei Chang, Kun Kuang, Long Chen, Jun Zhou
2024 A conf
PEACE: Prototype lEarning Augmented transferable framework for Cross-domain rEcommendation.
WSDM
Chunjing Gan, Bo Huang, Binbin Hu, Jian Ma, Zhiqiang Zhang, Jun Zhou, Guannan Zhang, Wenliang Zhong
2024 J jnl
Personalized Binomial DAGs Learning with Network Structured Covariates.
CoRR
Boxin Zhao, Weishi Wang, Dingyuan Zhu, Ziqi Liu, Dong Wang, Zhiqiang Zhang, Jun Zhou, Mladen Kolar
2024 J jnl
Prompting DirectSAM for Semantic Contour Extraction in Remote Sensing Images.
CoRR
Shiyu Miao, Delong Chen, Fan Liu, Chuanyi Zhang, Yanhui Gu, Shengjie Guo, Jun Zhou
2024 — conf
QoMRC: Query-oriented Machine Reading Comprehension Framework for Aspect Sentiment Triplet Extraction.
DASFAA (5)
Kehang Wang, Ye Liu, Kai Zhang, Qi Liu, Yankun Ren, Xinxing Yang, Longfei Li, Jun Zhou
2024 A conf
ReLand: Integrating Large Language Models' Insights into Industrial Recommenders via a Controllable Reasoning Pool.
RecSys
Changxin Tian, Binbin Hu, Chunjing Gan, Haoyu Chen, Zhuo Zhang, Li Yu, Ziqi Liu, Zhiqiang Zhang, Jun Zhou, Jiawei Chen
2024 J jnl
RemoteTrimmer: Adaptive Structural Pruning for Remote Sensing Image Classification.
CoRR
Guangwenjie Zou, Liang Yao, Fan Liu, Chuanyi Zhang, Xin Li, Ning Chen, Shengxiang Xu, Jun Zhou
2024 A* conf
Rethinking Memory and Communication Costs for Efficient Data Parallel Training of Large Language Models.
NeurIPS
Hanxiao Zhang, Lin Ju, Chan Wu, Jinjing Huang, Youshao Xiao, Zhenglei Zhou, Zhiming Fan, Zhaoxin Huan, Siyuan Li, Fanzhuang Meng, Lei Liang, Xiaolu Zhang, Jun Zhou
2024 J jnl
Scale-Invariant Feature Disentanglement via Adversarial Learning for UAV-based Object Detection.
CoRR
Fan Liu, Liang Yao, Chuanyi Zhang, Ting Wu, Xinlei Zhang, Xiruo Jiang, Jun Zhou
2024 A* conf
Self-cognitive Denoising in the Presence of Multiple Noisy Label Sources.
ICML
Yi-Xuan Sun, Ya-Lin Zhang, Bin Han, Longfei Li, Jun Zhou
2024 J jnl
Similarity is Not All You Need: Endowing Retrieval Augmented Generation with Multi Layered Thoughts.
CoRR
Chunjing Gan, Dan Yang, Binbin Hu, Hanxiao Zhang, Siyuan Li, Ziqi Liu, Yue Shen, Lin Ju, Zhiqiang Zhang, Jinjie Gu, Lei Liang, Jun Zhou
2024 J jnl
Survey and open problems in privacy-preserving knowledge graph: merging, query, representation, completion, and applications.
Int. J. Mach. Learn. Cybern.
Chao-Chao Chen, Fei Zheng, Jamie Cui, Yuwei Cao, Guanfeng Liu, Jia Wu, Jun Zhou
2024 A conf
TEXT CAN BE FAIR: Mitigating Popularity Bias with PLMs by Learning Relative Preference.
CIKM
Zuoli Tang, Zhaoxin Huan, Zihao Li, Shirui Hu, Xiaolu Zhang, Jun Zhou, Lixin Zou, Chenliang Li
2024 A* conf
TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting.
ICLR
Shiyu Wang, Haixu Wu, Xiaoming Shi, Tengge Hu, Huakun Luo, Lintao Ma, James Y. Zhang, Jun Zhou
2024 J jnl
TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting.
CoRR
Shiyu Wang, Haixu Wu, Xiaoming Shi, Tengge Hu, Huakun Luo, Lintao Ma, James Y. Zhang, Jun Zhou
2024 J jnl
Toward Enhanced Robustness in Unsupervised Graph Representation Learning: A Graph Information Bottleneck Perspective.
IEEE Trans. Knowl. Data Eng.
Jihong Wang, Minnan Luo, Jundong Li, Ziqi Liu, Jun Zhou, Qinghua Zheng
2024 J jnl
Towards Practical Backdoor Attacks on Federated Learning Systems.
IEEE Trans. Dependable Secur. Comput.
Chenghui Shi, Shouling Ji, Xudong Pan, Xuhong Zhang, Mi Zhang, Min Yang, Jun Zhou, Jianwei Yin, Ting Wang
2024 A* conf
Unifying Bayesian Flow Networks and Diffusion Models through Stochastic Differential Equations.
ICML
Kaiwen Xue, Yuhao Zhou, Shen Nie, Xu Min, Xiaolu Zhang, Jun Zhou, Chongxuan Li
2024 J jnl
Unifying Bayesian Flow Networks and Diffusion Models through Stochastic Differential Equations.
CoRR
Kaiwen Xue, Yuhao Zhou, Shen Nie, Xu Min, Xiaolu Zhang, Jun Zhou, Chongxuan Li
2024 J jnl
Your decision path does matter in pre-training industrial recommenders with multi-source behaviors.
CoRR
Chunjing Gan, Binbin Hu, Bo Huang, Ziqi Liu, Jian Ma, Zhiqiang Zhang, Wenliang Zhong, Jun Zhou
2024 A* conf
π-Light: Programmatic Interpretable Reinforcement Learning for Resource-Limited Traffic Signal Control.
AAAI
Yin Gu, Kai Zhang, Qi Liu, Weibo Gao, Longfei Li, Jun Zhou
2023 A conf
A Framework for Detecting Frauds from Extremely Few Labels.
WSDM
Ya-Lin Zhang, Yi-Xuan Sun, Fangfang Fan, Meng Li, Yeyu Zhao, Wei Wang, Longfei Li, Jun Zhou, Jinghua Feng
2023 A* conf
A Practical Online Allocation Framework at Industry-scale in Constrained Recommendation.
SIGIR
Daohong Jian, Yang Bao, Jun Zhou, Hua Wu
2023 — conf
A Practical Rule Learning Framework for Risk Management.
WWW (Companion Volume)
Jun Zhou, Meng Li, Lu Yu, Longfei Li, Fei Wu
2023 A* conf
A Rule-based Decision System for Financial Applications.
ICDE
Meng Li, Jun Zhou, Lu Yu, Xiaoguang Huang, Yongfeng Gu, Yi Ding, Hao Ding, Longfei Li
2023 — conf
A Scalable Social Recommendation Framework with Decoupled Graph Neural Network.
DASFAA (4)
Ke Tu, Zhengwei Wu, Binbin Hu, Zhiqiang Zhang, Peng Cui, Xiaolong Li, Jun Zhou
2023 J jnl
A Unified Framework for Cross-Domain and Cross-System Recommendations.
IEEE Trans. Knowl. Data Eng.
Feng Zhu, Yan Wang, Jun Zhou, Chaochao Chen, Longfei Li, Guanfeng Liu
2023 A* conf
ALT: An Automatic System for Long Tail Scenario Modeling.
ICDE
Ya-Lin Zhang, Jun Zhou, Yankun Ren, Yue Zhang, Xinxing Yang, Meng Li, Qitao Shi, Longfei Li
2023 J jnl
ALT: An Automatic System for Long Tail Scenario Modeling.
CoRR
Ya-Lin Zhang, Jun Zhou, Yankun Ren, Yue Zhang, Xinxing Yang, Meng Li, Qitao Shi, Longfei Li
2023 A* conf
Alleviating Matching Bias in Marketing Recommendations.
SIGIR
Junpeng Fang, Qing Cui, Gongduo Zhang, Caizhi Tang, Lihong Gu, Longfei Li, Jinjie Gu, Jun Zhou, Fei Wu
2023 J jnl
An Adaptive Placement and Parallelism Framework for Accelerating RLHF Training.
CoRR
Youshao Xiao, Weichang Wu, Zhenglei Zhou, Fagui Mao, Shangchun Zhao, Lin Ju, Lei Liang, Xiaolu Zhang, Jun Zhou
2023 J jnl
AntM
CoRR
Zhaoxin Huan, Ke Ding, Ang Li, Xiaolu Zhang, Xu Min, Yong He, Liang Zhang, Jun Zhou, Linjian Mo, Jinjie Gu, Zhongyi Liu, Wenliang Zhong, Guannan Zhang
2023 A conf
AntTS: A Toolkit for Time Series Forecasting in Industrial Scenarios.
WSDM
Jianping Wei, Zhibo Zhu, Ziqi Liu, Zhiqiang Zhang, Jun Zhou
2023 — conf
AntTune: An Efficient Distributed Hyperparameter Optimization System for Large-Scale Data.
DASFAA (4)
Jun Zhou, Qitao Shi, Yi Ding, Lin Wang, Longfei Li, Feng Zhu
2023 — conf
BCAD: An Interpretable Anomaly Transaction Detection System Based on Behavior Consistency.
ECML/PKDD (6)
Jun Hu, Xu Min, Xiaolu Zhang, Chilin Fu, Weichang Wu, Jun Zhou
2023 J jnl
Bi-objective evolutionary Bayesian network structure learning via skeleton constraint.
Frontiers Comput. Sci.
Ting Wu, Hong Qian, Ziqi Liu, Jun Zhou, Aimin Zhou
2023 — conf
Boosting Adaptive Graph Augmented MLPs via Customized Knowledge Distillation.
