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2020 – today
- 2025
[j20]Hangyu Wang, Jianghao Lin, Bo Chen, Yang Yang, Ruiming Tang, Weinan Zhang, Yong Yu:
Towards efficient and effective unlearning of large language models for recommendation. Frontiers Comput. Sci. 19(3): 193327 (2025)- [j19]Jianghao Lin, Xinyi Dai, Rong Shan, Bo Chen, Ruiming Tang, Yong Yu, Weinan Zhang:
Large language models make sample-efficient recommender systems. Frontiers Comput. Sci. 19(4): 194328 (2025) - [c151]Wenlin Zhang, Chuhan Wu, Xiangyang Li, Yuhao Wang, Kuicai Dong, Yichao Wang, Xinyi Dai, Xiangyu Zhao, Huifeng Guo, Ruiming Tang:
LLMTreeRec: Unleashing the Power of Large Language Models for Cold-Start Recommendations. COLING 2025: 886-896 - 2024
- [j18]Shiwei Li
, Huifeng Guo, Xing Tang, Ruiming Tang, Lu Hou, Ruixuan Li, Rui Zhang:
Embedding Compression in Recommender Systems: A Survey. ACM Comput. Surv. 56(5): 130:1-130:21 (2024) - [j17]Ziru Liu, Kecheng Chen, Fengyi Song, Bo Chen, Xiangyu Zhao, Huifeng Guo, Ruiming Tang:
AutoAssign+: Automatic Shared Embedding Assignment in streaming recommendation. Knowl. Inf. Syst. 66(1): 89-113 (2024) - [j16]Weitong Ou, Bo Chen, Xinyi Dai, Weinan Zhang, Weiwen Liu, Ruiming Tang, Yong Yu:
A Survey on Bid Optimization in Real-Time Bidding Display Advertising. ACM Trans. Knowl. Discov. Data 18(3): 58:1-58:31 (2024) - [j15]Yunjia Xi, Weiwen Liu, Xinyi Dai, Ruiming Tang, Qing Liu, Weinan Zhang, Yong Yu:
Utility-Oriented Reranking with Counterfactual Context. ACM Trans. Knowl. Discov. Data 18(8): 193:1-193:22 (2024) - [j14]Chang Meng, Ziqi Zhao, Wei Guo, Yingxue Zhang, Haolun Wu, Chen Gao, Dong Li, Xiu Li, Ruiming Tang:
Coarse-to-Fine Knowledge-Enhanced Multi-Interest Learning Framework for Multi-Behavior Recommendation. ACM Trans. Inf. Syst. 42(1): 30:1-30:27 (2024) - [j13]Bo Chen, Xiangyu Zhao, Yejing Wang, Wenqi Fan, Huifeng Guo, Ruiming Tang:
A Comprehensive Survey on Automated Machine Learning for Recommendations. Trans. Recomm. Syst. 2(2): 13:1-13:38 (2024) - [c150]Pengyue Jia, Yichao Wang, Shanru Lin, Xiaopeng Li, Xiangyu Zhao, Huifeng Guo, Ruiming Tang:
D3: A Methodological Exploration of Domain Division, Modeling, and Balance in Multi-Domain Recommendations. AAAI 2024: 8553-8561 - [c149]Yuxin Jiang, Yufei Wang, Chuhan Wu, Wanjun Zhong, Xingshan Zeng, Jiahui Gao, Liangyou Li, Xin Jiang, Lifeng Shang, Ruiming Tang, Qun Liu, Wei Wang:
Learning to Edit: Aligning LLMs with Knowledge Editing. ACL (1) 2024: 4689-4705 - [c148]Jizheng Chen, Kounianhua Du, Jianghao Lin, Bo Chen, Ruiming Tang, Weinan Zhang, Yong Yu:
ELCoRec: Enhance Language Understanding with Co-Propagation of Numerical and Categorical Features for Recommendation. CIKM 2024: 259-269 - [c147]Lingyue Fu, Hao Guan, Kounianhua Du, Jianghao Lin, Wei Xia, Weinan Zhang, Ruiming Tang, Yasheng Wang, Yong Yu:
SINKT: A Structure-Aware Inductive Knowledge Tracing Model with Large Language Model. CIKM 2024: 632-642 - [c146]Jingtong Gao, Bo Chen, Menghui Zhu, Xiangyu Zhao, Xiaopeng Li, Yuhao Wang, Yichao Wang, Huifeng Guo, Ruiming Tang:
HierRec: Scenario-Aware Hierarchical Modeling for Multi-scenario Recommendations. CIKM 2024: 653-662 - [c145]Huanshuo Liu, Bo Chen, Menghui Zhu, Jianghao Lin, Jiarui Qin, Hao Zhang, Yang Yang, Ruiming Tang:
Retrieval-Oriented Knowledge for Click-Through Rate Prediction. CIKM 2024: 1441-1451 - [c144]Yuhao Wang, Yichao Wang, Zichuan Fu, Xiangyang Li, Wanyu Wang, Yuyang Ye, Xiangyu Zhao, Huifeng Guo, Ruiming Tang:
LLM4MSR: An LLM-Enhanced Paradigm for Multi-Scenario Recommendation. CIKM 2024: 2472-2481 - [c143]Yunjia Xi, Weiwen Liu, Jianghao Lin, Bo Chen, Ruiming Tang, Weinan Zhang, Yong Yu:
MemoCRS: Memory-enhanced Sequential Conversational Recommender Systems with Large Language Models. CIKM 2024: 2585-2595 - [c142]Jingsen Zhang, Xiaohe Bo, Chenxi Wang, Quanyu Dai, Zhenhua Dong, Ruiming Tang, Xu Chen:
Active Explainable Recommendation with Limited Labeling Budgets. ICASSP 2024: 5375-5379 - [c141]Kounianhua Du, Jizheng Chen, Jianghao Lin, Yunjia Xi, Hangyu Wang, Xinyi Dai, Bo Chen, Ruiming Tang, Weinan Zhang:
DisCo: Towards Harmonious Disentanglement and Collaboration between Tabular and Semantic Space for Recommendation. KDD 2024: 666-676 - [c140]Pengyue Jia, Yejing Wang, Zhaocheng Du, Xiangyu Zhao, Yichao Wang, Bo Chen, Wanyu Wang, Huifeng Guo, Ruiming Tang:
ERASE: Benchmarking Feature Selection Methods for Deep Recommender Systems. KDD 2024: 5194-5205 - [c139]Yifan Liu, Weiwen Liu, Wei Xia, Jieming Zhu, Weinan Zhang, Zhenhua Dong, Yang Wang, Ruiming Tang, Rui Zhang, Yong Yu:
Multi-sourced Integrated Ranking with Exposure Fairness. PAKDD (5) 2024: 207-218 - [c138]Yunjia Xi, Weiwen Liu, Jianghao Lin, Xiaoling Cai, Hong Zhu, Jieming Zhu, Bo Chen, Ruiming Tang, Weinan Zhang, Yong Yu:
Towards Open-World Recommendation with Knowledge Augmentation from Large Language Models. RecSys 2024: 12-22 - [c137]Hangyu Wang, Jianghao Lin, Xiangyang Li, Bo Chen, Chenxu Zhu, Ruiming Tang, Weinan Zhang, Yong Yu:
FLIP: Fine-grained Alignment between ID-based Models and Pretrained Language Models for CTR Prediction. RecSys 2024: 94-104 - [c136]Yu Liu, Qinglin Jia, Shuting Shi, Chuhan Wu, Zhaocheng Du, Zheng Xie, Ruiming Tang, Muyu Zhang, Ming Li:
Ranking-Aware Unbiased Post-Click Conversion Rate Estimation via AUC Optimization on Entire Exposure Space. RecSys 2024: 360-369 - [c135]Yang Yang, Bo Chen, Chenxu Zhu, Menghui Zhu, Xinyi Dai, Huifeng Guo, Muyu Zhang, Zhenhua Dong, Ruiming Tang:
AIE: Auction Information Enhanced Framework for CTR Prediction in Online Advertising. RecSys 2024: 633-642 - [c134]Hengchang Hu, Wei Guo, Xu Liu, Yong Liu, Ruiming Tang, Rui Zhang, Min-Yen Kan:
User Behavior Enriched Temporal Knowledge Graphs for Sequential Recommendation. WSDM 2024: 266-275 - [c133]Yuhao Wang, Ziru Liu, Yichao Wang, Xiangyu Zhao, Bo Chen, Huifeng Guo, Ruiming Tang:
Diff-MSR: A Diffusion Model Enhanced Paradigm for Cold-Start Multi-Scenario Recommendation. WSDM 2024: 779-787 - [c132]Kexin Zhang, Yichao Wang, Xiu Li, Ruiming Tang, Rui Zhang:
IncMSR: An Incremental Learning Approach for Multi-Scenario Recommendation. WSDM 2024: 939-948 - [c131]Zhaocheng Du, Junhao Chen, Qinglin Jia, Chuhan Wu, Jieming Zhu, Zhenhua Dong, Ruiming Tang:
LightCS: Selecting Quadratic Feature Crosses in Linear Complexity. WWW (Companion Volume) 2024: 38-46 - [c130]Yifan Liu, Wei Xia, Weiwen Liu, Menghui Zhu, Weinan Zhang, Ruiming Tang, Yong Yu:
HiFI: Hierarchical Fairness-aware Integrated Ranking with Constrained Reinforcement Learning. WWW (Companion Volume) 2024: 196-205 - [c129]Junjie Huang, Guohao Cai, Jieming Zhu, Zhenhua Dong, Ruiming Tang, Weinan Zhang, Yong Yu:
Recall-Augmented Ranking: Enhancing Click-Through Rate Prediction Accuracy with Cross-Stage Data. WWW (Companion Volume) 2024: 830-833 - [c128]Jianghao Lin, Bo Chen, Hangyu Wang, Yunjia Xi, Yanru Qu, Xinyi Dai, Kangning Zhang, Ruiming Tang, Yong Yu, Weinan Zhang:
ClickPrompt: CTR Models are Strong Prompt Generators for Adapting Language Models to CTR Prediction. WWW 2024: 3319-3330 - [c127]Jianghao Lin, Rong Shan, Chenxu Zhu, Kounianhua Du, Bo Chen, Shigang Quan, Ruiming Tang, Yong Yu, Weinan Zhang:
ReLLa: Retrieval-enhanced Large Language Models for Lifelong Sequential Behavior Comprehension in Recommendation. WWW 2024: 3497-3508 - [c126]Jiachen Zhu, Yichao Wang, Jianghao Lin, Jiarui Qin, Ruiming Tang, Weinan Zhang, Yong Yu:
M-scan: A Multi-Scenario Causal-driven Adaptive Network for Recommendation. WWW 2024: 3844-3853 - [i137]Qingyao Li, Lingyue Fu, Weiming Zhang, Xianyu Chen, Jingwei Yu, Wei Xia, Weinan Zhang, Ruiming Tang, Yong Yu:
Adapting Large Language Models for Education: Foundational Capabilities, Potentials, and Challenges. CoRR abs/2401.08664 (2024) - [i136]Jiarui Qin, Weiwen Liu, Ruiming Tang, Weinan Zhang, Yong Yu:
D2K: Turning Historical Data into Retrievable Knowledge for Recommender Systems. CoRR abs/2401.11478 (2024) - [i135]Xu Huang, Weiwen Liu, Xiaolong Chen, Xingmei Wang, Hao Wang, Defu Lian, Yasheng Wang, Ruiming Tang, Enhong Chen:
Understanding the planning of LLM agents: A survey. CoRR abs/2402.02716 (2024) - [i134]Dexun Li, Cong Zhang, Kuicai Dong, Derrick-Goh-Xin Deik, Ruiming Tang, Yong Liu:
Aligning Crowd Feedback via Distributional Preference Reward Modeling. CoRR abs/2402.09764 (2024) - [i133]Yuxin Jiang, Yufei Wang, Chuhan Wu, Wanjun Zhong, Xingshan Zeng, Jiahui Gao, Liangyou Li, Xin Jiang, Lifeng Shang, Ruiming Tang, Qun Liu, Wei Wang:
Learning to Edit: Aligning LLMs with Knowledge Editing. CoRR abs/2402.11905 (2024) - [i132]Hangyu Wang, Jianghao Lin, Bo Chen, Yang Yang, Ruiming Tang, Weinan Zhang, Yong Yu:
Towards Efficient and Effective Unlearning of Large Language Models for Recommendation. CoRR abs/2403.03536 (2024) - [i131]Pengyue Jia, Yejing Wang, Zhaocheng Du, Xiangyu Zhao, Yichao Wang, Bo Chen, Wanyu Wang, Huifeng Guo, Ruiming Tang:
ERASE: Benchmarking Feature Selection Methods for Deep Recommender Systems. CoRR abs/2403.12660 (2024) - [i130]Yunjia Xi, Weiwen Liu, Jianghao Lin, Chuhan Wu, Bo Chen, Ruiming Tang, Weinan Zhang, Yong Yu:
Play to Your Strengths: Collaborative Intelligence of Conventional Recommender Models and Large Language Models. CoRR abs/2403.16378 (2024) - [i129]Wenlin Zhang, Chuhan Wu, Xiangyang Li, Yuhao Wang, Kuicai Dong, Yichao Wang, Xinyi Dai, Xiangyu Zhao, Huifeng Guo, Ruiming Tang:
Tired of Plugins? Large Language Models Can Be End-To-End Recommenders. CoRR abs/2404.00702 (2024) - [i128]Xu Huang, Weiwen Liu, Xiaolong Chen, Xingmei Wang, Defu Lian, Yasheng Wang, Ruiming Tang, Enhong Chen:
WESE: Weak Exploration to Strong Exploitation for LLM Agents. CoRR abs/2404.07456 (2024) - [i127]Jiachen Zhu, Yichao Wang, Jianghao Lin, Jiarui Qin, Ruiming Tang, Weinan Zhang, Yong Yu:
M-scan: A Multi-Scenario Causal-driven Adaptive Network for Recommendation. CoRR abs/2404.07581 (2024) - [i126]Junjie Huang, Guohao Cai, Jieming Zhu, Zhenhua Dong, Ruiming Tang, Weinan Zhang, Yong Yu:
Recall-Augmented Ranking: Enhancing Click-Through Rate Prediction Accuracy with Cross-Stage Data. CoRR abs/2404.09578 (2024) - [i125]Huanshuo Liu, Bo Chen, Menghui Zhu, Jianghao Lin, Jiarui Qin, Yang Yang, Hao Zhang, Ruiming Tang:
Retrieval-Oriented Knowledge for Click-Through Rate Prediction. CoRR abs/2404.18304 (2024) - [i124]Kounianhua Du, Renting Rui, Huacan Chai, Lingyue Fu, Wei Xia, Yasheng Wang, Ruiming Tang, Yong Yu, Weinan Zhang:
CodeGRAG: Extracting Composed Syntax Graphs for Retrieval Augmented Cross-Lingual Code Generation. CoRR abs/2405.02355 (2024) - [i123]Xingmei Wang, Weiwen Liu, Xiaolong Chen, Qi Liu, Xu Huang, Defu Lian, Xiangyang Li, Yasheng Wang, Zhenhua Dong, Ruiming Tang:
CELA: Cost-Efficient Language Model Alignment for CTR Prediction. CoRR abs/2405.10596 (2024) - [i122]Qingyao Li, Wei Xia, Kounianhua Du, Qiji Zhang, Weinan Zhang, Ruiming Tang, Yong Yu:
Learning Structure and Knowledge Aware Representation with Large Language Models for Concept Recommendation. CoRR abs/2405.12442 (2024) - [i121]Yuang Zhao, Zhaocheng Du, Qinglin Jia, Linxuan Zhang, Zhenhua Dong, Ruiming Tang:
Retrievable Domain-Sensitive Feature Memory for Multi-Domain Recommendation. CoRR abs/2405.12892 (2024) - [i120]Hao Zhang, Yuyang Zhang, Xiaoguang Li, Wenxuan Shi, Haonan Xu, Huanshuo Liu, Yasheng Wang, Lifeng Shang, Qun Liu, Yong Liu, Ruiming Tang:
Evaluating the External and Parametric Knowledge Fusion of Large Language Models. CoRR abs/2405.19010 (2024) - [i119]Kounianhua Du, Jizheng Chen, Jianghao Lin, Yunjia Xi, Hangyu Wang, Xinyi Dai, Bo Chen, Ruiming Tang, Weinan Zhang:
DisCo: Towards Harmonious Disentanglement and Collaboration between Tabular and Semantic Space for Recommendation. CoRR abs/2406.00011 (2024) - [i118]Kounianhua Du, Jizheng Chen, Jianghao Lin, Menghui Zhu, Bo Chen, Shuai Li, Ruiming Tang:
Extracting Essential and Disentangled Knowledge for Recommendation Enhancement. CoRR abs/2406.00012 (2024) - [i117]Jianghao Lin, Xinyi Dai, Rong Shan, Bo Chen, Ruiming Tang, Yong Yu, Weinan Zhang:
Large Language Models Make Sample-Efficient Recommender Systems. CoRR abs/2406.02368 (2024) - [i116]Jingtong Gao, Bo Chen, Xiangyu Zhao, Weiwen Liu, Xiangyang Li, Yichao Wang, Zijian Zhang, Wanyu Wang, Yuyang Ye, Shanru Lin, Huifeng Guo, Ruiming Tang:
LLM-enhanced Reranking in Recommender Systems. CoRR abs/2406.12433 (2024) - [i115]Yuhao Wang, Yichao Wang, Zichuan Fu, Xiangyang Li, Xiangyu Zhao, Huifeng Guo, Ruiming Tang:
LLM4MSR: An LLM-Enhanced Paradigm for Multi-Scenario Recommendation. CoRR abs/2406.12529 (2024) - [i114]Jizheng Chen, Kounianhua Du, Jianghao Lin, Bo Chen, Ruiming Tang, Weinan Zhang:
ELCoRec: Enhance Language Understanding with Co-Propagation of Numerical and Categorical Features for Recommendation. CoRR abs/2406.18825 (2024) - [i113]Lingyue Fu, Hao Guan, Kounianhua Du, Jianghao Lin, Wei Xia, Weinan Zhang, Ruiming Tang, Yasheng Wang, Yong Yu:
SINKT: A Structure-Aware Inductive Knowledge Tracing Model with Large Language Model. CoRR abs/2407.01245 (2024) - [i112]Xiangyang Li, Kuicai Dong, Yi Quan Lee, Wei Xia, Yichun Yin, Hao Zhang, Yong Liu, Yasheng Wang, Ruiming Tang:
CoIR: A Comprehensive Benchmark for Code Information Retrieval Models. CoRR abs/2407.02883 (2024) - [i111]Yunjia Xi, Weiwen Liu, Jianghao Lin, Bo Chen, Ruiming Tang, Weinan Zhang, Yong Yu:
MemoCRS: Memory-enhanced Sequential Conversational Recommender Systems with Large Language Models. CoRR abs/2407.04960 (2024) - [i110]Mingjia Yin, Chuhan Wu, Yufei Wang, Hao Wang, Wei Guo, Yasheng Wang, Yong Liu, Ruiming Tang, Defu Lian, Enhong Chen:
Entropy Law: The Story Behind Data Compression and LLM Performance. CoRR abs/2407.06645 (2024) - [i109]Bo Chen, Xinyi Dai, Huifeng Guo, Wei Guo, Weiwen Liu, Yong Liu, Jiarui Qin, Ruiming Tang, Yichao Wang, Chuhan Wu, Yaxiong Wu, Hao Zhang:
All Roads Lead to Rome: Unveiling the Trajectory of Recommender Systems Across the LLM Era. CoRR abs/2407.10081 (2024) - [i108]Shiwei Li, Huifeng Guo, Xing Tang, Ruiming Tang, Lu Hou, Ruixuan Li, Rui Zhang:
Embedding Compression in Recommender Systems: A Survey. CoRR abs/2408.02304 (2024) - [i107]Jiachen Zhu, Jianghao Lin, Xinyi Dai, Bo Chen, Rong Shan, Jieming Zhu, Ruiming Tang, Yong Yu, Weinan Zhang:
Lifelong Personalized Low-Rank Adaptation of Large Language Models for Recommendation. CoRR abs/2408.03533 (2024) - [i106]Yunjia Xi, Hangyu Wang, Bo Chen, Jianghao Lin, Menghui Zhu, Weiwen Liu, Ruiming Tang, Weinan Zhang, Yong Yu:
A Decoding Acceleration Framework for Industrial Deployable LLM-based Recommender Systems. CoRR abs/2408.05676 (2024) - [i105]Yusheng Lu, Zhaocheng Du, Xiangyang Li, Xiangyu Zhao, Weiwen Liu, Yichao Wang, Huifeng Guo, Ruiming Tang, Zhenhua Dong, Yongrui Duan:
Prompt Tuning as User Inherent Profile Inference Machine. CoRR abs/2408.06577 (2024) - [i104]Yuxin Jiang, Bo Huang, Yufei Wang, Xingshan Zeng, Liangyou Li, Yasheng Wang, Xin Jiang, Lifeng Shang, Ruiming Tang, Wei Wang:
Bridging and Modeling Correlations in Pairwise Data for Direct Preference Optimization. CoRR abs/2408.07471 (2024) - [i103]Yang Yang, Bo Chen, Chenxu Zhu, Menghui Zhu, Xinyi Dai, Huifeng Guo, Muyu Zhang, Zhenhua Dong, Ruiming Tang:
AIE: Auction Information Enhanced Framework for CTR Prediction in Online Advertising. CoRR abs/2408.07907 (2024) - [i102]Chuhan Wu, Ruiming Tang:
Performance Law of Large Language Models. CoRR abs/2408.09895 (2024) - [i101]Yunjia Xi, Weiwen Liu, Jianghao Lin, Muyan Weng, Xiaoling Cai, Hong Zhu, Jieming Zhu, Bo Chen, Ruiming Tang, Yong Yu, Weinan Zhang:
Efficient and Deployable Knowledge Infusion for Open-World Recommendations via Large Language Models. CoRR abs/2408.10520 (2024) - [i100]Weiwen Liu, Xu Huang, Xingshan Zeng, Xinlong Hao, Shuai Yu, Dexun Li, Shuai Wang, Weinan Gan, Zhengying Liu, Yuanqing Yu, Zezhong Wang, Yuxian Wang, Wu Ning, Yutai Hou, Bin Wang, Chuhan Wu, Xinzhi Wang, Yong Liu, Yasheng Wang, Duyu Tang, Dandan Tu, Lifeng Shang, Xin Jiang, Ruiming Tang, Defu Lian, Qun Liu, Enhong Chen:
ToolACE: Winning the Points of LLM Function Calling. CoRR abs/2409.00920 (2024) - [i99]Qingyao Li, Wei Xia, Kounianhua Du, Xinyi Dai, Ruiming Tang, Yasheng Wang, Yong Yu, Weinan Zhang:
RethinkMCTS: Refining Erroneous Thoughts in Monte Carlo Tree Search for Code Generation. CoRR abs/2409.09584 (2024) - [i98]Qiyuan Zhang, Yufei Wang, Tiezheng Yu, Yuxin Jiang, Chuhan Wu, Liangyou Li, Yasheng Wang, Xin Jiang, Lifeng Shang, Ruiming Tang, Fuyuan Lyu, Chen Ma:
RevisEval: Improving LLM-as-a-Judge via Response-Adapted References. CoRR abs/2410.05193 (2024) - [i97]Muyan Weng, Yunjia Xi, Weiwen Liu, Bo Chen, Jianghao Lin, Ruiming Tang, Weinan Zhang, Yong Yu:
Beyond Positive History: Re-ranking with List-level Hybrid Feedback. CoRR abs/2410.20778 (2024) - [i96]Shuai Wang, Weiwen Liu, Jingxuan Chen, Weinan Gan, Xingshan Zeng, Shuai Yu, Xinlong Hao, Kun Shao, Yasheng Wang, Ruiming Tang:
GUI Agents with Foundation Models: A Comprehensive Survey. CoRR abs/2411.04890 (2024) - [i95]Chenxu Zhu, Shigang Quan, Bo Chen, Jianghao Lin, Xiaoling Cai, Hong Zhu, Xiangyang Li, Yunjia Xi, Weinan Zhang, Ruiming Tang:
LIBER: Lifelong User Behavior Modeling Based on Large Language Models. CoRR abs/2411.14713 (2024) - [i94]Tingjia Shen, Hao Wang, Chuhan Wu, Jin Yao Chin, Wei Guo, Yong Liu, Huifeng Guo, Defu Lian, Ruiming Tang, Enhong Chen:
Predictive Models in Sequential Recommendations: Bridging Performance Laws with Data Quality Insights. CoRR abs/2412.00430 (2024) - [i93]Wei Guo, Hao Wang, Luankang Zhang, Jin Yao Chin, Zhongzhou Liu, Kai Cheng, Qiushi Pan, Yi Quan Lee, Wanqi Xue, Tingjia Shen, Kenan Song, Kefan Wang, Wenjia Xie, Yuyang Ye, Huifeng Guo, Yong Liu, Defu Lian, Ruiming Tang, Enhong Chen:
Scaling New Frontiers: Insights into Large Recommendation Models. CoRR abs/2412.00714 (2024) - [i92]Pengyue Jia, Zhaocheng Du, Yichao Wang, Xiangyu Zhao, Xiaopeng Li, Yuhao Wang, Qidong Liu, Huifeng Guo, Ruiming Tang:
AltFS: Agency-light Feature Selection with Large Language Models in Deep Recommender Systems. CoRR abs/2412.08516 (2024) - [i91]Pengyue Jia, Derong Xu, Xiaopeng Li, Zhaocheng Du, Xiangyang Li, Xiangyu Zhao, Yichao Wang, Yuhao Wang, Huifeng Guo, Ruiming Tang:
Bridging Relevance and Reasoning: Rationale Distillation in Retrieval-Augmented Generation. CoRR abs/2412.08519 (2024) - [i90]Xiaopeng Li, Xiangyang Li, Hao Zhang, Zhaocheng Du, Pengyue Jia, Yichao Wang, Xiangyu Zhao, Huifeng Guo, Ruiming Tang:
SyNeg: LLM-Driven Synthetic Hard-Negatives for Dense Retrieval. CoRR abs/2412.17250 (2024) - [i89]Xiaopeng Li, Jingtong Gao, Pengyue Jia, Yichao Wang, Wanyu Wang, Yejing Wang, Yuhao Wang, Huifeng Guo, Ruiming Tang:
Scenario-Wise Rec: A Multi-Scenario Recommendation Benchmark. CoRR abs/2412.17374 (2024) - [i88]Rong Shan, Jianghao Lin, Chenxu Zhu, Bo Chen, Menghui Zhu, Kangning Zhang, Jieming Zhu, Ruiming Tang, Yong Yu, Weinan Zhang:
An Automatic Graph Construction Framework based on Large Language Models for Recommendation. CoRR abs/2412.18241 (2024) - 2023
- [j12]Chenxu Zhu, Bo Chen, Weinan Zhang, Jincai Lai, Ruiming Tang, Xiuqiang He, Zhenguo Li, Yong Yu:
AIM: Automatic Interaction Machine for Click-Through Rate Prediction. IEEE Trans. Knowl. Data Eng. 35(4): 3389-3403 (2023) - [j11]Haokun Chen, Chenxu Zhu, Ruiming Tang, Weinan Zhang, Xiuqiang He, Yong Yu:
Large-Scale Interactive Recommendation With Tree-Structured Reinforcement Learning. IEEE Trans. Knowl. Data Eng. 35(4): 4018-4032 (2023) - [j10]Jiarui Qin, Weinan Zhang, Rong Su, Zhirong Liu, Weiwen Liu, Guangpeng Zhao, Hao Li, Ruiming Tang, Xiuqiang He, Yong Yu:
Learning to Retrieve User Behaviors for Click-through Rate Estimation. ACM Trans. Inf. Syst. 41(4): 98:1-98:31 (2023) - [c125]Shiwei Li, Huifeng Guo, Lu Hou, Wei Zhang, Xing Tang, Ruiming Tang, Rui Zhang, Ruixuan Li:
Adaptive Low-Precision Training for Embeddings in Click-Through Rate Prediction. AAAI 2023: 4435-4443 - [c124]Yuening Wang, Yingxue Zhang, Antonios Valkanas, Ruiming Tang, Chen Ma, Jianye Hao, Mark Coates:
Structure Aware Incremental Learning with Personalized Imitation Weights for Recommender Systems. AAAI 2023: 4711-4719 - [c123]Xianyu Chen, Jian Shen, Wei Xia, Jiarui Jin, Yakun Song, Weinan Zhang, Weiwen Liu, Menghui Zhu, Ruiming Tang, Kai Dong, Dingyin Xia, Yong Yu:
Set-to-Sequence Ranking-Based Concept-Aware Learning Path Recommendation. AAAI 2023: 5027-5035 - [c122]Bowei He, Xu He, Renrui Zhang, Yingxue Zhang, Ruiming Tang, Chen Ma:
Dynamic Embedding Size Search with Minimum Regret for Streaming Recommender System. CIKM 2023: 741-750 - [c121]Xiaopeng Li, Fan Yan, Xiangyu Zhao, Yichao Wang, Bo Chen, Huifeng Guo, Ruiming Tang:
HAMUR: Hyper Adapter for Multi-Domain Recommendation. CIKM 2023: 1268-1277 - [c120]Qingyao Li, Wei Xia, Li'ang Yin, Jian Shen, Renting Rui, Weinan Zhang, Xianyu Chen, Ruiming Tang, Yong Yu:
Graph Enhanced Hierarchical Reinforcement Learning for Goal-oriented Learning Path Recommendation. CIKM 2023: 1318-1327 - [c119]Qidong Liu, Fan Yan, Xiangyu Zhao, Zhaocheng Du, Huifeng Guo, Ruiming Tang, Feng Tian:
Diffusion Augmentation for Sequential Recommendation. CIKM 2023: 1576-1586 - [c118]Mingjia Yin, Hao Wang, Xiang Xu, Likang Wu, Sirui Zhao, Wei Guo, Yong Liu, Ruiming Tang, Defu Lian, Enhong Chen:
APGL4SR: A Generic Framework with Adaptive and Personalized Global Collaborative Information in Sequential Recommendation. CIKM 2023: 3009-3019 - [c117]Wei Guo, Chenxu Zhu, Fan Yan, Bo Chen, Weiwen Liu, Huifeng Guo, Hongkun Zheng, Yong Liu, Ruiming Tang:
DFFM: Domain Facilitated Feature Modeling for CTR Prediction. CIKM 2023: 4602-4608 - [c116]Weitong Ou, Bo Chen, Weiwen Liu, Xinyi Dai, Weinan Zhang, Wei Xia, Xuan Li, Ruiming Tang, Yong Yu:
Optimal Real-Time Bidding Strategy for Position Auctions in Online Advertising. CIKM 2023: 4766-4772 - [c115]Weiwen Liu, Yunjia Xi, Jiarui Qin, Xinyi Dai, Ruiming Tang, Shuai Li, Weinan Zhang, Rui Zhang:
Personalized Diversification for Neural Re-ranking in Recommendation. ICDE 2023: 802-815 - [c114]Haolun Wu, Yingxue Zhang, Chen Ma, Wei Guo, Ruiming Tang, Xue Liu, Mark Coates:
Intent-aware Multi-source Contrastive Alignment for Tag-enhanced Recommendation. ICDE 2023: 1112-1125 - [c113]Zhicheng He, Weiwen Liu, Wei Guo, Jiarui Qin, Yingxue Zhang, Yaochen Hu, Ruiming Tang:
A Survey on User Behavior Modeling in Recommender Systems. IJCAI 2023: 6656-6664 - [c112]Jianghao Lin, Yanru Qu, Wei Guo, Xinyi Dai, Ruiming Tang, Yong Yu, Weinan Zhang:
MAP: A Model-agnostic Pretraining Framework for Click-through Rate Prediction. KDD 2023: 1384-1395 - [c111]Hangyu Wang, Ting Long, Liang Yin, Weinan Zhang, Wei Xia, Qichen Hong, Dingyin Xia, Ruiming Tang, Yong Yu:
GMOCAT: A Graph-Enhanced Multi-Objective Method for Computerized Adaptive Testing. KDD 2023: 2279-2289 - [c110]Chang Meng, Hengyu Zhang, Wei Guo, Huifeng Guo, Haotian Liu, Yingxue Zhang, Hongkun Zheng, Ruiming Tang, Xiu Li, Rui Zhang:
Hierarchical Projection Enhanced Multi-behavior Recommendation. KDD 2023: 4649-4660 - [c109]Weitong Ou, Bo Chen, Yingxuan Yang, Xinyi Dai, Weiwen Liu, Weinan Zhang, Ruiming Tang, Yong Yu:
Deep Landscape Forecasting in Multi-Slot Real-Time Bidding. KDD 2023: 4685-4695 - [c108]Yunjia Xi, Weiwen Liu, Yang Wang, Ruiming Tang, Weinan Zhang, Yue Zhu, Rui Zhang, Yong Yu:
On-device Integrated Re-ranking with Heterogeneous Behavior Modeling. KDD 2023: 5225-5236 - [c107]Jieming Zhu, Guohao Cai, Junjie Huang, Zhenhua Dong, Ruiming Tang, Weinan Zhang:
ReLoop2: Building Self-Adaptive Recommendation Models via Responsive Error Compensation Loop. KDD 2023: 5728-5738 - [c106]Xu Chen, Jingsen Zhang, Lei Wang, Quanyu Dai, Zhenhua Dong, Ruiming Tang, Rui Zhang, Li Chen, Xin Zhao, Ji-Rong Wen:
REASONER: An Explainable Recommendation Dataset with Comprehensive Labeling Ground Truths. NeurIPS 2023 - [c105]Hao Wang, Jiajun Fan, Zhichao Chen, Haoxuan Li, Weiming Liu, Tianqiao Liu, Quanyu Dai, Yichao Wang, Zhenhua Dong, Ruiming Tang:
Optimal Transport for Treatment Effect Estimation. NeurIPS 2023 - [c104]Jing Wang, Mengchen Zhao, Wei Xia, Zhenhua Dong, Ruiming Tang, Rui Zhang, Jianye Hao, Guangyong Chen, Pheng-Ann Heng:
RLMixer: A Reinforcement Learning Approach for Integrated Ranking with Contrastive User Preference Modeling. PAKDD (3) 2023: 400-413 - [c103]Yujun Li, Xing Tang, Bo Chen, Yimin Huang, Ruiming Tang, Zhenguo Li:
AutoOpt: Automatic Hyperparameter Scheduling and Optimization for Deep Click-through Rate Prediction. RecSys 2023: 183-194 - [c102]Ruiming Tang, Xiaoqiang Zhu, Junfeng Ge, Kuang-chih Lee, Biye Jiang, Xingxing Wang, Han Zhu, Tao Zhuang, Weiwen Liu, Kan Ren, Weinan Zhang, Xiangyu Zhao:
International Workshop on Deep Learning Practice for High-Dimensional Sparse Data with RecSys 2023. RecSys 2023: 1276-1280 - [c101]Weiwen Liu, Wei Guo, Yong Liu, Ruiming Tang, Hao Wang:
User Behavior Modeling with Deep Learning for Recommendation: Recent Advances. RecSys 2023: 1286-1287 - [c100]Chuhan Wu, Qinglin Jia, Zhenhua Dong, Ruiming Tang:
Customer Lifetime Value Prediction: Towards the Paradigm Shift of Recommender System Objectives. RecSys 2023: 1293-1294 - [c99]Yejing Wang, Zhaocheng Du, Xiangyu Zhao, Bo Chen, Huifeng Guo, Ruiming Tang, Zhenhua Dong:
Single-shot Feature Selection for Multi-task Recommendations. SIGIR 2023: 341-351 - [c98]Liangcai Su, Fan Yan, Jieming Zhu, Xi Xiao, Haoyi Duan, Zhou Zhao, Zhenhua Dong, Ruiming Tang:
Beyond Two-Tower Matching: Learning Sparse Retrievable Cross-Interactions for Recommendation. SIGIR 2023: 548-557 - [c97]Jingtong Gao, Xiangyu Zhao, Bo Chen, Fan Yan, Huifeng Guo, Ruiming Tang:
AutoTransfer: Instance Transfer for Cross-Domain Recommendations. SIGIR 2023: 1478-1487 - [c96]Yuhao Wang, Xiangyu Zhao, Bo Chen, Qidong Liu, Huifeng Guo, Huanshuo Liu, Yichao Wang, Rui Zhang, Ruiming Tang:
PLATE: A Prompt-Enhanced Paradigm for Multi-Scenario Recommendations. SIGIR 2023: 1498-1507 - [c95]Jieming Zhu, Qinglin Jia, Guohao Cai, Quanyu Dai, Jingjie Li, Zhenhua Dong, Ruiming Tang, Rui Zhang:
FINAL: Factorized Interaction Layer for CTR Prediction. SIGIR 2023: 2006-2010 - [c94]Zhiheng Zhang, Quanyu Dai, Xu Chen, Zhenhua Dong, Ruiming Tang:
Robust Causal Inference for Recommender System to Overcome Noisy Confounders. SIGIR 2023: 2349-2353 - [c93]Chenxu Zhu, Bo Chen, Huifeng Guo, Hang Xu, Xiangyang Li, Xiangyu Zhao, Weinan Zhang, Yong Yu, Ruiming Tang:
AutoGen: An Automated Dynamic Model Generation Framework for Recommender System. WSDM 2023: 598-606 - [c92]Lingyue Fu, Jianghao Lin, Weiwen Liu, Ruiming Tang, Weinan Zhang, Rui Zhang, Yong Yu:
An F-shape Click Model for Information Retrieval on Multi-block Mobile Pages. WSDM 2023: 1057-1065 - [c91]Yunjia Xi, Jianghao Lin, Weiwen Liu, Xinyi Dai, Weinan Zhang, Rui Zhang, Ruiming Tang, Yong Yu:
A Bird's-eye View of Reranking: From List Level to Page Level. WSDM 2023: 1075-1083 - [c90]Ruiming Tang, Bo Chen, Yejing Wang, Huifeng Guo, Yong Liu, Wenqi Fan, Xiangyu Zhao:
AutoML for Deep Recommender Systems: Fundamentals and Advances. WSDM 2023: 1264-1267 - [c89]Menghui Zhu, Wei Xia, Weiwen Liu, Yifan Liu, Ruiming Tang, Weinan Zhang:
Integrated Ranking for News Feed with Reinforcement Learning. WWW (Companion Volume) 2023: 480-484 - [c88]Xiaofan Liu, Qinglin Jia, Chuhan Wu, Jingjie Li, Quanyu Dai, Lin Bo, Rui Zhang, Ruiming Tang:
Task Adaptive Multi-learner Network for Joint CTR and CVR Estimation. WWW (Companion Volume) 2023: 490-494 - [c87]Wei Guo, Chang Meng, Enming Yuan, Zhicheng He, Huifeng Guo, Yingxue Zhang, Bo Chen, Yaochen Hu, Ruiming Tang, Xiu Li, Rui Zhang:
Compressed Interaction Graph based Framework for Multi-behavior Recommendation. WWW 2023: 960-970 - [c86]Bowei He, Xu He, Yingxue Zhang, Ruiming Tang, Chen Ma:
Dynamically Expandable Graph Convolution for Streaming Recommendation. WWW 2023: 1457-1467 - [i87]Yuhao Wang, Ha Tsz Lam, Yi Wong, Ziru Liu, Xiangyu Zhao, Yichao Wang, Bo Chen, Huifeng Guo, Ruiming Tang:
Multi-Task Deep Recommender Systems: A Survey. CoRR abs/2302.03525 (2023) - [i86]Zhicheng He, Weiwen Liu, Wei Guo, Jiarui Qin, Yingxue Zhang, Yaochen Hu, Ruiming Tang:
A Survey on User Behavior Modeling in Recommender Systems. CoRR abs/2302.11087 (2023) - [i85]Xu Chen, Jingsen Zhang, Lei Wang, Quanyu Dai, Zhenhua Dong, Ruiming Tang, Rui Zhang, Li Chen, Ji-Rong Wen:
REASONER: An Explainable Recommendation Dataset with Multi-aspect Real User Labeled Ground Truths Towards more Measurable Explainable Recommendation. CoRR abs/2303.00168 (2023) - [i84]Wei Guo, Chang Meng, Enming Yuan, Zhicheng He, Huifeng Guo, Yingxue Zhang, Bo Chen, Yaochen Hu, Ruiming Tang, Xiu Li, Rui Zhang:
Compressed Interaction Graph based Framework for Multi-behavior Recommendation. CoRR abs/2303.02418 (2023) - [i83]Bowei He, Xu He, Yingxue Zhang, Ruiming Tang, Chen Ma:
Dynamically Expandable Graph Convolution for Streaming Recommendation. CoRR abs/2303.11700 (2023) - [i82]Yuening Wang, Yingxue Zhang, Antonios Valkanas, Ruiming Tang, Chen Ma, Jianye Hao, Mark Coates:
Structure Aware Incremental Learning with Personalized Imitation Weights for Recommender Systems. CoRR abs/2305.01204 (2023) - [i81]Xiangyang Li, Bo Chen, Lu Hou, Ruiming Tang:
CTRL: Connect Tabular and Language Model for CTR Prediction. CoRR abs/2306.02841 (2023) - [i80]Xianyu Chen, Jian Shen, Wei Xia, Jiarui Jin, Yakun Song, Weinan Zhang, Weiwen Liu, Menghui Zhu, Ruiming Tang, Kai Dong, Dingyin Xia, Yong Yu:
Set-to-Sequence Ranking-based Concept-aware Learning Path Recommendation. CoRR abs/2306.04234 (2023) - [i79]Jianghao Lin, Xinyi Dai, Yunjia Xi, Weiwen Liu, Bo Chen, Xiangyang Li, Chenxu Zhu, Huifeng Guo, Yong Yu, Ruiming Tang, Weinan Zhang:
How Can Recommender Systems Benefit from Large Language Models: A Survey. CoRR abs/2306.05817 (2023) - [i78]Jieming Zhu, Guohao Cai, Junjie Huang, Zhenhua Dong, Ruiming Tang, Weinan Zhang:
ReLoop2: Building Self-Adaptive Recommendation Models via Responsive Error Compensation Loop. CoRR abs/2306.08808 (2023) - [i77]Yunjia Xi, Weiwen Liu, Jianghao Lin, Jieming Zhu, Bo Chen, Ruiming Tang, Weinan Zhang, Rui Zhang, Yong Yu:
Towards Open-World Recommendation with Knowledge Augmentation from Large Language Models. CoRR abs/2306.10933 (2023) - [i76]Chuhan Wu, Jingjie Li, Qinglin Jia, Hong Zhu, Yuan Fang, Ruiming Tang:
Contrastive Multi-view Framework for Customer Lifetime Value Prediction. CoRR abs/2306.14400 (2023) - [i75]Jianghao Lin, Yanru Qu, Wei Guo, Xinyi Dai, Ruiming Tang, Yong Yu, Weinan Zhang:
MAP: A Model-agnostic Pretraining Framework for Click-through Rate Prediction. CoRR abs/2308.01737 (2023) - [i74]Ziru Liu, Kecheng Chen, Fengyi Song, Bo Chen, Xiangyu Zhao, Huifeng Guo, Ruiming Tang:
AutoAssign+: Automatic Shared Embedding Assignment in Streaming Recommendation. CoRR abs/2308.06965 (2023) - [i73]Bowei He, Xu He, Renrui Zhang, Yingxue Zhang, Ruiming Tang, Chen Ma:
Dynamic Embedding Size Search with Minimum Regret for Streaming Recommender System. CoRR abs/2308.07760 (2023) - [i72]Hengyu Zhang, Chang Meng, Wei Guo, Huifeng Guo, Jieming Zhu, Guangpeng Zhao, Ruiming Tang, Xiu Li:
Time-aligned Exposure-enhanced Model for Click-Through Rate Prediction. CoRR abs/2308.09966 (2023) - [i71]Jianghao Lin, Rong Shan, Chenxu Zhu, Kounianhua Du, Bo Chen, Shigang Quan, Ruiming Tang, Yong Yu, Weinan Zhang:
ReLLa: Retrieval-enhanced Large Language Models for Lifelong Sequential Behavior Comprehension in Recommendation. CoRR abs/2308.11131 (2023) - [i70]Jingtong Gao, Bo Chen, Menghui Zhu, Xiangyu Zhao, Xiaopeng Li, Yuhao Wang, Yichao Wang, Huifeng Guo, Ruiming Tang:
Scenario-Aware Hierarchical Dynamic Network for Multi-Scenario Recommendation. CoRR abs/2309.02061 (2023) - [i69]Xiaopeng Li, Fan Yan, Xiangyu Zhao, Yichao Wang, Bo Chen, Huifeng Guo, Ruiming Tang:
HAMUR: Hyper Adapter for Multi-Domain Recommendation. CoRR abs/2309.06217 (2023) - [i68]Qidong Liu, Fan Yan, Xiangyu Zhao, Zhaocheng Du, Huifeng Guo, Ruiming Tang, Feng Tian:
Diffusion Augmentation for Sequential Recommendation. CoRR abs/2309.12858 (2023) - [i67]Zhenhua Dong, Jieming Zhu, Weiwen Liu, Ruiming Tang:
Ten Challenges in Industrial Recommender Systems. CoRR abs/2310.04804 (2023) - [i66]Hangyu Wang, Ting Long, Liang Yin, Weinan Zhang, Wei Xia, Qichen Hong, Dingyin Xia, Ruiming Tang, Yong Yu:
GMOCAT: A Graph-Enhanced Multi-Objective Method for Computerized Adaptive Testing. CoRR abs/2310.07477 (2023) - [i65]Jianghao Lin, Bo Chen, Hangyu Wang, Yunjia Xi, Yanru Qu, Xinyi Dai, Kangning Zhang, Ruiming Tang, Yong Yu, Weinan Zhang:
ClickPrompt: CTR Models are Strong Prompt Generators for Adapting Language Models to CTR Prediction. CoRR abs/2310.09234 (2023) - [i64]Hao Wang, Zhichao Chen, Jiajun Fan, Haoxuan Li, Tianqiao Liu, Weiming Liu, Quanyu Dai, Yichao Wang, Zhenhua Dong, Ruiming Tang:
Optimal Transport for Treatment Effect Estimation. CoRR abs/2310.18286 (2023) - [i63]Hangyu Wang, Jianghao Lin, Xiangyang Li, Bo Chen, Chenxu Zhu, Ruiming Tang, Weinan Zhang, Yong Yu:
ALT: Towards Fine-grained Alignment between Language and CTR Models for Click-Through Rate Prediction. CoRR abs/2310.19453 (2023) - [i62]Mingjia Yin, Hao Wang, Xiang Xu, Likang Wu, Sirui Zhao, Wei Guo, Yong Liu, Ruiming Tang, Defu Lian, Enhong Chen:
APGL4SR: A Generic Framework with Adaptive and Personalized Global Collaborative Information in Sequential Recommendation. CoRR abs/2311.02816 (2023) - [i61]Fuyuan Lyu, Yaochen Hu, Xing Tang, Yingxue Zhang, Ruiming Tang, Xue Liu:
Towards Automated Negative Sampling in Implicit Recommendation. CoRR abs/2311.03526 (2023) - [i60]Liangcai Su, Fan Yan, Jieming Zhu, Xi Xiao, Haoyi Duan, Zhou Zhao, Zhenhua Dong, Ruiming Tang:
Beyond Two-Tower Matching: Learning Sparse Retrievable Cross-Interactions for Recommendation. CoRR abs/2311.18213 (2023) - [i59]Dong Yao, Shengyu Zhang, Zhou Zhao, Jieming Zhu, Liqun Deng, Wenqiao Zhang, Zhenhua Dong, Ruiming Tang, Xin Jiang:
Music-PAW: Learning Music Representations via Hierarchical Part-whole Interaction and Contrast. CoRR abs/2312.06197 (2023) - [i58]Zichuan Fu, Xiangyang Li, Chuhan Wu, Yichao Wang, Kuicai Dong, Xiangyu Zhao, Mengchen Zhao, Huifeng Guo, Ruiming Tang:
A Unified Framework for Multi-Domain CTR Prediction via Large Language Models. CoRR abs/2312.10743 (2023) - 2022
- [j9]Xiangli Yang, Qing Liu, Rong Su, Ruiming Tang, Zhirong Liu, Xiuqiang He, Jianxi Yang:
Click-through rate prediction using transfer learning with fine-tuned parameters. Inf. Sci. 612: 188-200 (2022) - [j8]Niannan Xue, Bin Liu, Huifeng Guo, Ruiming Tang, Fengwei Zhou, Stefanos Zafeiriou, Yuzhou Zhang, Jun Wang, Zhenguo Li:
AutoHash: Learning Higher-Order Feature Interactions for Deep CTR Prediction. IEEE Trans. Knowl. Data Eng. 34(6): 2653-2666 (2022) - [j7]Xinyi Dai, Yunjia Xi, Weinan Zhang, Qing Liu, Ruiming Tang, Xiuqiang He, Jiawei Hou, Jun Wang, Yong Yu:
Beyond Relevance Ranking: A General Graph Matching Framework for Utility-Oriented Learning to Rank. ACM Trans. Inf. Syst. 40(2): 25:1-25:29 (2022) - [c85]Fuyuan Lyu, Xing Tang, Hong Zhu, Huifeng Guo, Yingxue Zhang, Ruiming Tang, Xue Liu:
OptEmbed: Learning Optimal Embedding Table for Click-through Rate Prediction. CIKM 2022: 1399-1409 - [c84]Haolun Wu, Chen Ma, Yingxue Zhang, Xue Liu, Ruiming Tang, Mark Coates:
Adapting Triplet Importance of Implicit Feedback for Personalized Recommendation. CIKM 2022: 2148-2157 - [c83]Hengyu Zhang, Enming Yuan, Wei Guo, Zhicheng He, Jiarui Qin, Huifeng Guo, Bo Chen, Xiu Li, Ruiming Tang:
Disentangling Past-Future Modeling in Sequential Recommendation via Dual Networks. CIKM 2022: 2549-2558 - [c82]Bo Chen, Huifeng Guo, Weiwen Liu, Yue Ding, Yunzhe Li, Wei Guo, Yichao Wang, Zhicheng He, Ruiming Tang, Rui Zhang:
Numerical Feature Representation with Hybrid N-ary Encoding. CIKM 2022: 2984-2993 - [c81]Xiangyang Li, Bo Chen, Huifeng Guo, Jingjie Li, Chenxu Zhu, Xiang Long, Sujian Li, Yichao Wang, Wei Guo, Longxia Mao, Jinxing Liu, Zhenhua Dong, Ruiming Tang:
IntTower: The Next Generation of Two-Tower Model for Pre-Ranking System. CIKM 2022: 3292-3301 - [c80]Quanyu Dai, Yalei Lv, Jieming Zhu, Junjie Ye, Zhenhua Dong, Rui Zhang, Shu-Tao Xia, Ruiming Tang:
LCD: Adaptive Label Correction for Denoising Music Recommendation. CIKM 2022: 3903-3907 - [c79]Wei Xia, Weiwen Liu, Yifan Liu, Ruiming Tang:
Balancing Utility and Exposure Fairness for Integrated Ranking with Reinforcement Learning. CIKM 2022: 4590-4594 - [c78]Ting Long, Yunfei Liu, Weinan Zhang, Wei Xia, Zhicheng He, Ruiming Tang, Yong Yu:
Automatical Graph-based Knowledge Tracing. EDM 2022 - [c77]Wei Guo, Can Zhang, Zhicheng He, Jiarui Qin, Huifeng Guo, Bo Chen, Ruiming Tang, Xiuqiang He, Rui Zhang:
MISS: Multi-Interest Self-Supervised Learning Framework for Click-Through Rate Prediction. ICDE 2022: 727-740 - [c76]Fuyuan Lyu, Xing Tang, Huifeng Guo, Ruiming Tang, Xiuqiang He, Rui Zhang, Xue Liu:
Memorize, Factorize, or be Naive: Learning Optimal Feature Interaction Methods for CTR Prediction. ICDE 2022: 1450-1462 - [c75]Fengyi Song, Bo Chen, Xiangyu Zhao, Huifeng Guo, Ruiming Tang:
AutoAssign: Automatic Shared Embedding Assignment in Streaming Recommendation. ICDM 2022: 458-467 - [c74]Weiwen Liu, Yunjia Xi, Jiarui Qin, Fei Sun, Bo Chen, Weinan Zhang, Rui Zhang, Ruiming Tang:
Neural Re-ranking in Multi-stage Recommender Systems: A Review. IJCAI 2022: 5512-5520 - [c73]Yankai Chen, Yifei Zhang, Huifeng Guo, Ruiming Tang, Irwin King:
An Effective Post-training Embedding Binarization Approach for Fast Online Top-K Passage Matching. AACL/IJCNLP (2) 2022: 102-108 - [c72]Yankai Chen, Huifeng Guo, Yingxue Zhang, Chen Ma, Ruiming Tang, Jingjie Li, Irwin King:
Learning Binarized Graph Representations with Multi-faceted Quantization Reinforcement for Top-K Recommendation. KDD 2022: 168-178 - [c71]Zhicheng He, Wei Xia, Kai Dong, Huifeng Guo, Ruiming Tang, Dingyin Xia, Rui Zhang:
Unsupervised Learning Style Classification for Learning Path Generation in Online Education Platforms. KDD 2022: 2997-3006 - [c70]Yichao Wang, Huifeng Guo, Bo Chen, Weiwen Liu, Zhirong Liu, Qi Zhang, Zhicheng He, Hongkun Zheng, Weiwei Yao, Muyu Zhang, Zhenhua Dong, Ruiming Tang:
CausalInt: Causal Inspired Intervention for Multi-Scenario Recommendation. KDD 2022: 4090-4099 - [c69]Roberto Corizzo, Junfeng Ge, Colin Bellinger, Xiaoqiang Zhu, Paula Branco, Kuang-chih Lee, Nathalie Japkowicz, Ruiming Tang, Tao Zhuang, Han Zhu, Biye Jiang, Jiaxin Mao, Weinan Zhang:
4th Workshop on Deep Learning Practice and Theory for High-Dimensional Sparse and Imbalanced Data with KDD 2022. KDD 2022: 4860-4861 - [c68]Weiwen Liu, Jiarui Qin, Ruiming Tang, Bo Chen:
Neural Re-ranking for Multi-stage Recommender Systems. RecSys 2022: 698-699 - [c67]Jiarui Qin, Jiachen Zhu, Bo Chen, Zhirong Liu, Weiwen Liu, Ruiming Tang, Rui Zhang, Yong Yu, Weinan Zhang:
RankFlow: Joint Optimization of Multi-Stage Cascade Ranking Systems as Flows. SIGIR 2022: 814-824 - [c66]Yunjia Xi, Weiwen Liu, Jieming Zhu, Xilong Zhao, Xinyi Dai, Ruiming Tang, Weinan Zhang, Rui Zhang, Yong Yu:
Multi-Level Interaction Reranking with User Behavior History. SIGIR 2022: 1336-1346 - [c65]Enming Yuan, Wei Guo, Zhicheng He, Huifeng Guo, Chengkai Liu, Ruiming Tang:
Multi-Behavior Sequential Transformer Recommender. SIGIR 2022: 1642-1652 - [c64]Guohao Cai, Jieming Zhu, Quanyu Dai, Zhenhua Dong, Xiuqiang He, Ruiming Tang, Rui Zhang:
ReLoop: A Self-Correction Continual Learning Loop for Recommender Systems. SIGIR 2022: 2692-2697 - [c63]Ting Long, Jiarui Qin, Jian Shen, Weinan Zhang, Wei Xia, Ruiming Tang, Xiuqiang He, Yong Yu:
Improving Knowledge Tracing with Collaborative Information. WSDM 2022: 599-607 - [c62]Lu Wang, Ruiming Tang, Xiaofeng He, Xiuqiang He:
Hierarchical Imitation Learning via Subgoal Representation Learning for Dynamic Treatment Recommendation. WSDM 2022: 1081-1089 - [c61]Yi Li, Jieming Zhu, Weiwen Liu, Liangcai Su, Guohao Cai, Qi Zhang, Ruiming Tang, Xi Xiao, Xiuqiang He:
PEAR: Personalized Re-ranking with Contextualized Transformer for Recommendation. WWW (Companion Volume) 2022: 62-66 - [c60]Riccardo Tommasini, Senjuti Basu Roy, Xuan Wang, Hongwei Wang, Heng Ji, Jiawei Han, Preslav Nakov, Giovanni Da San Martino, Firoj Alam, Markus Schedl, Elisabeth Lex, Akash Bharadwaj, Graham Cormode, Milan Dojchinovski, Jan Forberg, Johannes Frey, Pieter Bonte, Marco Balduini, Matteo Belcao, Emanuele Della Valle, Junliang Yu, Hongzhi Yin, Tong Chen, Haochen Liu, Yiqi Wang, Wenqi Fan, Xiaorui Liu, Jamell Dacon, Lingjuan Lye, Jiliang Tang, Aristides Gionis, Stefan Neumann, Bruno Ordozgoiti, Simon Razniewski, Hiba Arnaout, Shrestha Ghosh, Fabian M. Suchanek, Lingfei Wu, Yu Chen, Yunyao Li, Bang Liu, Filip Ilievski, Daniel Garijo, Hans Chalupsky, Pedro A. Szekely, Ilias Kanellos, Dimitris Sacharidis, Thanasis Vergoulis, Nurendra Choudhary, Nikhil Rao, Karthik Subbian, Srinivasan H. Sengamedu, Chandan K. Reddy, Friedhelm Victor, Bernhard Haslhofer, George Katsogiannis-Meimarakis, Georgia Koutrika, Shengmin Jin, Danai Koutra, Reza Zafarani, Yulia Tsvetkov, Vidhisha Balachandran, Sachin Kumar, Xiangyu Zhao, Bo Chen, Huifeng Guo, Yejing Wang, Ruiming Tang, Yang Zhang, Wenjie Wang, Peng Wu, Fuli Feng, Xiangnan He:
Accepted Tutorials at The Web Conference 2022. WWW (Companion Volume) 2022: 391-399 - [c59]Qi Wan, Xiangnan He, Xiang Wang, Jiancan Wu, Wei Guo, Ruiming Tang:
Cross Pairwise Ranking for Unbiased Item Recommendation. WWW 2022: 2370-2378 - [i57]Weijun Hong, Guilin Li, Weinan Zhang, Ruiming Tang, Yunhe Wang, Zhenguo Li, Yong Yu:
DropNAS: Grouped Operation Dropout for Differentiable Architecture Search. CoRR abs/2201.11679 (2022) - [i56]Weiwen Liu, Yunjia Xi, Jiarui Qin, Fei Sun, Bo Chen, Weinan Zhang, Rui Zhang, Ruiming Tang:
Neural Re-ranking in Multi-stage Recommender Systems: A Review. CoRR abs/2202.06602 (2022) - [i55]Yi Li, Jieming Zhu, Weiwen Liu, Liangcai Su, Guohao Cai, Qi Zhang, Ruiming Tang, Xi Xiao, Xiuqiang He:
PEAR: Personalized Re-ranking with Contextualized Transformer for Recommendation. CoRR abs/2203.12267 (2022) - [i54]Bo Chen, Xiangyu Zhao, Yejing Wang, Wenqi Fan, Huifeng Guo, Ruiming Tang:
Automated Machine Learning for Deep Recommender Systems: A Survey. CoRR abs/2204.01390 (2022) - [i53]Yunjia Xi, Weiwen Liu, Jieming Zhu, Xilong Zhao, Xinyi Dai, Ruiming Tang, Weinan Zhang, Rui Zhang, Yong Yu:
Multi-Level Interaction Reranking with User Behavior History. CoRR abs/2204.09370 (2022) - [i52]Guohao Cai, Jieming Zhu, Quanyu Dai, Zhenhua Dong, Xiuqiang He, Ruiming Tang, Rui Zhang:
ReLoop: A Self-Correction Continual Learning Loop for Recommender Systems. CoRR abs/2204.11165 (2022) - [i51]Qi Wan, Xiangnan He, Xiang Wang, Jiancan Wu, Wei Guo, Ruiming Tang:
Cross Pairwise Ranking for Unbiased Item Recommendation. CoRR abs/2204.12176 (2022) - [i50]Yankai Chen, Huifeng Guo, Yingxue Zhang, Chen Ma, Ruiming Tang, Jingjie Li, Irwin King:
Learning Binarized Graph Representations with Multi-faceted Quantization Reinforcement for Top-K Recommendation. CoRR abs/2206.02115 (2022) - [i49]Lingyue Fu, Jianghao Lin, Weiwen Liu, Ruiming Tang, Weinan Zhang, Rui Zhang, Yong Yu:
An F-shape Click Model for Information Retrieval on Multi-block Mobile Pages. CoRR abs/2206.08604 (2022) - [i48]Jianghao Lin, Weiwen Liu, Xinyi Dai, Weinan Zhang, Shuai Li, Ruiming Tang, Xiuqiang He, Jianye Hao, Yong Yu:
A Graph-Enhanced Click Model for Web Search. CoRR abs/2206.08621 (2022) - [i47]Haolun Wu, Chen Ma, Yingxue Zhang, Xue Liu, Ruiming Tang, Mark Coates:
Adapting Triplet Importance of Implicit Feedback for Personalized Recommendation. CoRR abs/2208.01709 (2022) - [i46]Chang Meng, Ziqi Zhao, Wei Guo, Yingxue Zhang, Haolun Wu, Chen Gao, Dong Li, Xiu Li, Ruiming Tang:
Coarse-to-Fine Knowledge-Enhanced Multi-Interest Learning Framework for Multi-Behavior Recommendation. CoRR abs/2208.01849 (2022) - [i45]Fuyuan Lyu, Xing Tang, Hong Zhu, Huifeng Guo, Yingxue Zhang, Ruiming Tang, Xue Liu:
OptEmbed: Learning Optimal Embedding Table for Click-through Rate Prediction. CoRR abs/2208.04482 (2022) - [i44]Yuxiang Shi, Yue Ding, Bo Chen, Yuyang Huang, Ruiming Tang, Dong Wang:
Task Aligned Meta-learning based Augmented Graph for Cold-Start Recommendation. CoRR abs/2208.05716 (2022) - [i43]Zhenhua Dong, Zhe Wang, Jun Xu, Ruiming Tang, Jirong Wen:
A Brief History of Recommender Systems. CoRR abs/2209.01860 (2022) - [i42]Xiangyang Li, Bo Chen, Huifeng Guo, Jingjie Li, Chenxu Zhu, Xiang Long, Sujian Li, Yichao Wang, Wei Guo, Longxia Mao, Jinxing Liu, Zhenhua Dong, Ruiming Tang:
IntTower: the Next Generation of Two-Tower Model for Pre-Ranking System. CoRR abs/2210.09890 (2022) - [i41]Hengyu Zhang, Enming Yuan, Wei Guo, Zhicheng He, Jiarui Qin, Huifeng Guo, Bo Chen, Xiu Li, Ruiming Tang:
Disentangling Past-Future Modeling in Sequential Recommendation via Dual Networks. CoRR abs/2210.14577 (2022) - [i40]Haolun Wu, Yingxue Zhang, Chen Ma, Wei Guo, Ruiming Tang, Xue Liu, Mark Coates:
Intent-aware Multi-source Contrastive Alignment for Tag-enhanced Recommendation. CoRR abs/2211.06370 (2022) - [i39]Yunjia Xi, Jianghao Lin, Weiwen Liu, Xinyi Dai, Weinan Zhang, Rui Zhang, Ruiming Tang, Yong Yu:
A Bird's-eye View of Reranking: from List Level to Page Level. CoRR abs/2211.09303 (2022) - [i38]Shiwei Li, Huifeng Guo, Lu Hou, Wei Zhang, Xing Tang, Ruiming Tang, Rui Zhang, Ruixuan Li:
Adaptive Low-Precision Training for Embeddings in Click-Through Rate Prediction. CoRR abs/2212.05735 (2022) - 2021
- [j6]Handong Ma, Jiawei Hou, Chenxu Zhu, Weinan Zhang, Ruiming Tang, Jincai Lai, Jieming Zhu, Xiuqiang He, Yong Yu:
QA4PRF: A Question Answering Based Framework for Pseudo Relevance Feedback. IEEE Access 9: 139303-139314 (2021) - [c58]Yue Ding, Yuxiang Shi, Bo Chen, Chenghua Lin, Hongtao Lu, Jie Li, Ruiming Tang, Dong Wang:
Semi-deterministic and Contrastive Variational Graph Autoencoder for Recommendation. CIKM 2021: 382-391 - [c57]Yunzhe Li, Yue Ding, Bo Chen, Xin Xin, Yule Wang, Yuxiang Shi, Ruiming Tang, Dong Wang:
Extracting Attentive Social Temporal Excitation for Sequential Recommendation. CIKM 2021: 998-1007 - [c56]Bo Chen, Yichao Wang, Zhirong Liu, Ruiming Tang, Wei Guo, Hongkun Zheng, Weiwei Yao, Muyu Zhang, Xiuqiang He:
Enhancing Explicit and Implicit Feature Interactions via Information Sharing for Parallel Deep CTR Models. CIKM 2021: 3757-3766 - [c55]Weinan Zhang, Jiarui Qin, Wei Guo, Ruiming Tang, Xiuqiang He:
Deep Learning for Click-Through Rate Estimation. IJCAI 2021: 4695-4703 - [c54]Wei Guo, Rong Su, Renhao Tan, Huifeng Guo, Yingxue Zhang, Zhirong Liu, Ruiming Tang, Xiuqiang He:
Dual Graph enhanced Embedding Neural Network for CTR Prediction. KDD 2021: 496-504 - [c53]Jiarui Qin, Weinan Zhang, Rong Su, Zhirong Liu, Weiwen Liu, Ruiming Tang, Xiuqiang He, Yong Yu:
Retrieval & Interaction Machine for Tabular Data Prediction. KDD 2021: 1379-1389 - [c52]Huifeng Guo, Bo Chen, Ruiming Tang, Weinan Zhang, Zhenguo Li, Xiuqiang He:
An Embedding Learning Framework for Numerical Features in CTR Prediction. KDD 2021: 2910-2918 - [c51]Xiaoqiang Zhu, Kuang-chih Lee, Guorui Zhou, Biye Jiang, Zhe Wang, Ruiming Tang, Kan Ren, Qingyao Ai, Weinan Zhang:
3rd International Workshop on Deep Learning Practice for High-Dimensional Sparse Data with KDD 2021. KDD 2021: 4187-4188 - [c50]Yunfeng Lin, Guilin Li, Xing Zhang, Weinan Zhang, Bo Chen, Ruiming Tang, Zhenguo Li, Jiashi Feng, Yong Yu:
ModularNAS: Towards Modularized and Reusable Neural Architecture Search. MLSys 2021 - [c49]Hang Lai, Jian Shen, Weinan Zhang, Yimin Huang, Xing Zhang, Ruiming Tang, Yong Yu, Zhenguo Li:
On Effective Scheduling of Model-based Reinforcement Learning. NeurIPS 2021: 3694-3705 - [c48]Weinan Zhang, Zhengyu Yang, Jian Shen, Minghuan Liu, Yimin Huang, Xing Zhang, Ruiming Tang, Zhenguo Li:
Learning to Build High-Fidelity and Robust Environment Models. ECML/PKDD (1) 2021: 104-121 - [c47]Jianghao Lin, Weiwen Liu, Xinyi Dai, Weinan Zhang, Shuai Li, Ruiming Tang, Xiuqiang He, Jianye Hao, Yong Yu:
A Graph-Enhanced Click Model for Web Search. SIGIR 2021: 1259-1268 - [c46]Huifeng Guo, Wei Guo, Yong Gao, Ruiming Tang, Xiuqiang He, Wenzhi Liu:
ScaleFreeCTR: MixCache-based Distributed Training System for CTR Models with Huge Embedding Table. SIGIR 2021: 1269-1278 - [c45]Xinyi Dai, Jianghao Lin, Weinan Zhang, Shuai Li, Weiwen Liu, Ruiming Tang, Xiuqiang He, Jianye Hao, Jun Wang, Yong Yu:
An Adversarial Imitation Click Model for Information Retrieval. WWW 2021: 1809-1820 - [i37]Chen Ma, Liheng Ma, Yingxue Zhang, Ruiming Tang, Xue Liu, Mark Coates:
Probabilistic Metric Learning with Adaptive Margin for Top-K Recommendation. CoRR abs/2101.04849 (2021) - [i36]Xinyi Dai, Jianghao Lin, Weinan Zhang, Shuai Li, Weiwen Liu, Ruiming Tang, Xiuqiang He, Jianye Hao, Jun Wang, Yong Yu:
An Adversarial Imitation Click Model for Information Retrieval. CoRR abs/2104.06077 (2021) - [i35]Huifeng Guo, Wei Guo, Yong Gao, Ruiming Tang, Xiuqiang He, Wenzhi Liu:
ScaleFreeCTR: MixCache-based Distributed Training System for CTR Models with Huge Embedding Table. CoRR abs/2104.08542 (2021) - [i34]Weinan Zhang, Jiarui Qin, Wei Guo, Ruiming Tang, Xiuqiang He:
Deep Learning for Click-Through Rate Estimation. CoRR abs/2104.10584 (2021) - [i33]Wei Guo, Rong Su, Renhao Tan, Huifeng Guo, Yingxue Zhang, Zhirong Liu, Ruiming Tang, Xiuqiang He:
Dual Graph enhanced Embedding Neural Network for CTR Prediction. CoRR abs/2106.00314 (2021) - [i32]Xiangli Yang, Qing Liu, Rong Su, Ruiming Tang, Zhirong Liu, Xiuqiang He:
AutoFT: Automatic Fine-Tune for Parameters Transfer Learning in Click-Through Rate Prediction. CoRR abs/2106.04873 (2021) - [i31]Weiwen Liu, Feng Liu, Ruiming Tang, Ben Liao, Guangyong Chen, Pheng-Ann Heng:
Balancing Accuracy and Fairness for Interactive Recommendation with Reinforcement Learning. CoRR abs/2106.13386 (2021) - [i30]Fuyuan Lyu, Xing Tang, Huifeng Guo, Ruiming Tang, Xiuqiang He, Rui Zhang, Xue Liu:
Memorize, Factorize, or be Naïve: Learning Optimal Feature Interaction Methods for CTR Prediction. CoRR abs/2108.01265 (2021) - [i29]Jiarui Qin, Weinan Zhang, Rong Su, Zhirong Liu, Weiwen Liu, Ruiming Tang, Xiuqiang He, Yong Yu:
Retrieval & Interaction Machine for Tabular Data Prediction. CoRR abs/2108.05252 (2021) - [i28]Yunzhe Li, Yue Ding, Bo Chen, Xin Xin, Yule Wang, Yuxiang Shi, Ruiming Tang, Dong Wang:
Extracting Attentive Social Temporal Excitation for Sequential Recommendation. CoRR abs/2109.13539 (2021) - [i27]Yunjia Xi, Weiwen Liu, Xinyi Dai, Ruiming Tang, Weinan Zhang, Qing Liu, Xiuqiang He, Yong Yu:
Context-aware Reranking with Utility Maximization for Recommendation. CoRR abs/2110.09059 (2021) - [i26]Yong Gao, Huifeng Guo, Dandan Lin, Yingxue Zhang, Ruiming Tang, Xiuqiang He:
Content Filtering Enriched GNN Framework for News Recommendation. CoRR abs/2110.12681 (2021) - [i25]Chenxu Zhu, Bo Chen, Weinan Zhang, Jincai Lai, Ruiming Tang, Xiuqiang He, Zhenguo Li, Yong Yu:
AIM: Automatic Interaction Machine for Click-Through Rate Prediction. CoRR abs/2111.03318 (2021) - [i24]Handong Ma, Jiawei Hou, Chenxu Zhu, Weinan Zhang, Ruiming Tang, Jincai Lai, Jieming Zhu, Xiuqiang He, Yong Yu:
QA4PRF: A Question Answering based Framework for Pseudo Relevance Feedback. CoRR abs/2111.08229 (2021) - [i23]Hang Lai, Jian Shen, Weinan Zhang, Yimin Huang, Xing Zhang, Ruiming Tang, Yong Yu, Zhenguo Li:
On Effective Scheduling of Model-based Reinforcement Learning. CoRR abs/2111.08550 (2021) - [i22]Wei Guo, Can Zhang, Zhicheng He, Jiarui Qin, Huifeng Guo, Bo Chen, Ruiming Tang, Xiuqiang He, Rui Zhang:
MISS: Multi-Interest Self-Supervised Learning Framework for Click-Through Rate Prediction. CoRR abs/2111.15068 (2021) - [i21]Yankai Chen, Yifei Zhang, Yingxue Zhang, Huifeng Guo, Jingjie Li, Ruiming Tang, Xiuqiang He, Irwin King:
Towards Low-loss 1-bit Quantization of User-item Representations for Top-K Recommendation. CoRR abs/2112.01944 (2021) - 2020
- [j5]Feng Liu, Ruiming Tang, Huifeng Guo, Xutao Li, Yunming Ye, Xiuqiang He:
Top-aware reinforcement learning based recommendation. Neurocomputing 417: 255-269 (2020) - [j4]Feng Liu, Ruiming Tang, Xutao Li, Weinan Zhang, Yunming Ye, Haokun Chen, Huifeng Guo, Yuzhou Zhang, Xiuqiang He:
State representation modeling for deep reinforcement learning based recommendation. Knowl. Based Syst. 205: 106170 (2020) - [c44]Bo Chen, Wei Guo, Ruiming Tang, Xin Xin, Yue Ding, Xiuqiang He, Dong Wang:
TGCN: Tag Graph Convolutional Network for Tag-Aware Recommendation. CIKM 2020: 155-164 - [c43]Farhan Khawar, Xu Hang, Ruiming Tang, Bin Liu, Zhenguo Li, Xiuqiang He:
AutoFeature: Searching for Feature Interactions and Their Architectures for Click-through Rate Prediction. CIKM 2020: 625-634 - [c42]Weiwen Liu, Qing Liu, Ruiming Tang, Junyang Chen, Xiuqiang He, Pheng-Ann Heng:
Personalized Re-ranking with Item Relationships for E-commerce. CIKM 2020: 925-934 - [c41]Xinyi Dai, Jiawei Hou, Qing Liu, Yunjia Xi, Ruiming Tang, Weinan Zhang, Xiuqiang He, Jun Wang, Yong Yu:
U-rank: Utility-oriented Learning to Rank with Implicit Feedback. CIKM 2020: 2373-2380 - [c40]Yishi Xu, Yingxue Zhang, Wei Guo, Huifeng Guo, Ruiming Tang, Mark Coates:
GraphSAIL: Graph Structure Aware Incremental Learning for Recommender Systems. CIKM 2020: 2861-2868 - [c39]Weijun Hong, Guilin Li, Weinan Zhang, Ruiming Tang, Yunhe Wang, Zhenguo Li, Yong Yu:
DropNAS: Grouped Operation Dropout for Differentiable Architecture Search. IJCAI 2020: 2326-2332 - [c38]Chen Ma, Liheng Ma, Yingxue Zhang, Ruiming Tang, Xue Liu, Mark Coates:
Probabilistic Metric Learning with Adaptive Margin for Top-K Recommendation. KDD 2020: 1036-1044 - [c37]Jianing Sun, Wei Guo, Dengcheng Zhang, Yingxue Zhang, Florence Regol, Yaochen Hu, Huifeng Guo, Ruiming Tang, Han Yuan, Xiuqiang He, Mark Coates:
A Framework for Recommending Accurate and Diverse Items Using Bayesian Graph Convolutional Neural Networks. KDD 2020: 2030-2039 - [c36]Bin Liu, Chenxu Zhu, Guilin Li, Weinan Zhang, Jincai Lai, Ruiming Tang, Xiuqiang He, Zhenguo Li, Yong Yu:
AutoFIS: Automatic Feature Interaction Selection in Factorization Models for Click-Through Rate Prediction. KDD 2020: 2636-2645 - [c35]Weiwen Liu, Feng Liu, Ruiming Tang, Ben Liao, Guangyong Chen, Pheng-Ann Heng:
Balancing Between Accuracy and Fairness for Interactive Recommendation with Reinforcement Learning. PAKDD (1) 2020: 155-167 - [c34]Sijin Zhou, Xinyi Dai, Haokun Chen, Weinan Zhang, Kan Ren, Ruiming Tang, Xiuqiang He, Yong Yu:
Interactive Recommender System via Knowledge Graph-enhanced Reinforcement Learning. SIGIR 2020: 179-188 - [c33]Bin Liu, Niannan Xue, Huifeng Guo, Ruiming Tang, Stefanos Zafeiriou, Xiuqiang He, Zhenguo Li:
AutoGroup: Automatic Feature Grouping for Modelling Explicit High-Order Feature Interactions in CTR Prediction. SIGIR 2020: 199-208 - [c32]Jianing Sun, Yingxue Zhang, Wei Guo, Huifeng Guo, Ruiming Tang, Xiuqiang He, Chen Ma, Mark Coates:
Neighbor Interaction Aware Graph Convolution Networks for Recommendation. SIGIR 2020: 1289-1298 - [c31]Wei Guo, Can Zhang, Huifeng Guo, Ruiming Tang, Xiuqiang He:
Multi-Branch Convolutional Network for Context-Aware Recommendation. SIGIR 2020: 1709-1712 - [c30]Kelong Mao, Xi Xiao, Jieming Zhu, Biao Lu, Ruiming Tang, Xiuqiang He:
Item Tagging for Information Retrieval: A Tripartite Graph Neural Network based Approach. SIGIR 2020: 2327-2336 - [c29]Feng Liu, Huifeng Guo, Xutao Li, Ruiming Tang, Yunming Ye, Xiuqiang He:
End-to-End Deep Reinforcement Learning based Recommendation with Supervised Embedding. WSDM 2020: 384-392 - [c28]Feng Liu, Wei Guo, Huifeng Guo, Ruiming Tang, Yunming Ye, Xiuqiang He:
Dual-attentional Factorization-Machines based Neural Network for User Response Prediction. WWW (Companion Volume) 2020: 26-27 - [i20]Jianing Sun, Yingxue Zhang, Chen Ma, Mark Coates, Huifeng Guo, Ruiming Tang, Xiuqiang He:
Multi-Graph Convolution Collaborative Filtering. CoRR abs/2001.00267 (2020) - [i19]Bin Liu, Chenxu Zhu, Guilin Li, Weinan Zhang, Jincai Lai, Ruiming Tang, Xiuqiang He, Zhenguo Li, Yong Yu:
AutoFIS: Automatic Feature Interaction Selection in Factorization Models for Click-Through Rate Prediction. CoRR abs/2003.11235 (2020) - [i18]Yichao Wang, Xiangyu Zhang, Zhirong Liu, Zhenhua Dong, Xinhua Feng, Ruiming Tang, Xiuqiang He:
Personalized Re-ranking for Improving Diversity in Live Recommender Systems. CoRR abs/2004.06390 (2020) - [i17]Sijin Zhou, Xinyi Dai, Haokun Chen, Weinan Zhang, Kan Ren, Ruiming Tang, Xiuqiang He, Yong Yu:
Interactive Recommender System via Knowledge Graph-enhanced Reinforcement Learning. CoRR abs/2006.10389 (2020) - [i16]Kelong Mao, Xi Xiao, Jieming Zhu, Biao Lu, Ruiming Tang, Xiuqiang He:
Item Tagging for Information Retrieval: A Tripartite Graph Neural Network based Approach. CoRR abs/2008.11567 (2020) - [i15]Yishi Xu, Yingxue Zhang, Wei Guo, Huifeng Guo, Ruiming Tang, Mark Coates:
GraphSAIL: Graph Structure Aware Incremental Learning for Recommender Systems. CoRR abs/2008.13517 (2020) - [i14]Yichao Wang, Huifeng Guo, Ruiming Tang, Zhirong Liu, Xiuqiang He:
A Practical Incremental Method to Train Deep CTR Models. CoRR abs/2009.02147 (2020) - [i13]Xinyi Dai, Jiawei Hou, Qing Liu, Yunjia Xi, Ruiming Tang, Weinan Zhang, Xiuqiang He, Jun Wang, Yong Yu:
U-rank: Utility-oriented Learning to Rank with Implicit Feedback. CoRR abs/2011.00550 (2020) - [i12]Huifeng Guo, Bo Chen, Ruiming Tang, Zhenguo Li, Xiuqiang He:
AutoDis: Automatic Discretization for Embedding Numerical Features in CTR Prediction. CoRR abs/2012.08986 (2020)
2010 – 2019
- 2019
- [j3]Yanru Qu, Bohui Fang, Weinan Zhang, Ruiming Tang, Minzhe Niu, Huifeng Guo, Yong Yu, Xiuqiang He:
Product-Based Neural Networks for User Response Prediction over Multi-Field Categorical Data. ACM Trans. Inf. Syst. 37(1): 5:1-5:35 (2019) - [c27]Haokun Chen, Xinyi Dai, Han Cai, Weinan Zhang, Xuejian Wang, Ruiming Tang, Yuzhou Zhang, Yong Yu:
Large-Scale Interactive Recommendation with Tree-Structured Policy Gradient. AAAI 2019: 3312-3320 - [c26]Jianhua Han, Yong Yu, Feng Liu, Ruiming Tang, Yuzhou Zhang:
Optimizing Ranking Algorithm in Recommender System via Deep Reinforcement Learning. AIAM (IEEE) 2019: 22-26 - [c25]Jianing Sun, Yingxue Zhang, Chen Ma, Mark Coates, Huifeng Guo, Ruiming Tang, Xiuqiang He:
Multi-graph Convolution Collaborative Filtering. ICDM 2019: 1306-1311 - [c24]Huifeng Guo, Ruiming Tang, Yunming Ye, Feng Liu, Yuzhou Zhang:
A Novel KNN Approach for Session-Based Recommendation. PAKDD (2) 2019: 381-393 - [c23]Huifeng Guo, Jinkai Yu, Qing Liu, Ruiming Tang, Yuzhou Zhang:
PAL: a position-bias aware learning framework for CTR prediction in live recommender systems. RecSys 2019: 452-456 - [c22]Wei Guo, Ruiming Tang, Huifeng Guo, Jianhua Han, Wen Yang, Yuzhou Zhang:
Order-aware Embedding Neural Network for CTR Prediction. SIGIR 2019: 1121-1124 - [c21]Bin Liu, Ruiming Tang, Yingzhi Chen, Jinkai Yu, Huifeng Guo, Yuzhou Zhang:
Feature Generation by Convolutional Neural Network for Click-Through Rate Prediction. WWW 2019: 1119-1129 - [i11]Bin Liu, Ruiming Tang, Yingzhi Chen, Jinkai Yu, Huifeng Guo, Yuzhou Zhang:
Feature Generation by Convolutional Neural Network for Click-Through Rate Prediction. CoRR abs/1904.04447 (2019) - 2018
- [c20]Feng Liu, Ruiming Tang, Xutao Li, Yunming Ye, Huifeng Guo, Xiuqiang He:
Novel Approaches to Accelerating the Convergence Rate of Markov Decision Process for Search Result Diversification. DASFAA (2) 2018: 184-200 - [c19]Weiwen Liu, Ruiming Tang, Jiajin Li, Jinkai Yu, Huifeng Guo, Xiuqiang He, Shengyu Zhang:
Field-aware probabilistic embedding neural network for CTR prediction. RecSys 2018: 412-416 - [i10]Feng Liu, Ruiming Tang, Xutao Li, Yunming Ye, Huifeng Guo, Xiuqiang He:
Novel Approaches to Accelerating the Convergence Rate of Markov Decision Process for Search Result Diversification. CoRR abs/1802.08401 (2018) - [i9]Minzhe Niu, Weinan Zhang, Yanru Qu, Xuezhi Cao, Ruiming Tang, Xiuqiang He, Yong Yu:
Collaborative Filtering with Graph-based Implicit Feedback. CoRR abs/1803.03502 (2018) - [i8]Huifeng Guo, Ruiming Tang, Yunming Ye, Zhenguo Li, Xiuqiang He, Zhenhua Dong:
DeepFM: An End-to-End Wide & Deep Learning Framework for CTR Prediction. CoRR abs/1804.04950 (2018) - [i7]Yanru Qu, Bohui Fang, Weinan Zhang, Ruiming Tang, Minzhe Niu, Huifeng Guo, Yong Yu, Xiuqiang He:
Product-based Neural Networks for User Response Prediction over Multi-field Categorical Data. CoRR abs/1807.00311 (2018) - [i6]Huifeng Guo, Ruiming Tang, Yunming Ye, Feng Liu, Yuzhou Zhang:
An Adjustable Heat Conduction based KNN Approach for Session-based Recommendation. CoRR abs/1807.05739 (2018) - [i5]Feng Liu, Ruiming Tang, Xutao Li, Yunming Ye, Haokun Chen, Huifeng Guo, Yuzhou Zhang:
Deep Reinforcement Learning based Recommendation with Explicit User-Item Interactions Modeling. CoRR abs/1810.12027 (2018) - [i4]Haokun Chen, Xinyi Dai, Han Cai, Weinan Zhang, Xuejian Wang, Ruiming Tang, Yuzhou Zhang, Yong Yu:
Large-scale Interactive Recommendation with Tree-structured Policy Gradient. CoRR abs/1811.05869 (2018) - [i3]Qing Liu, Tie Luo, Ruiming Tang, Stéphane Bressan:
An Efficient and Truthful Pricing Mechanism for Team Formation in Crowdsourcing Markets. CoRR abs/1812.04865 (2018) - 2017
- [c18]Huifeng Guo, Ruiming Tang, Yunming Ye, Zhenguo Li, Xiuqiang He:
A Graph-Based Push Service Platform. DASFAA (2) 2017: 636-648 - [c17]Huifeng Guo, Ruiming Tang, Yunming Ye, Zhenguo Li, Xiuqiang He:
DeepFM: A Factorization-Machine based Neural Network for CTR Prediction. IJCAI 2017: 1725-1731 - [c16]Huifeng Guo, Ruiming Tang, Yunming Ye, Xiuqiang He:
Holistic Neural Network for CTR Prediction. WWW (Companion Volume) 2017: 787-788 - [i2]Huifeng Guo, Ruiming Tang, Yunming Ye, Zhenguo Li, Xiuqiang He:
DeepFM: A Factorization-Machine based Neural Network for CTR Prediction. CoRR abs/1703.04247 (2017) - 2016
- [j2]Hong Zhu, Caicai Zhang, Zhongsheng Cao, Ruiming Tang:
On efficient conditioning of probabilistic relational databases. Knowl. Based Syst. 92: 112-126 (2016) - [j1]Ruiming Tang, Antoine Amarilli, Pierre Senellart, Stéphane Bressan:
A Framework for Sampling-Based XML Data Pricing. Trans. Large Scale Data Knowl. Centered Syst. 24: 116-138 (2016) - [i1]Huifeng Guo, Ruiming Tang, Yunming Ye, Zhenguo Li, Xiuqiang He:
A Graph-based Push Service Platform. CoRR abs/1611.09496 (2016) - 2015
- [c15]Xiuqiang He, Wenyuan Dai, Guoxiang Cao, Ruiming Tang, Mingxuan Yuan, Qiang Yang:
Mining target users for online marketing based on App Store data. IEEE BigData 2015: 1043-1052 - [c14]Huayu Wu, Dongxu Shao, Ruiming Tang, Tok Wang Ling, Stéphane Bressan:
Expressing and Processing Path-Centric XML Queries. DEXA (2) 2015: 250-257 - [c13]Qing Liu, Tie Luo, Ruiming Tang, Stéphane Bressan:
An efficient and truthful pricing mechanism for team formation in crowdsourcing markets. ICC 2015: 567-572 - [c12]Ruiming Tang, Huayu Wu, Xiuqiang He, Stéphane Bressan:
Valuating Queries for Data Trading in Modern Cities. ICDM Workshops 2015: 414-421 - 2014
- [c11]Mouhamadou Lamine Ba, Sébastien Montenez, Ruiming Tang, Talel Abdessalem:
Integration of Web Sources Under Uncertainty and Dependencies Using Probabilistic XML. DASFAA Workshops 2014: 360-375 - [c10]Ruiming Tang, Dongxu Shao, Mouhamadou Lamine Ba, Huayu Wu:
Conditioning Probabilistic Relational Data with Referential Constraints. DASFAA Workshops 2014: 413-427 - [c9]Ruiming Tang, Antoine Amarilli, Pierre Senellart, Stéphane Bressan:
Get a Sample for a Discount - Sampling-Based XML Data Pricing. DEXA (1) 2014: 20-34 - [c8]Hong Zhu, Caicai Zhang, Zhongsheng Cao, Ruiming Tang, Mengyuan Yang:
An Efficient Conditioning Method for Probabilistic Relational Databases. WAIM 2014: 225-236 - 2013
- [c7]Huayu Wu, Ruiming Tang, Tok Wang Ling:
Querying Semi-structured Data with Mutual Exclusion. DASFAA (1) 2013: 284-298 - [c6]Ruiming Tang, Huayu Wu, Zhifeng Bao, Stéphane Bressan, Patrick Valduriez:
The Price Is Right - Models and Algorithms for Pricing Data. DEXA (2) 2013: 380-394 - [c5]Ruiming Tang, Dongxu Shao, Stéphane Bressan, Patrick Valduriez:
What You Pay for Is What You Get. DEXA (2) 2013: 395-409 - 2012
- [c4]Huayu Wu, Ruiming Tang, Tok Wang Ling, Yong Zeng, Stéphane Bressan:
A Hybrid Approach for General XML Query Processing. DEXA (1) 2012: 10-25 - [c3]Ruiming Tang, Reynold Cheng, Huayu Wu, Stéphane Bressan:
A Framework for Conditioning Uncertain Relational Data. DEXA (2) 2012: 71-87 - 2011
- [c2]Ruiming Tang, Huayu Wu, Sadegh Nobari, Stéphane Bressan:
Edit Distance between XML and Probabilistic XML Documents. DEXA (1) 2011: 448-456 - [c1]Ruiming Tang, Huayu Wu, Stéphane Bressan:
Measuring XML Structured-ness with Entropy. WAIM Workshops 2011: 113-123
Coauthor Index
[j20] [j19] [j17] [j16] [j13] [c148] [c146] [c145] [c143] [c141] [c140] [c138] [c137] [c135] [c133] [c128] [c127] [i132] [i131] [i130] [i125] [i119] [i118] [i117] [i116] [i114] [i111] [i109] [i107] [i106] [i103] [i101] [i97] [i95] [i88] [j12] [c121] [c117] [c116] [c109] [c103] [c99] [c97] [c96] [c93] [c90] [c87] [i87] [i84] [i81] [i79] [i77] [i74] [i71] [i70] [i69] [i65] [i63] [c83] [c82] [c81] [c77] [c75] [c74] [c70] [c68] [c67] [c60] [i56] [i54] [i44] [i42] [i41] [c58] [c57] [c56] [c52] [c50] [i28] [i25] [i22] [c44] [i12]
[c151] [j18] [j17] [j13] [c150] [c146] [c144] [c140] [c135] [c133] [i131] [i129] [i116] [i115] [i109] [i108] [i105] [i103] [i94] [i93] [i92] [i91] [i90] [i89] [c125] [c121] [c119] [c117] [c110] [c99] [c97] [c96] [c93] [c90] [c87] [i87] [i84] [i79] [i74] [i72] [i70] [i69] [i68] [i58] [j8] [c85] [c83] [c82] [c81] [c77] [c76] [c75] [c73] [c72] [c71] [c70] [c65] [c60] [i54] [i50] [i45] [i42] [i41] [i38] [c54] [c52] [c46] [i35] [i33] [i30] [i26] [i22] [i21] [j5] [j4] [c40] [c37] [c33] [c32] [c31] [c29] [c28] [i20] [i15] [i14] [i12] [j3] [c25] [c24] [c23] [c22] [c21] [i11] [c20] [c19] [i10] [i8] [i7] [i6] [i5] [c18] [c17] [c16] [i2] [i1]
[j12] [j11] [j10] [j9] [j7] [c77] [c76] [c64] [c63] [c62] [c61] [i55] [i52] [i48] [j6] [c56] [c55] [c54] [c53] [c52] [c47] [c46] [c45] [i36] [i35] [i34] [i33] [i32] [i30] [i29] [i27] [i26] [i25] [i24] [i22] [i21] [j5] [j4] [c44] [c43] [c42] [c41] [c37] [c36] [c34] [c33] [c32] [c31] [c30] [c29] [c28] [i20] [i19] [i18] [i17] [i16] [i14] [i13] [i12] [j3] [c25] [c20] [c19] [i10] [i9] [i8] [i7] [c18] [c17] [c16] [i2] [i1] [c15] [c12]
[j16] [j15] [c143] [c139] [c138] [c130] [i136] [i135] [i130] [i128] [i123] [i116] [i111] [i109] [i106] [i105] [i101] [i100] [i97] [i96] [j10] [c123] [c117] [c116] [c115] [c113] [c109] [c108] [c102] [c101] [c92] [c91] [c89] [i86] [i80] [i79] [i77] [i67] [c82] [c79] [c74] [c70] [c68] [c67] [c66] [c61] [i56] [i55] [i53] [i49] [i48] [i39] [c53] [c47] [c45] [i36] [i31] [i29] [i27] [c42] [c35] [c19]
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[j20] [j19] [j16] [j15] [c148] [c147] [c143] [c141] [c139] [c138] [c137] [c130] [c129] [c128] [c127] [c126] [i137] [i136] [i132] [i130] [i127] [i126] [i124] [i122] [i119] [i117] [i114] [i113] [i111] [i107] [i106] [i101] [i99] [i97] [i95] [i88] [j12] [j11] [j10] [c123] [c120] [c116] [c115] [c112] [c111] [c109] [c108] [c107] [c102] [c93] [c92] [c91] [c89] [i80] [i79] [i78] [i77] [i75] [i71] [i66] [i65] [i63] [j7] [c78] [c74] [c69] [c67] [c66] [c63] [i57] [i56] [i53] [i49] [i48] [i39] [j6] [c55] [c53] [c52] [c51] [c50] [c49] [c48] [c47] [c45] [i36] [i34] [i29] [i27] [i25] [i24] [i23] [j4] [c41] [c39] [c36] [c34] [i19] [i17] [i13] [j3] [c27] [i9] [i7] [i4]
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