ECML/PKDD (3)
Shaowei Wei, Zhengwei Wu, Zhiqiang Zhang, Jun Zhou
2023 A* conf
COUPA: An Industrial Recommender System for Online to Offline Service Platforms.
SIGIR
Sicong Xie, Binbin Hu, Fengze Li, Ziqi Liu, Zhiqiang Zhang, Wenliang Zhong, Jun Zhou
2023 J jnl
COUPA: An Industrial Recommender System for Online to Offline Service Platforms.
CoRR
Sicong Xie, Binbin Hu, Fengze Li, Ziqi Liu, Zhiqiang Zhang, Wenliang Zhong, Jun Zhou
2023 A* conf
Commonsense Knowledge Graph towards Super APP and Its Applications in Alipay.
KDD
Xiaoling Zang, Binbin Hu, Jun Chu, Zhiqiang Zhang, Guannan Zhang, Jun Zhou, Wenliang Zhong
2023 A conf
Continual Learning in Predictive Autoscaling.
CIKM
Hongyan Hao, Zhixuan Chu, Shiyi Zhu, Gangwei Jiang, Yan Wang, Caigao Jiang, James Y. Zhang, Wei Jiang, Siqiao Xue, Jun Zhou
2023 J jnl
Continual Learning in Predictive Autoscaling.
CoRR
Hongyan Hao, Zhixuan Chu, Shiyi Zhu, Gangwei Jiang, Yan Wang, Caigao Jiang, James Zhang, Wei Jiang, Siqiao Xue, Jun Zhou
2023 A* conf
DCMT: A Direct Entire-Space Causal Multi-Task Framework for Post-Click Conversion Estimation.
ICDE
Feng Zhu, Mingjie Zhong, Xinxing Yang, Longfei Li, Lu Yu, Tiehua Zhang, Jun Zhou, Chaochao Chen, Fei Wu, Guanfeng Liu, Yan Wang
2023 J jnl
DCMT: A Direct Entire-Space Causal Multi-Task Framework for Post-Click Conversion Estimation.
CoRR
Feng Zhu, Mingjie Zhong, Xinxing Yang, Longfei Li, Lu Yu, Tiehua Zhang, Jun Zhou, Chaochao Chen, Fei Wu, Guanfeng Liu, Yan Wang
2023 — conf
DGBCT: A Scalable Distributed Gradient Boosting Causal Tree at Alipay.
WWW (Companion Volume)
Jun Zhou, Caizhi Tang, Qing Cui, Yi Ding, Longfei Li, Fei Wu
2023 J jnl
Data-Centric Financial Large Language Models.
CoRR
Zhixuan Chu, Huaiyu Guo, Xinyuan Zhou, Yijia Wang, Fei Yu, Hong Chen, Wanqing Xu, Xin Lu, Qing Cui, Longfei Li, Jun Zhou, Sheng Li
2023 J jnl
Deep Tabular Data Modeling With Dual-Route Structure-Adaptive Graph Networks.
IEEE Trans. Knowl. Data Eng.
Qinghua Zheng, Zhen Peng, Zhuohang Dang, Linchao Zhu, Ziqi Liu, Zhiqiang Zhang, Jun Zhou
2023 J jnl
Description-Enhanced Label Embedding Contrastive Learning for Text Classification.
CoRR
Kun Zhang, Le Wu, Guangyi Lv, Enhong Chen, Shulan Ruan, Jing Liu, Zhiqiang Zhang, Jun Zhou, Meng Wang
2023 A* conf
Difference-in-Differences Meets Tree-based Methods: Heterogeneous Treatment Effects Estimation with Unmeasured Confounding.
ICML
Caizhi Tang, Huiyuan Wang, Xinyu Li, Qing Cui, Longfei Li, Jun Zhou
2023 A conf
Disentangled Interest importance aware Knowledge Graph Neural Network for Fund Recommendation.
CIKM
Ke Tu, Wei Qu, Zhengwei Wu, Zhiqiang Zhang, Zhongyi Liu, Yiming Zhao, Le Wu, Jun Zhou, Guannan Zhang
2023 A conf
DistriBayes: A Distributed Platform for Learning, Inference and Attribution on Large Scale Bayesian Network.
WSDM
Yi Ding, Jun Zhou, Qing Cui, Lin Wang, Mengqi Zhang, Yang Dong
2023 J jnl
EATN: An Efficient Adaptive Transfer Network for Aspect-Level Sentiment Analysis.
IEEE Trans. Knowl. Data Eng.
Kai Zhang, Qi Liu, Hao Qian, Biao Xiang, Qing Cui, Jun Zhou, Enhong Chen
2023 J jnl
EasyTPP: Towards Open Benchmarking the Temporal Point Processes.
CoRR
Siqiao Xue, Xiaoming Shi, Zhixuan Chu, Yan Wang, Fan Zhou, Hongyan Hao, Caigao Jiang, Chen Pan, Yi Xu, James Y. Zhang, Qingsong Wen, Jun Zhou, Hongyuan Mei
2023 A conf
ElasticDL: A Kubernetes-native Deep Learning Framework with Fault-tolerance and Elastic Scheduling.
WSDM
Jun Zhou, Ke Zhang, Feng Zhu, Qitao Shi, Wenjing Fang, Lin Wang, Yi Wang
2023 — conf
Enhancing Asynchronous Time Series Forecasting with Contrastive Relational Inference.
ICDM (Workshops)
Yan Wang, Zhixuan Chu, Tao Zhou, Caigao Jiang, Hongyan Hao, Minjie Zhu, Xindong Cai, Qing Cui, Longfei Li, James Y. Zhang, Siqiao Xue, Jun Zhou
2023 J jnl
Enhancing Asynchronous Time Series Forecasting with Contrastive Relational Inference.
CoRR
Yan Wang, Zhixuan Chu, Tao Zhou, Caigao Jiang, Hongyan Hao, Minjie Zhu, Xindong Cai, Qing Cui, Longfei Li, James Y. Zhang, Siqiao Xue, Jun Zhou
2023 J jnl
Enhancing Recommender Systems with Large Language Model Reasoning Graphs.
CoRR
Yan Wang, Zhixuan Chu, Xin Ouyang, Simeng Wang, Hongyan Hao, Yue Shen, Jinjie Gu, Siqiao Xue, James Y. Zhang, Qing Cui, Longfei Li, Jun Zhou, Sheng Li
2023 J jnl
Exploring the combination of self and mutual teaching for tabular-data-related semi-supervised regression.
Expert Syst. Appl.
Ya-Lin Zhang, Jun Zhou, Qitao Shi, Longfei Li
2023 A* conf
FAST: a Fused and Accurate Shrinkage Tree for Heterogeneous Treatment Effects Estimation.
NeurIPS
Jia Gu, Caizhi Tang, Han Yan, Qing Cui, Longfei Li, Jun Zhou
2023 A conf
FINRule: Feature Interactive Neural Rule Learning.
CIKM
Lu Yu, Meng Li, Ya-Lin Zhang, Longfei Li, Jun Zhou
2023 J jnl
Federated Large Language Model: A Position Paper.
CoRR
Chaochao Chen, Xiaohua Feng, Jun Zhou, Jianwei Yin, Xiaolin Zheng
2023 A* conf
Financial Default Prediction via Motif-preserving Graph Neural Network with Curriculum Learning.
KDD
Daixin Wang, Zhiqiang Zhang, Yeyu Zhao, Kai Huang, Yulin Kang, Jun Zhou
2023 J jnl
Fraud-Agents Detection in Online Microfinance: A Large-Scale Empirical Study.
IEEE Trans. Dependable Secur. Comput.
Yiming Wu, Zhiyuan Xie, Shouling Ji, Zhenguang Liu, Xuhong Zhang, Changting Lin, Shuiguang Deng, Jun Zhou, Ting Wang, Raheem Beyah
2023 A conf
G-Meta: Distributed Meta Learning in GPU Clusters for Large-Scale Recommender Systems.
CIKM
Youshao Xiao, Shangchun Zhao, Zhenglei Zhou, Zhaoxin Huan, Lin Ju, Xiaolu Zhang, Lin Wang, Jun Zhou
2023 A* conf
GARCIA: Powering Representations of Long-tail Query with Multi-granularity Contrastive Learning.
ICDE
Weifan Wang, Binbin Hu, Zhicheng Peng, Mingjie Zhong, Zhiqiang Zhang, Zhongyi Liu, Guannan Zhang, Jun Zhou
2023 J jnl
GARCIA: Powering Representations of Long-tail Query with Multi-granularity Contrastive Learning.
CoRR
Weifan Wang, Binbin Hu, Zhicheng Peng, Mingjie Zhong, Zhiqiang Zhang, Zhongyi Liu, Guannan Zhang, Jun Zhou
2023 J jnl
GINT: A Generative Interpretability method via perturbation in the latent space.
Expert Syst. Appl.
Caizhi Tang, Qing Cui, Longfei Li, Jun Zhou
2023 J jnl
Generative Contrastive Graph Learning for Recommendation.
CoRR
Yonghui Yang, Zhengwei Wu, Le Wu, Kun Zhang, Richang Hong, Zhiqiang Zhang, Jun Zhou, Meng Wang
2023 A* conf
Generative-Contrastive Graph Learning for Recommendation.
SIGIR
Yonghui Yang, Zhengwei Wu, Le Wu, Kun Zhang, Richang Hong, Zhiqiang Zhang, Jun Zhou, Meng Wang
2023 — conf
Global-Aware Model-Free Self-distillation for Recommendation System.
DASFAA (4)
Ang Li, Jian Hu, Wei Lu, Ke Ding, Xiaolu Zhang, Jun Zhou, Yong He, Liang Zhang, Lihong Gu
2023 A* conf
Graph Neural Network with Two Uplift Estimators for Label-Scarcity Individual Uplift Modeling.
WWW
Dingyuan Zhu, Daixin Wang, Zhiqiang Zhang, Kun Kuang, Yan Zhang, Yulin Kang, Jun Zhou
2023 J jnl
GraphTune: An Efficient Dependency-Aware Substrate to Alleviate Irregularity in Concurrent Graph Processing.
ACM Trans. Archit. Code Optim.
Jin Zhao, Yu Zhang, Ligang He, Qikun Li, Xiang Zhang, Xinyu Jiang, Hui Yu, Xiaofei Liao, Hai Jin, Lin Gu, Haikun Liu, Bingsheng He, Ji Zhang, Xianzheng Song, Lin Wang, Jun Zhou
2023 A* conf
GreenSeq: Automatic Design of Green Networks for Sequential Recommendation Systems.
SIGIR
Yankun Ren, Xinxing Yang, Xingyu Lu, Longfei Li, Jun Zhou, Jinjie Gu, Guannan Zhang
2023 A* conf
Improving Recommendation Fairness via Data Augmentation.
WWW
Lei Chen, Le Wu, Kun Zhang, Richang Hong, Defu Lian, Zhiqiang Zhang, Jun Zhou, Meng Wang
2023 J jnl
Improving Recommendation Fairness via Data Augmentation.
CoRR
Lei Chen, Le Wu, Kun Zhang, Richang Hong, Defu Lian, Zhiqiang Zhang, Jun Zhou, Meng Wang
2023 A* conf
InferTurbo: A Scalable System for Boosting Full-graph Inference of Graph Neural Network over Huge Graphs.
ICDE
Dalong Zhang, Xianzheng Song, Zhiyang Hu, Yang Li, Miao Tao, Binbin Hu, Lin Wang, Zhiqiang Zhang, Jun Zhou
2023 J jnl
InferTurbo: A Scalable System for Boosting Full-graph Inference of Graph Neural Network over Huge Graphs.
CoRR
Dalong Zhang, Xianzheng Song, Zhiyang Hu, Yang Li, Miao Tao, Binbin Hu, Lin Wang, Zhiqiang Zhang, Jun Zhou
2023 A* conf
Keep Skills in Mind: Understanding and Implementing Skills in Commonsense Question Answering.
IJCAI
Meikai Bao, Qi Liu, Kai Zhang, Ye Liu, Linan Yue, Longfei Li, Jun Zhou
2023 A* conf
Language Models Can Improve Event Prediction by Few-Shot Abductive Reasoning.
NeurIPS
Xiaoming Shi, Siqiao Xue, Kangrui Wang, Fan Zhou, James Y. Zhang, Jun Zhou, Chenhao Tan, Hongyuan Mei
2023 J jnl
Language Models Can Improve Event Prediction by Few-Shot Abductive Reasoning.
CoRR
Xiaoming Shi, Siqiao Xue, Kangrui Wang, Fan Zhou, James Y. Zhang, Jun Zhou, Chenhao Tan, Hongyuan Mei
2023 — conf
Long-Tail Augmented Graph Contrastive Learning for Recommendation.
ECML/PKDD (4)
Qian Zhao, Zhengwei Wu, Zhiqiang Zhang, Jun Zhou
2023 J jnl
Long-tail Augmented Graph Contrastive Learning for Recommendation.
CoRR
Qian Zhao, Zhengwei Wu, Zhiqiang Zhang, Jun Zhou
2023 A* conf
MDI: A Debiasing Method Combining Unbiased and Biased Data.
SIGIR
Han Zhao, Qing Cui, Xinyu Li, Rongzhou Bao, Longfei Li, Jun Zhou, Zhehao Liu, Jinghua Feng
2023 J jnl
Making Large Language Models Better Knowledge Miners for Online Marketing with Progressive Prompting Augmentation.
CoRR
Chunjing Gan, Dan Yang, Binbin Hu, Ziqi Liu, Yue Shen, Zhiqiang Zhang, Jinjie Gu, Jun Zhou, Guannan Zhang
2023 — conf
Multi-Source Domain Adaptation via Latent Domain Reconstruction.
WWW (Companion Volume)
Jun Zhou, Chilin Fu, Xiaolu Zhang
2023 J jnl
Not All Negatives Are Worth Attending to: Meta-Bootstrapping Negative Sampling Framework for Link Prediction.
CoRR
Yakun Wang, Binbin Hu, Shuo Yang, Meiqi Zhu, Zhiqiang Zhang, Qiyang Zhang, Jun Zhou, Guo Ye, Huimei He
2023 J jnl
One Model for All: Large Language Models are Domain-Agnostic Recommendation Systems.
CoRR
Zuoli Tang, Zhaoxin Huan, Zihao Li, Xiaolu Zhang, Jun Hu, Chilin Fu, Jun Zhou, Chenliang Li
2023 A* conf
Online resource allocation in Markov Chains.
WWW
Jianhao Jia, Hao Li, Kai Liu, Ziqi Liu, Jun Zhou, Nikolai Gravin, Zhihao Gavin Tang
2023 A* conf
PDAS: A Practical Distributed ADMM System for Large-Scale Linear Programming Problems at Alipay.
KDD
Jun Zhou, Yang Bao, Daohong Jian, Hua Wu
2023 J jnl
PEACE: Prototype lEarning Augmented transferable framework for Cross-domain rEcommendation.
CoRR
Chunjing Gan, Bo Huang, Binbin Hu, Jian Ma, Ziqi Liu, Zhiqiang Zhang, Jun Zhou, Guannan Zhang, Wenliang Zhong
2023 A conf
Periodicity May Be Emanative: Hierarchical Contrastive Learning for Sequential Recommendation.
CIKM
Changxin Tian, Binbin Hu, Wayne Xin Zhao, Zhiqiang Zhang, Jun Zhou
2023 A* conf
Prompt-augmented Temporal Point Process for Streaming Event Sequence.
NeurIPS
Siqiao Xue, Yan Wang, Zhixuan Chu, Xiaoming Shi, Caigao Jiang, Hongyan Hao, Gangwei Jiang, Xiaoyun Feng, James Zhang, Jun Zhou
2023 J jnl
Prompt-augmented Temporal Point Process for Streaming Event Sequence.
CoRR
Siqiao Xue, Yan Wang, Zhixuan Chu, Xiaoming Shi, Caigao Jiang, Hongyan Hao, Gangwei Jiang, Xiaoyun Feng, James Y. Zhang, Jun Zhou
2023 J jnl
Rethinking Memory and Communication Cost for Efficient Large Language Model Training.
CoRR
Chan Wu, Hanxiao Zhang, Lin Ju, Jinjing Huang, Youshao Xiao, Zhaoxin Huan, Siyuan Li, Fanzhuang Meng, Lei Liang, Xiaolu Zhang, Jun Zhou
2023 A conf
Robust User Behavioral Sequence Representation via Multi-scale Stochastic Distribution Prediction.
CIKM
Chilin Fu, Weichang Wu, Xiaolu Zhang, Jun Hu, Jing Wang, Jun Zhou
2023 A* conf
SAMD: An Industrial Framework for Heterogeneous Multi-Scenario Recommendation.
KDD
Zhaoxin Huan, Ang Li, Xiaolu Zhang, Xu Min, Jieyu Yang, Yong He, Jun Zhou
2023 J jnl
SQLFlow: An Extensible Toolkit Integrating DB and AI.
J. Mach. Learn. Res.
Jun Zhou, Ke Zhang, Lin Wang, Hua Wu, Yi Wang, Chaochao Chen
2023 A conf
SeqGen: A Sequence Generator via User Side Information for Behavior Sparsity in Recommendation.
CIKM
Xu Min, Xiaolu Zhang, Bin Shen, Shuhan Wang, Yong He, Changsheng Li, Jun Zhou
2023 A* conf
TAML: Time-Aware Meta Learning for Cold-Start Problem in News Recommendation.
SIGIR
Jingyuan Li, Yue Zhang, Xuan Lin, Xinxing Yang, Ge Zhou, Longfei Li, Hong Chen, Jun Zhou
2023 J jnl
Towards Anytime Fine-tuning: Continually Pre-trained Language Models with Hypernetwork Prompt.
CoRR
Gangwei Jiang, Caigao Jiang, Siqiao Xue, James Y. Zhang, Jun Zhou, Defu Lian, Ying Wei
2023 — conf
Towards Anytime Fine-tuning: Continually Pre-trained Language Models with Hypernetwork Prompts.
EMNLP (Findings)
Gangwei Jiang, Caigao Jiang, Siqiao Xue, James Zhang, Jun Zhou, Defu Lian, Ying Wei
2023 A* conf
Towards Multi-Interest Pre-training with Sparse Capsule Network.
SIGIR
Zuoli Tang, Lin Wang, Lixin Zou, Xiaolu Zhang, Jun Zhou, Chenliang Li
2023 A* conf
Towards Open Temporal Graph Neural Networks.
ICLR
Kaituo Feng, Changsheng Li, Xiaolu Zhang, Jun Zhou
2023 J jnl
Towards Open Temporal Graph Neural Networks.
CoRR
Kaituo Feng, Changsheng Li, Xiaolu Zhang, Jun Zhou
2023 A conf
Treatment Effect Estimation across Domains.
CIKM
Yi-Xuan Sun, Ya-Lin Zhang, Wei Wang, Longfei Li, Jun Zhou
2023 A* conf
Uncertainty-based Heterogeneous Privileged Knowledge Distillation for Recommendation System.
SIGIR
Ang Li, Jian Hu, Ke Ding, Xiaolu Zhang, Jun Zhou, Yong He, Xu Min
2023 A* conf
Unleashing the Power of Graph Data Augmentation on Covariate Distribution Shift.
NeurIPS
Yongduo Sui, Qitian Wu, Jiancan Wu, Qing Cui, Longfei Li, Jun Zhou, Xiang Wang, Xiangnan He
2023 — conf
Unsupervised Fraud Transaction Detection on Dynamic Attributed Networks.
DASFAA (4)
Yangyang Hou, Daixin Wang, Binbin Hu, Ruoyu Zhuang, Zhiqiang Zhang, Jun Zhou, Feng Zhao, Yulin Kang, Zhanwen Qiao
2023 J jnl
WeaverBird: Empowering Financial Decision-Making with Large Language Model, Knowledge Base, and Search Engine.
CoRR
Siqiao Xue, Fan Zhou, Yi Xu, Hongyu Zhao, Shuo Xie, Qingyang Dai, Caigao Jiang, James Y. Zhang, Jun Zhou, Dacheng Xiu, Hongyuan Mei
2023 A* conf
Which Matters Most in Making Fund Investment Decisions? A Multi-granularity Graph Disentangled Learning Framework.
SIGIR
Chunjing Gan, Binbin Hu, Bo Huang, Tianyu Zhao, Yingru Lin, Wenliang Zhong, Zhiqiang Zhang, Jun Zhou, Chuan Shi
2023 J jnl
Which Matters Most in Making Fund Investment Decisions? A Multi-granularity Graph Disentangled Learning Framework.
CoRR
Chunjing Gan, Binbin Hu, Bo Huang, Tianyu Zhao, Yingru Lin, Wenliang Zhong, Zhiqiang Zhang, Jun Zhou, Chuan Shi
2023 J jnl
Your Labels are Selling You Out: Relation Leaks in Vertical Federated Learning.
IEEE Trans. Dependable Secur. Comput.
Pengyu Qiu, Xuhong Zhang, Shouling Ji, Tianyu Du, Yuwen Pu, Jun Zhou, Ting Wang
2022 A conf
A Biased Sampling Method for Imbalanced Personalized Ranking.
CIKM
Lu Yu, Shichao Pei, Feng Zhu, Longfei Li, Jun Zhou, Chuxu Zhang, Xiangliang Zhang
2022 A* conf
A Graph Learning Based Framework for Billion-Scale Offline User Identification.
KDD
Daixin Wang, Zujian Weng, Zhengwei Wu, Zhiqiang Zhang, Peng Cui, Hongwei Zhao, Jun Zhou
2022 — conf
A Multi-Task Learning Approach for Delayed Feedback Modeling.
WWW (Companion Volume)
Zhigang Huangfu, Gongduo Zhang, Zhengwei Wu, Qintong Wu, Zhiqiang Zhang, Lihong Gu, Jun Zhou, Jinjie Gu
2022 A conf
A Practical Distributed ADMM Solver for Billion-Scale Generalized Assignment Problems.
CIKM
Jun Zhou, Feng Qi, Zhigang Hua, Daohong Jian, Ziqi Liu, Hua Wu
2022 J jnl
A Practical Distributed ADMM Solver for Billion-Scale Generalized Assignment Problems.
CoRR
Jun Zhou, Feng Qi, Zhigang Hua, Daohong Jian, Ziqi Liu, Hua Wu, Xingwen Zhang, Shuang Yang
2022 A conf
A Real-time Post-processing System for Itinerary Recommendation.
CIKM
Linge Jiang, Guiyang Wang, Zhibo Zhu, Binghao Wang, Runsheng Gan, Ziqi Liu, Jun Zhou
2022 B conf
A Self-adaptive Indicator Selection Approach for Solving Credit Risk Assessment.
COMPSAC
Yongfeng Gu, Yue Ning, Hao Ding, Kecai Gu, Daohong Jian, Zhou Xu, Hua Wu, Jun Zhou
2022 — conf
A Task-Aware Attention-Based Method for Improved Meta-Learning.
APWeb/WAIM (2)
Yue Zhang, Xinxing Yang, Feng Zhu, Yalin Zhang, Meng Li, Qitao Shi, Longfei Li, Jun Zhou
2022 J jnl
AHEAD: A Triple Attention Based Heterogeneous Graph Anomaly Detection Approach.
CoRR
Shujie Yang, Binchi Zhang, Shangbin Feng, Zhaoxuan Tan, Qinghua Zheng, Jun Zhou, Minnan Luo
2022 A conf
An Adaptive Framework for Confidence-constraint Rule Set Learning Algorithm in Large Dataset.
CIKM
Meng Li, Lu Yu, Ya-Lin Zhang, Xiaoguang Huang, Qitao Shi, Qing Cui, Xinxing Yang, Longfei Li, Wei Zhu, Yanming Fang, Jun Zhou
2022 J jnl
An Effective Graph Learning based Approach for Temporal Link Prediction: The First Place of WSDM Cup 2022.
CoRR
Qian Zhao, Shuo Yang, Binbin Hu, Zhiqiang Zhang, Yakun Wang, Yusong Chen, Jun Zhou, Chuan Shi
2022 A* conf
An Industrial Framework for Cold-Start Recommendation in Zero-Shot Scenarios.
SIGIR
Zhaoxin Huan, Gongduo Zhang, Xiaolu Zhang, Jun Zhou, Qintong Wu, Lihong Gu, Jinjie Gu, Yong He, Yue Zhu, Linjian Mo
2022 Misc conf
Attribute-Conditioned Face Swapping Network for Low-Resolution Images.
ICASSP
Ang Li, Jian Hu, Chilin Fu, Xiaolu Zhang, Jun Zhou
2022 — conf
AutoTransformer: Automatic Transformer Architecture Design for Time Series Classification.
PAKDD (1)
Yankun Ren, Longfei Li, Xinxing Yang, Jun Zhou
2022 — conf
BadDet: Backdoor Attacks on Object Detection.
ECCV Workshops (1)
Shih-Han Chan, Yinpeng Dong, Jun Zhu, Xiaolu Zhang, Jun Zhou
2022 J jnl
BadDet: Backdoor Attacks on Object Detection.
CoRR
Shih-Han Chan, Yinpeng Dong, Jun Zhu, Xiaolu Zhang, Jun Zhou
2022 A* conf
Confidence May Cheat: Self-Training on Graph Neural Networks under Distribution Shift.
WWW
Hongrui Liu, Binbin Hu, Xiao Wang, Chuan Shi, Zhiqiang Zhang, Jun Zhou
2022 J jnl
Confidence May Cheat: Self-Training on Graph Neural Networks under Distribution Shift.
CoRR
Hongrui Liu, Binbin Hu, Xiao Wang, Chuan Shi, Zhiqiang Zhang, Jun Zhou
2022 A* conf
Debiased Causal Tree: Heterogeneous Treatment Effects Estimation with Unmeasured Confounding.
NeurIPS
Caizhi Tang, Huiyuan Wang, Xinyu Li, Qing Cui, Ya-Lin Zhang, Feng Zhu, Longfei Li, Jun Zhou, Linbo Jiang
2022 J jnl
FinBrain 2.0: when finance meets trustworthy AI.
Frontiers Inf. Technol. Electron. Eng.
Jun Zhou, Chaochao Chen, Longfei Li, Zhiqiang Zhang, Xiaolin Zheng
2022 A conf
FwSeqBlock: A Field-wise Approach for Modeling Behavior Representation in Sequential Recommendation.
CIKM
Hao Qian, Qintong Wu, Minghao Li, Zhengwei Wu, Zhiqiang Zhang, Jun Zhou, Lihong Gu, Jinjie Gu
2022 A* conf
Gaia: Graph Neural Network with Temporal Shift aware Attention for Gross Merchandise Value Forecast in E-commerce.
ICDE
Borui Ye, Shuo Yang, Binbin Hu, Zhiqiang Zhang, Youqiang He, Kai Huang, Jun Zhou, Yanming Fang
2022 J jnl
Gaia: Graph Neural Network with Temporal Shift aware Attention for Gross Merchandise Value Forecast in E-commerce.
CoRR
Borui Ye, Shuo Yang, Binbin Hu, Zhiqiang Zhang, Youqiang He, Kai Huang, Jun Zhou, Yanming Fang
2022 A conf
GraTO: Graph Neural Network Framework Tackling Over-smoothing with Neural Architecture Search.
CIKM
Xinshun Feng, Herun Wan, Shangbin Feng, Hongrui Wang, Qinghua Zheng, Jun Zhou, Minnan Luo
2022 J jnl
GraTO: Graph Neural Network Framework Tackling Over-smoothing with Neural Architecture Search.
CoRR
Xinshun Feng, Herun Wan, Shangbin Feng, Hongrui Wang, Jun Zhou, Qinghua Zheng, Minnan Luo
2022 — conf
Heuristic strategies for solving the combinatorial optimization problem in real-world credit risk assessment.
GECCO Companion
Yongfeng Gu, Hao Ding, Kecai Gu, Runsheng Gan, Xiaoguang Huang, Yanming Fang, Zhigang Hua, Hua Wu, Jifeng Xuan, Jun Zhou
2022 A* conf
Intent Mining: A Social and Semantic Enhanced Topic Model for Operation-Friendly Digital Marketing.
ICDE
Weifan Wang, Xiaocheng Cheng, Ziqi Liu, Yu Lin, Yue Shen, Binbin Hu, Zhiqiang Zhang, Xiaodong Zeng, Jun Zhou, Jinjie Gu, Minnan Luo
2022 J jnl
Interpreting Model Predictions with Constrained Perturbation and Counterfactual Instances.
Int. J. Pattern Recognit. Artif. Intell.
Jun-Peng Fang, Jun Zhou, Qing Cui, Caizhi Tang, Longfei Li
2022 J jnl
KGNN: Distributed Framework for Graph Neural Knowledge Representation.
CoRR
Binbin Hu, Zhiyang Hu, Zhiqiang Zhang, Jun Zhou, Chuan Shi
2022 A* conf
Label Inference Attacks Against Vertical Federated Learning.
USENIX Security Symposium
Chong Fu, Xuhong Zhang, Shouling Ji, Jinyin Chen, Jingzheng Wu, Shanqing Guo, Jun Zhou, Alex X. Liu, Ting Wang
2022 A* conf
Learning Mixture of Neural Temporal Point Processes for Multi-dimensional Event Sequence Clustering.
IJCAI
Yunhao Zhang, Junchi Yan, Xiaolu Zhang, Jun Zhou, Xiaokang Yang
2022 A* conf
MERIT: Learning Multi-level Representations on Temporal Graphs.
IJCAI
Binbin Hu, Zhengwei Wu, Jun Zhou, Ziqi Liu, Zhigang Huangfu, Zhiqiang Zhang, Chaochao Chen
2022 A* conf
MetaCare++: Meta-Learning with Hierarchical Subtyping for Cold-Start Diagnosis Prediction in Healthcare Data.
SIGIR
Yanchao Tan, Carl Yang, Xiangyu Wei, Chaochao Chen, Weiming Liu, Longfei Li, Jun Zhou, Xiaolin Zheng
2022 A conf
MetaRule: A Meta-path Guided Ensemble Rule Set Learning for Explainable Fraud Detection.
CIKM
Lu Yu, Meng Li, Xiaoguang Huang, Wei Zhu, Yanming Fang, Jun Zhou, Longfei Li
2022 — conf
Mixture of Graph Enhanced Expert Networks for Multi-task Recommendation.
PRICAI (3)
Binbin Hu, Bin Shen, Ruize Wu, Zhiqiang Zhang, Yuetian Cao, Yong He, Liang Zhang, Linjian Mo, Jun Zhou
2022 — conf
NL-SOMA-CLP for real parameter single objective bound constrained optimization.
GECCO Companion
Hao Ding, Yongfeng Gu, Hua Wu, Jun Zhou
2022 A conf
Neural Graph Matching for Pre-training Graph Neural Networks.
SDM
Yupeng Hou, Binbin Hu, Wayne Xin Zhao, Zhiqiang Zhang, Jun Zhou, Ji-Rong Wen
2022 J jnl
Neural Graph Matching for Pre-training Graph Neural Networks.
CoRR
Yupeng Hou, Binbin Hu, Wayne Xin Zhao, Zhiqiang Zhang, Jun Zhou, Ji-Rong Wen
2022 — conf
Opposite learning and multi-migrating strategy-based self-organizing migrating algorithm with the convergence monitoring mechanism.
GECCO Companion
Yongfeng Gu, Hao Ding, Hua Wu, Jun Zhou
2022 A* conf
Regularizing Graph Neural Networks via Consistency-Diversity Graph Augmentations.
AAAI
Deyu Bo, Binbin Hu, Xiao Wang, Zhiqiang Zhang, Chuan Shi, Jun Zhou
2022 C conf
Robust Direct Learning for Causal Data Fusion.
ACML
Xinyu Li, Yilin Li, Qing Cui, Longfei Li, Jun Zhou
2022 J jnl
Robust Direct Learning for Causal Data Fusion.
CoRR
Xinyu Li, Yilin Li, Qing Cui, Longfei Li, Jun Zhou
2022 A* conf
Robust Heterogeneous Graph Neural Networks against Adversarial Attacks.
AAAI
Mengmei Zhang, Xiao Wang, Meiqi Zhu, Chuan Shi, Zhiqiang Zhang, Jun Zhou
2022 J jnl
Robust Unsupervised Graph Representation Learning via Mutual Information Maximization.
CoRR
Jihong Wang, Minnan Luo, Jundong Li, Ziqi Liu, Jun Zhou, Qinghua Zheng
2022 A* conf
SAIL: Self-Augmented Graph Contrastive Learning.
AAAI
Lu Yu, Shichao Pei, Lizhong Ding, Jun Zhou, Longfei Li, Chuxu Zhang, Xiangliang Zhang
2022 A conf
Scope-aware Re-ranking with Gated Attention in Feed.
WSDM
Hao Qian, Qintong Wu, Kai Zhang, Zhiqiang Zhang, Lihong Gu, Xiaodong Zeng, Jun Zhou, Jinjie Gu
2022 A conf
Semi-Supervised Learning with Data Augmentation for Tabular Data.
CIKM
Jun-Peng Fang, Caizhi Tang, Qing Cui, Feng Zhu, Longfei Li, Jun Zhou, Wei Zhu
2022 — conf
TAMOR: Tier-Aware Multi-objective Recommendation for Ant Fortune Financial Marketing.
ECML/PKDD (6)
Xu Min, Xiaolu Zhang, Jun Zhou, Changxun Fan, Junlin Yu
2022 A conf
Task Similarity Aware Meta Learning for Cold-Start Recommendation.
CIKM
Jieyu Yang, Zhaoxin Huan, Yong He, Ke Ding, Liang Zhang, Xiaolu Zhang, Jun Zhou, Linjian Mo
2022 J jnl
Toward Scalable and Privacy-preserving Deep Neural Network via Algorithmic-Cryptographic Co-design.
ACM Trans. Intell. Syst. Technol.
Jun Zhou, Longfei Zheng, Chaochao Chen, Yan Wang, Xiaolin Zheng, Bingzhe Wu, Cen Chen, Li Wang, Jianwei Yin
2022 A* conf
Transfer Attacks Revisited: A Large-Scale Empirical Study in Real Computer Vision Settings.
SP
Yuhao Mao, Chong Fu, Saizhuo Wang, Shouling Ji, Xuhong Zhang, Zhenguang Liu, Jun Zhou, Alex X. Liu, Raheem Beyah, Ting Wang
2022 J jnl
Transfer Attacks Revisited: A Large-Scale Empirical Study in Real Computer Vision Settings.
CoRR
Yuhao Mao, Chong Fu, Saizhuo Wang, Shouling Ji, Xuhong Zhang, Zhenguang Liu, Jun Zhou, Alex X. Liu, Raheem Beyah, Ting Wang
2022 A* conf
Vertically Federated Graph Neural Network for Privacy-Preserving Node Classification.
IJCAI
Chaochao Chen, Jun Zhou, Longfei Zheng, Huiwen Wu, Lingjuan Lyu, Jia Wu, Bingzhe Wu, Ziqi Liu, Li Wang, Xiaolin Zheng
2022 — conf
Zeroth-order covariance matrix adaptation evolution strategy for single objective bound constrained numerical optimization competition.
GECCO Companion
Yue Ning, Daohong Jian, Hua Wu, Jun Zhou
2021 A* conf
A Bi-Level Framework for Learning to Solve Combinatorial Optimization on Graphs.
NeurIPS
Runzhong Wang, Zhigang Hua, Gan Liu, Jiayi Zhang, Junchi Yan, Feng Qi, Shuang Yang, Jun Zhou, Xiaokang Yang
2021 J jnl
A Bi-Level Framework for Learning to Solve Combinatorial Optimization on Graphs.
CoRR
Runzhong Wang, Zhigang Hua, Gan Liu, Jiayi Zhang, Junchi Yan, Feng Qi, Shuang Yang, Jun Zhou, Xiaokang Yang
2021 J jnl
A Boosting Framework of Factorization Machine.
Int. J. Pattern Recognit. Artif. Intell.
Jun Zhou, Longfei Li, Ziqi Liu, Chaochao Chen
2021 — conf
A Classification Based Ensemble Pruning Framework with Multi-metric Consideration.
IntelliSys (1)
Ya-Lin Zhang, Qitao Shi, Meng Li, Xinxing Yang, Longfei Li, Jun Zhou
2021 — conf
A Graph Attention Network Model for GMV Forecast on Online Shopping Festival.
APWeb/WAIM (1)
Qianyu Yu, Shuo Yang, Zhiqiang Zhang, Ya-Lin Zhang, Binbin Hu, Ziqi Liu, Kai Huang, Xingyu Zhong, Jun Zhou, Yanming Fang
2021 J jnl
A Unified Framework for Cross-Domain and Cross-System Recommendations.
CoRR
Feng Zhu, Yan Wang, Jun Zhou, Chaochao Chen, Longfei Li, Guanfeng Liu
2021 J jnl
ASFGNN: Automated separated-federated graph neural network.
Peer-to-Peer Netw. Appl.
Longfei Zheng, Jun Zhou, Chaochao Chen, Bingzhe Wu, Li Wang, Benyu Zhang
2021 J jnl
Adaptive Client Sampling in Federated Learning via Online Learning with Bandit Feedback.
CoRR
Boxin Zhao, Ziqi Liu, Chaochao Chen, Mladen Kolar, Zhiqiang Zhang, Jun Zhou
2021 A conf
AntOpt: A Multi-functional Large-scale Decision Optimization Platform.
CIKM
Jun Zhou, Yang Bao, Hua Wu, Zhigang Hua
2021 J jnl
Conditional Attention Networks for Distilling Knowledge Graphs in Recommendation.
CoRR
Ke Tu, Peng Cui, Daixin Wang, Zhiqiang Zhang, Jun Zhou, Yuan Qi, Wenwu Zhu
2021 A conf
Conditional Graph Attention Networks for Distilling and Refining Knowledge Graphs in Recommendation.
CIKM
Ke Tu, Peng Cui, Daixin Wang, Zhiqiang Zhang, Jun Zhou, Yuan Qi, Wenwu Zhu
2021 — conf
Constraint-Adaptive Rule Mining in Large Databases.
DASFAA (3)
Meng Li, Ya-Lin Zhang, Qitao Shi, Xinxing Yang, Qing Cui, Longfei Li, Jun Zhou
2021 A conf
Counterfactual Review-based Recommendation.
CIKM
Kun Xiong, Wenwen Ye, Xu Chen, Yongfeng Zhang, Wayne Xin Zhao, Binbin Hu, Zhiqiang Zhang, Jun Zhou
2021 A* conf
Cross-Domain Recommendation: Challenges, Progress, and Prospects.
IJCAI
Feng Zhu, Yan Wang, Chaochao Chen, Jun Zhou, Longfei Li, Guanfeng Liu
2021 J jnl
Cross-Domain Recommendation: Challenges, Progress, and Prospects.
CoRR
Feng Zhu, Yan Wang, Chaochao Chen, Jun Zhou, Longfei Li, Guanfeng Liu
2021 A* conf
Improving Transferability of Adversarial Patches on Face Recognition With Generative Models.
CVPR
Zihao Xiao, Xianfeng Gao, Chilin Fu, Yinpeng Dong, Wei Gao, Xiaolu Zhang, Jun Zhou, Jun Zhu
2021 J jnl
Improving Transferability of Adversarial Patches on Face Recognition with Generative Models.
CoRR
Zihao Xiao, Xianfeng Gao, Chilin Fu, Yinpeng Dong, Wei Gao, Xiaolu Zhang, Jun Zhou, Jun Zhu
2021 — conf
Inductive Link Prediction with Interactive Structure Learning on Attributed Graph.
ECML/PKDD (2)
Shuo Yang, Binbin Hu, Zhiqiang Zhang, Wang Sun, Yang Wang, Jun Zhou, Hongyu Shan, Yuetian Cao, Borui Ye, Yanming Fang, Quan Yu
2021 A* conf
IntelliTag: An Intelligent Cloud Customer Service System Based on Tag Recommendation.
ICDE
Minghui Yang, Shaosheng Cao, Binbin Hu, Xianling Chen, Hengbin Cui, Zhiqiang Zhang, Jun Zhou, Xiaolong Li
2021 A conf
Large-scale Secure XGB for Vertical Federated Learning.
CIKM
Wenjing Fang, Derun Zhao, Jin Tan, Chaochao Chen, Chaofan Yu, Li Wang, Lei Wang, Jun Zhou, Benyu Zhang
2021 A conf
Learning Representations of Inactive Users: A Cross Domain Approach with Graph Neural Networks.
CIKM
Ziqi Liu, Yue Shen, Xiaocheng Cheng, Qiang Li, Jianping Wei, Zhiqiang Zhang, Dong Wang, Xiaodong Zeng, Jinjie Gu, Jun Zhou
2021 A* conf
Learning to Select Instance: Simultaneous Transfer Learning and Clustering.
SIGIR
Zhaoxin Huan, Yulong Wang, Yong He, Xiaolu Zhang, Chilin Fu, Weichang Wu, Jun Zhou, Ke Ding, Liang Zhang, Linjian Mo
2021 A conf
Low-dimensional Alignment for Cross-Domain Recommendation.
CIKM
Tianxin Wang, Fuzhen Zhuang, Zhiqiang Zhang, Daixin Wang, Jun Zhou, Qing He
2021 A* conf
MixSeq: Connecting Macroscopic Time Series Forecasting with Microscopic Time Series Data.
NeurIPS
Zhibo Zhu, Ziqi Liu, Ge Jin, Zhiqiang Zhang, Lei Chen, Jun Zhou, Jianyong Zhou
2021 J jnl
MixSeq: Connecting Macroscopic Time Series Forecasting with Microscopic Time Series Data.
CoRR
Zhibo Zhu, Ziqi Liu, Ge Jin, Zhiqiang Zhang, Lei Chen, Jun Zhou, Jianyong Zhou
2021 A conf
Multi-Interactive Attention Network for Fine-grained Feature Learning in CTR Prediction.
WSDM
Kai Zhang, Hao Qian, Qing Cui, Qi Liu, Longfei Li, Jun Zhou, Jianhui Ma, Enhong Chen
2021 J jnl
PPSGCN: A Privacy-Preserving Subgraph Sampling Based Distributed GCN Training Method.
CoRR
Binchi Zhang, Minnan Luo, Shangbin Feng, Ziqi Liu, Jun Zhou, Qinghua Zheng
2021 — conf
Rethinking the Effectiveness of Selective Attention in Neural Networks.
ICONIP (3)
Yulong Wang, Xiaolu Zhang, Jun Zhou, Hang Su
2021 A conf
SIFN: A Sentiment-aware Interactive Fusion Network for Review-based Item Recommendation.
CIKM
Kai Zhang, Hao Qian, Qi Liu, Zhiqiang Zhang, Jun Zhou, Jianhui Ma, Enhong Chen
2021 J jnl
SIFN: A Sentiment-aware Interactive Fusion Network for Review-based Item Recommendation.
CoRR
Kai Zhang, Hao Qian, Qi Liu, Zhiqiang Zhang, Jun Zhou, Jianhui Ma, Enhong Chen
2021 B conf
Simtrojan: Stealthy Backdoor Attack.
ICIP
Yankun Ren, Longfei Li, Jun Zhou
2021 A conf
Temporal-Aware Graph Neural Network for Credit Risk Prediction.
SDM
Daixin Wang, Zhiqiang Zhang, Jun Zhou, Peng Cui, Jingli Fang, Quanhui Jia, Yanming Fang, Yuan Qi
2021 A* conf
When Homomorphic Encryption Marries Secret Sharing: Secure Large-Scale Sparse Logistic Regression and Applications in Risk Control.
KDD
Chaochao Chen, Jun Zhou, Li Wang, Xibin Wu, Wenjing Fang, Jin Tan, Lei Wang, Alex X. Liu, Hao Wang, Cheng Hong
2020 J jnl
A Comprehensive Analysis of Information Leakage in Deep Transfer Learning.
CoRR
Cen Chen, Bingzhe Wu, Minghui Qiu, Li Wang, Jun Zhou
2020 J jnl
A Hybrid-Domain Framework for Secure Gradient Tree Boosting.
CoRR
Wenjing Fang, Chaochao Chen, Jin Tan, Chaofan Yu, Yufei Lu, Li Wang, Lei Wang, Jun Zhou, Alex X
2020 J jnl
A Semi-supervised Graph Attentive Network for Financial Fraud Detection.
CoRR
Daixin Wang, Jianbin Lin, Peng Cui, Quanhui Jia, Zhen Wang, Yanming Fang, Quan Yu, Jun Zhou, Shuang Yang, Yuan Qi
2020 J jnl
AGL: A Scalable System for Industrial-purpose Graph Machine Learning.
Proc. VLDB Endow.
Dalong Zhang, Xin Huang, Ziqi Liu, Jun Zhou, Zhiyang Hu, Xianzheng Song, Zhibang Ge, Lin Wang, Zhiqiang Zhang, Yuan Qi
2020 J jnl
AGL: a Scalable System for Industrial-purpose Graph Machine Learning.
CoRR
Dalong Zhang, Xin Huang, Ziqi Liu, Zhiyang Hu, Xianzheng Song, Zhibang Ge, Zhiqiang Zhang, Lin Wang, Jun Zhou, Shuang Yang, Yuan Qi
2020 J jnl
ASFGNN: Automated Separated-Federated Graph Neural Network.
CoRR
Longfei Zheng, Jun Zhou, Chaochao Chen, Bingzhe Wu, Li Wang, Benyu Zhang
2020 J jnl
Adapted tree boosting for Transfer Learning.
CoRR
Wenjing Fang, Chaochao Chen, Bowen Song, Li Wang, Jun Zhou, Kenny Q. Zhu
2020 — conf
AutoRec: A Comprehensive Platform for Building Effective and Explainable Recommender Models.
ECML/PKDD (5)
Qing Cui, Qitao Shi, Hao Qian, Caizhi Tang, Xixi Li, Yiming Zhao, Tao Jiang, Longfei Li, Jun Zhou
2020 — conf
Automatic Knowledge Fusion in Transferrable Networks for Semantic Text Matching.
WWW (Companion Volume)
Cen Chen, Ya-Lin Zhang, Minghui Qiu, Bingzhe Wu, Li Wang, Longfei Li, Jun Zhou
2020 A* conf
Bandit Samplers for Training Graph Neural Networks.
NeurIPS
Ziqi Liu, Zhengwei Wu, Zhiqiang Zhang, Jun Zhou, Shuang Yang, Le Song, Yuan Qi
2020 J jnl
Bandit Samplers for Training Graph Neural Networks.
CoRR
Ziqi Liu, Zhengwei Wu, Zhiqiang Zhang, Jun Zhou, Shuang Yang, Le Song, Yuan Qi
2020 A* conf
Characterizing Membership Privacy in Stochastic Gradient Langevin Dynamics.
AAAI
Bingzhe Wu, Chaochao Chen, Shiwan Zhao, Cen Chen, Yuan Yao, Guangyu Sun, Li Wang, Xiaolu Zhang, Jun Zhou
2020 J jnl
DSSLP: A Distributed Framework for Semi-supervised Link Prediction.
CoRR
Dalong Zhang, Xianzheng Song, Ziqi Liu, Zhiqiang Zhang, Xin Huang, Lin Wang, Jun Zhou
2020 — conf
Data-Free Adversarial Perturbations for Practical Black-Box Attack.
PAKDD (2)
Zhaoxin Huan, Yulong Wang, Xiaolu Zhang, Lin Shang, Chilin Fu, Jun Zhou
2020 J jnl
Data-Free Adversarial Perturbations for Practical Black-Box Attack.
CoRR
Zhaoxin Huan, Yulong Wang, Xiaolu Zhang, Lin Shang, Chilin Fu, Jun Zhou
2020 A conf
EasyGML: A Fully-functional and Easy-to-use Platform for Industrial Graph Machine Learning.
CIKM
Zhiqiang Zhang, Jun Zhou, Chuan Shi
2020 A* conf
Financial Risk Analysis for SMEs with Graph-based Supply Chain Mining.
IJCAI
Shuo Yang, Zhiqiang Zhang, Jun Zhou, Yang Wang, Wang Sun, Xingyu Zhong, Yanming Fang, Quan Yu, Yuan Qi
2020 A conf
Generating Natural Language Adversarial Examples on a Large Scale with Generative Models.
ECAI
Yankun Ren, Jianbin Lin, Siliang Tang, Jun Zhou, Shuang Yang, Yuan Qi, Xiang Ren
2020 J jnl
Generating Natural Language Adversarial Examples on a Large Scale with Generative Models.
CoRR
Yankun Ren, Jianbin Lin, Siliang Tang, Jun Zhou, Shuang Yang, Yuan Qi, Xiang Ren
2020 J jnl
Graph Representation Learning for Merchant Incentive Optimization in Mobile Payment Marketing.
CoRR
Ziqi Liu, Dong Wang, Qianyu Yu, Zhiqiang Zhang, Yue Shen, Jian Ma, Wenliang Zhong, Jinjie Gu, Jun Zhou, Shuang Yang, Yuan Qi
2020 J jnl
Heterogeneous Graph Neural Network for Recommendation.
CoRR
Jinghan Shi, Houye Ji, Chuan Shi, Xiao Wang, Zhiqiang Zhang, Jun Zhou
2020 J jnl
Heterogeneous Graph Neural Networks for Malicious Account Detection.
CoRR
Ziqi Liu, Chaochao Chen, Xinxing Yang, Jun Zhou, Xiaolong Li, Le Song
2020 J jnl
How Much Can A Retailer Sell? Sales Forecasting on Tmall.
CoRR
Chaochao Chen, Ziqi Liu, Jun Zhou, Xiaolong Li, Yuan Qi, Yujing Jiao, Xingyu Zhong
2020 A* conf
Hubble: An Industrial System for Audience Expansion in Mobile Marketing.
KDD
Chenyi Zhuang, Ziqi Liu, Zhiqiang Zhang, Yize Tan, Zhengwei Wu, Zhining Liu, Jianping Wei, Jinjie Gu, Guannan Zhang, Jun Zhou, Yuan Qi
2020 J jnl
Industrial Scale Privacy Preserving Deep Neural Network.
CoRR
Longfei Zheng, Chaochao Chen, Yingting Liu, Bingzhe Wu, Xibin Wu, Li Wang, Lei Wang, Jun Zhou, Shuang Yang
2020 J jnl
InfDetect: a Large Scale Graph-based Fraud Detection System for E-Commerce Insurance.
CoRR
Cen Chen, Chen Liang, Jianbin Lin, Li Wang, Ziqi Liu, Xinxing Yang, Xiukun Wang, Jun Zhou, Shuang Yang, Yuan Qi
2020 A conf
Loan Default Analysis with Multiplex Graph Learning.
CIKM
Binbin Hu, Zhiqiang Zhang, Jun Zhou, Jingli Fang, Quanhui Jia, Yanming Fang, Quan Yu, Yuan Qi
2020 J jnl
Multi-Interactive Attention Network for Fine-grained Feature Learning in CTR Prediction.
CoRR
Kai Zhang, Hao Qian, Qing Cui, Qi Liu, Longfei Li, Jun Zhou, Jianhui Ma, Enhong Chen
2020 A conf
Nebula: A Scalable Privacy-Preserving Machine Learning System in Ant Financial.
CIKM
Cen Chen, Bingzhe Wu, Li Wang, Chaochao Chen, Jin Tan, Lei Wang, Jun Zhou, Benyu Zhang
2020 J jnl
NetDP: An Industrial-Scale Distributed Network Representation Framework for Default Prediction in Ant Credit Pay.
CoRR
Jianbin Lin, Zhiqiang Zhang, Jun Zhou, Xiaolong Li, Jingli Fang, Yanming Fang, Quan Yu, Yuan Qi
2020 — conf
Neural Zero-Shot Fine-Grained Entity Typing.
WWW (Companion Volume)
Yankun Ren, Jianbin Lin, Jun Zhou
2020 J jnl
Practical Privacy Preserving POI Recommendation.
CoRR
Chaochao Chen, Bingzhe Wu, Wenjin Fang, Jun Zhou, Li Wang, Yuan Qi, Xiaolin Zheng
2020 J jnl
Practical Privacy Preserving POI Recommendation.
ACM Trans. Intell. Syst. Technol.
Chaochao Chen, Jun Zhou, Bingzhe Wu, Wenjing Fang, Li Wang, Yuan Qi, Xiaolin Zheng
2020 J jnl
Privacy Preserving PCA for Multiparty Modeling.
CoRR
Yingting Liu, Chaochao Chen, Longfei Zheng, Li Wang, Jun Zhou, Guiquan Liu
2020 J jnl
Privacy Preserving Point-of-interest Recommendation Using Decentralized Matrix Factorization.
CoRR
Chaochao Chen, Ziqi Liu, Peilin Zhao, Jun Zhou, Xiaolong Li
2020 J jnl
Privacy-Preserving Graph Neural Network for Node Classification.
CoRR
Jun Zhou, Chaochao Chen, Longfei Zheng, Xiaolin Zheng, Bingzhe Wu, Ziqi Liu, Li Wang
2020 A* conf
Pruning from Scratch.
AAAI
Yulong Wang, Xiaolu Zhang, Lingxi Xie, Jun Zhou, Hang Su, Bo Zhang, Xiaolin Hu
2020 J jnl
RNE: A Scalable Network Embedding for Billion-scale Recommendation.
CoRR
Jianbin Lin, Daixin Wang, Lu Guan, Yin Zhao, Binqiang Zhao, Jun Zhou, Xiaolong Li, Yuan Qi
2020 A* conf
SAFE: Scalable Automatic Feature Engineering Framework for Industrial Tasks.
ICDE
Qitao Shi, Ya-Lin Zhang, Longfei Li, Xinxing Yang, Meng Li, Jun Zhou
2020 J jnl
SAFE: Scalable Automatic Feature Engineering Framework for Industrial Tasks.
CoRR
Qitao Shi, Ya-Lin Zhang, Longfei Li, Xinxing Yang, Meng Li, Jun Zhou
2020 J jnl
Secret Sharing based Secure Regressions with Applications.
CoRR
Chaochao Chen, Liang Li, Wenjing Fang, Jun Zhou, Li Wang, Lei Wang, Shuang Yang, Alex Liu, Hao Wang
2020 A conf
Secure Social Recommendation Based on Secret Sharing.
ECAI
Chaochao Chen, Liang Li, Bingzhe Wu, Cheng Hong, Li Wang, Jun Zhou
2020 J jnl
Secure Social Recommendation based on Secret Sharing.
CoRR
Chaochao Chen, Liang Li, Bingzhe Wu, Cheng Hong, Li Wang, Jun Zhou
2020 J jnl
Self-supervised Smoothing Graph Neural Networks.
CoRR
Lu Yu, Shichao Pei, Chuxu Zhang, Lizhong Ding, Jun Zhou, Longfei Li, Xiangliang Zhang
2020 J jnl
Towards Scalable and Privacy-Preserving Deep Neural Network via Algorithmic-Cryptographic Co-design.
CoRR
Chaochao Chen, Jun Zhou, Longfei Zheng, Yan Wang, Xiaolin Zheng, Bingzhe Wu, Cen Chen, Li Wang, Jianwei Yin
2020 J jnl
Uncovering Insurance Fraud Conspiracy with Network Learning.
CoRR
Chen Liang, Ziqi Liu, Bin Liu, Jun Zhou, Xiaolong Li, Shuang Yang, Yuan Qi
2020 J jnl
Unpack Local Model Interpretation for GBDT.
CoRR
Wenjing Fang, Jun Zhou, Xiaolong Li, Kenny Q. Zhu
2020 J jnl
When Homomorphic Encryption Marries Secret Sharing: Secure Large-Scale Sparse Logistic Regression and Applications in Risk Control.
CoRR
Chaochao Chen, Jun Zhou, Li Wang, Xibin Wu, Wenjing Fang, Jin Tan, Lei Wang, Xiaoxi Ji, Alex Liu, Hao Wang, Cheng Hong
2020 A conf
aDMSCN: A Novel Perspective for User Intent Prediction in Customer Service Bots.
CIKM
Kuan Xu, Chilin Fu, Xiaolu Zhang, Cen Chen, Ya-Lin Zhang, Wenge Rong, Zujie Wen, Jun Zhou, Xiaolong Li, Yu Qiao
2019 A* conf
A Semi-Supervised Graph Attentive Network for Financial Fraud Detection.
ICDM
Daixin Wang, Yuan Qi, Jianbin Lin, Peng Cui, Quanhui Jia, Zhen Wang, Yanming Fang, Quan Yu, Jun Zhou, Shuang Yang
2019 J jnl
A Time Attention based Fraud Transaction Detection Framework.
CoRR
Longfei Li, Ziqi Liu, Chaochao Chen, Ya-Lin Zhang, Jun Zhou, Xiaolong Li
2019 — conf
Adapted Tree Boosting for Transfer Learning.
IEEE BigData
Wenjing Fang, Chaochao Chen, Bowen Song, Li Wang, Jun Zhou, Kenny Q. Zhu
2019 A* conf
AntProphet: an Intention Mining System behind Alipay's Intelligent Customer Service Bot.
IJCAI
Cen Chen, Xiaolu Zhang, Sheng Ju, Chilin Fu, Caizhi Tang, Jun Zhou, Xiaolong Li
2019 A* conf
Cash-Out User Detection Based on Attributed Heterogeneous Information Network with a Hierarchical Attention Mechanism.
AAAI
Binbin Hu, Zhiqiang Zhang, Chuan Shi, Jun Zhou, Xiaolong Li, Yuan Qi
2019 J jnl
Characterizing Membership Privacy in Stochastic Gradient Langevin Dynamics.
CoRR
Bingzhe Wu, Chaochao Chen, Shiwan Zhao, Cen Chen, Yuan Yao, Guangyu Sun, Li Wang, Xiaolu Zhang, Jun Zhou
2019 — conf
DSSLP: A Distributed Framework for Semi-supervised Link Prediction.
IEEE BigData
Dalong Zhang, Xianzheng Song, Ziqi Liu, Zhiqiang Zhang, Xin Huang, Lin Wang, Jun Zhou
2019 J jnl
Distributed Deep Forest and its Application to Automatic Detection of Cash-Out Fraud.
ACM Trans. Intell. Syst. Technol.
Ya-Lin Zhang, Jun Zhou, Wenhao Zheng, Ji Feng, Longfei Li, Ziqi Liu, Ming Li, Zhiqiang Zhang, Chaochao Chen, Xiaolong Li, Yuan (Alan) Qi, Zhi-Hua Zhou
2019 A* conf
Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection.
NeurIPS
Bingzhe Wu, Shiwan Zhao, Chaochao Chen, Haoyang Xu, Li Wang, Xiaolu Zhang, Guangyu Sun, Jun Zhou
2019 J jnl
Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection.
CoRR
Bingzhe Wu, Shiwan Zhao, Haoyang Xu, Chaochao Chen, Li Wang, Xiaolu Zhang, Guangyu Sun, Jun Zhou
2019 A* conf
GeniePath: Graph Neural Networks with Adaptive Receptive Paths.
AAAI
Ziqi Liu, Chaochao Chen, Longfei Li, Jun Zhou, Xiaolong Li, Le Song, Yuan Qi
2019 A conf
Graph Representation Learning for Merchant Incentive Optimization in Mobile Payment Marketing.
CIKM
Ziqi Liu, Dong Wang, Qianyu Yu, Zhiqiang Zhang, Yue Shen, Jian Ma, Wenliang Zhong, Jinjie Gu, Jun Zhou, Shuang Yang, Yuan Qi
2019 — conf
How Much Can A Retailer Sell? Sales Forecasting on Tmall.
PAKDD (2)
Chaochao Chen, Ziqi Liu, Jun Zhou, Xiaolong Li, Yuan Qi, Yujing Jiao, Xingyu Zhong
2019 — conf
InfDetect: a Large Scale Graph-based Fraud Detection System for E-Commerce Insurance.
IEEE BigData
Cen Chen, Chen Liang, Jianbin Lin, Li Wang, Ziqi Liu, Xinxing Yang, Jun Zhou, Shuang Yang, Yuan Qi
2019 A* conf
Multi-Domain Gated CNN for Review Helpfulness Prediction.
WWW
Cen Chen, Minghui Qiu, Yinfei Yang, Jun Zhou, Jun Huang, Xiaolong Li, Forrest Sheng Bao
2019 J jnl
Pruning from Scratch.
CoRR
Yulong Wang, Xiaolu Zhang, Lingxi Xie, Jun Zhou, Hang Su, Bo Zhang, Xiaolin Hu
2019 — conf
RNE: A Scalable Network Embedding for Billion-Scale Recommendation.
PAKDD (2)
Jianbin Lin, Daixin Wang, Lu Guan, Yin Zhao, Binqiang Zhao, Jun Zhou, Xiaolong Li, Yuan (Alan) Qi
2019 A* conf
Reinforcement Learning for User Intent Prediction in Customer Service Bots.
SIGIR
Cen Chen, Chilin Fu, Xu Hu, Xiaolu Zhang, Jun Zhou, Xiaolong Li, Forrest Sheng Bao
2019 J jnl
TitAnt: Online Real-time Transaction Fraud Detection in Ant Financial.
CoRR
Shaosheng Cao, Xinxing Yang, Cen Chen, Jun Zhou, Xiaolong Li, Yuan (Alan) Qi
2019 J jnl
TitAnt: Online Real-time Transaction Fraud Detection in Ant Financial.
Proc. VLDB Endow.
Shaosheng Cao, Xinxing Yang, Cen Chen, Jun Zhou, Xiaolong Li, Yuan Qi
2019 A* conf
Uncovering Insurance Fraud Conspiracy with Network Learning.
SIGIR
Chen Liang, Ziqi Liu, Bin Liu, Jun Zhou, Xiaolong Li, Shuang Yang, Yuan Qi
2018 J jnl
A Boosting Framework of Factorization Machine.
CoRR
Longfei Li, Peilin Zhao, Jun Zhou, Xiaolong Li
2018 — conf
A Local Online Learning Approach for Non-linear Data.
PAKDD (2)
Xinxing Yang, Jun Zhou, Peilin Zhao, Cen Chen, Chaochao Chen, Xiaolong Li
2018 — conf
An Industrial-Scale System for Heterogeneous Information Card Ranking in Alipay.
DASFAA (2)
Zhiqiang Zhang, Chaochao Chen, Jun Zhou, Xiaolong Li
2018 — conf
Anomaly Detection with Partially Observed Anomalies.
WWW (Companion Volume)
Ya-Lin Zhang, Longfei Li, Jun Zhou, Xiaolong Li, Zhi-Hua Zhou
2018 — conf
Cross-Domain Review Helpfulness Prediction Based on Convolutional Neural Networks with Auxiliary Domain Discriminators.
NAACL-HLT (2)
Cen Chen, Yinfei Yang, Jun Zhou, Xiaolong Li, Forrest Sheng Bao
2018 A* conf
Distributed Collaborative Hashing and Its Applications in Ant Financial.
KDD
Chaochao Chen, Ziqi Liu, Peilin Zhao, Longfei Li, Jun Zhou, Xiaolong Li
2018 J jnl
Distributed Collaborative Hashing and Its Applications in Ant Financial.
CoRR
Chaochao Chen, Ziqi Liu, Peilin Zhao, Longfei Li, Jun Zhou, Xiaolong Li
2018 J jnl
Distributed Deep Forest and its Application to Automatic Detection of Cash-out Fraud.
CoRR
Ya-Lin Zhang, Jun Zhou, Wenhao Zheng, Ji Feng, Longfei Li, Ziqi Liu, Ming Li, Zhiqiang Zhang, Chaochao Chen, Xiaolong Li, Zhi-Hua Zhou
2018 J jnl
Feature Propagation on Graph: A New Perspective to Graph Representation Learning.
CoRR
Biao Xiang, Ziqi Liu, Jun Zhou, Xiaolong Li
2018 J jnl
GeniePath: Graph Neural Networks with Adaptive Receptive Paths.
CoRR
Ziqi Liu, Chaochao Chen, Longfei Li, Jun Zhou, Xiaolong Li, Le Song
2018 A conf
Heterogeneous Graph Neural Networks for Malicious Account Detection.
CIKM
Ziqi Liu, Chaochao Chen, Xinxing Yang, Jun Zhou, Xiaolong Li, Le Song
2018 — conf
NetDP: An Industrial-Scale Distributed Network Representation Framework for Default Prediction in Ant Credit Pay.
IEEE BigData
Jianbin Lin, Zhiqiang Zhang, Jun Zhou, Xiaolong Li, Jingli Fang, Yanming Fang, Quan Yu, Yuan (Alan) Qi
2018 A* conf
Privacy Preserving Point-of-Interest Recommendation Using Decentralized Matrix Factorization.
AAAI
Chaochao Chen, Ziqi Liu, Peilin Zhao, Jun Zhou, Xiaolong Li
2018 J jnl
Review Helpfulness Prediction with Embedding-Gated CNN.
CoRR
Cen Chen, Minghui Qiu, Yinfei Yang, Jun Zhou, Jun Huang, Xiaolong Li, Forrest Sheng Bao
2018 J jnl
Time-sensitive Customer Churn Prediction based on PU Learning.
CoRR
Li Wang, Chaochao Chen, Jun Zhou, Xiaolong Li
2018 — conf
Unpack Local Model Interpretation for GBDT.
DASFAA (2)
Wenjing Fang, Jun Zhou, Xiaolong Li, Kenny Q. Zhu
2018 A* conf
cw2vec: Learning Chinese Word Embeddings with Stroke n-gram Information.
AAAI
Shaosheng Cao, Wei Lu, Jun Zhou, Xiaolong Li
2017 — conf
Investigating Stroke-Level Information for Learning Chinese Word Embeddings.
ISWC (Posters, Demos & Industry Tracks)
Shaosheng Cao, Wei Lu, Jun Zhou, Xiaolong Li
2017 A* conf
KunPeng: Parameter Server based Distributed Learning Systems and Its Applications in Alibaba and Ant Financial.
KDD
Jun Zhou, Xiaolong Li, Peilin Zhao, Chaochao Chen, Longfei Li, Xinxing Yang, Qing Cui, Jin Yu, Xu Chen, Yi Ding, Yuan (Alan) Qi
2017 — conf
Large scale app recommendation in Ant Financial.
IEEE BigData
Chaochao Chen, Xinxing Yang, Li Wang, Jun Zhou, Xiaolong Li
2017 — conf
Locally Connected Deep Learning Framework for Industrial-scale Recommender Systems.
WWW (Companion Volume)
Cen Chen, Peilin Zhao, Longfei Li, Jun Zhou, Xiaolong Li, Minghui Qiu
2017 A* conf
Locally Linear Factorization Machines.
IJCAI
Chenghao Liu, Teng Zhang, Peilin Zhao, Jun Zhou, Jianling Sun
2017 A* conf
POSTER: A PU Learning based System for Potential Malicious URL Detection.
CCS
Ya-Lin Zhang, Longfei Li, Jun Zhou, Xiaolong Li, Yujiang Liu, Yuanchao Zhang, Zhi-Hua Zhou
2017 A* conf
POSTER: Actively Detecting Implicit Fraudulent Transactions.
CCS
Shaosheng Cao, Xinxing Yang, Jun Zhou, Xiaolong Li, Yuan (Alan) Qi, Kai Xiao
2017 A* conf
POSTER: Neural Network-based Graph Embedding for Malicious Accounts Detection.
CCS
Ziqi Liu, Chaochao Chen, Jun Zhou, Xiaolong Li, Feng Xu, Tao Chen, Le Song
2017 A* conf
POSTER: Practical Fraud Transaction Prediction.
CCS
Longfei Li, Jun Zhou, Xiaolong Li, Tao Chen
2017 — conf
PSMART: Parameter Server based Multiple Additive Regression Trees System.
WWW (Companion Volume)
Jun Zhou, Qing Cui, Xiaolong Li, Peilin Zhao, Shenquan Qu, Jun Huang
2017 J jnl
Small-footprint Keyword Spotting Using Deep Neural Network and Connectionist Temporal Classifier.
CoRR
Zhiming Wang, Xiaolong Li, Jun Zhou