Recommendation With Social Roles. - Dugang Liu; Jie Huang; Chen Lin 001 (IEEE Access, 2018)

Spiral of Silence in Recommender Systems. - Dugang Liu; Chen Lin 001; Zhilin Zhang 001; Yanghua Xiao; Hanghang Tong (WSDM, 2019)

A General Knowledge Distillation Framework for Counterfactual Recommendation via Uniform Data. - Dugang Liu; Pengxiang Cheng 002; Zhenhua Dong; Xiuqiang He 001; Weike Pan; Zhong Ming 001 (SIGIR, 2020)

Transfer Learning in Collaborative Recommendation for Bias Reduction. - Zinan Lin 004; Dugang Liu; Weike Pan; Zhong Ming 001 (RecSys, 2021)

Mitigating Confounding Bias in Recommendation via Information Bottleneck. - Dugang Liu; Pengxiang Cheng 002; Hong Zhu 003; Zhenhua Dong; Xiuqiang He 001; Weike Pan; Zhong Ming 001 (RecSys, 2021)

Augmenting Legal Judgment Prediction with Contrastive Case Relations. - Dugang Liu; Weihao Du; Lei Li 042; Weike Pan; Zhong Ming 001 (COLING, 2022)

ALTRec: Adversarial Learning for Autoencoder-based Tail Recommendation. - Jixiong Liu; Dugang Liu; Weike Pan; Zhong Ming 001 (DSAA, 2022)

SQL-Rank++: A Novel Listwise Approach for Collaborative Ranking with Implicit Feedback. - Zheng Yuan; Dugang Liu; Weike Pan; Zhong Ming 001 (IJCNN, 2022)

User-Event Graph Embedding Learning for Context-Aware Recommendation. - Dugang Liu; Mingkai He; Jinwei Luo; Jiangxu Lin; Meng Wang 009; Xiaolian Zhang; Weike Pan; Zhong Ming 001 (KDD, 2022)

Spiral of Silence and Its Application in Recommender Systems. - Chen Lin 001; Dugang Liu; Hanghang Tong; Yanghua Xiao (IEEE Trans. Knowl. Data Eng., 2022)

Self-Sampling Training and Evaluation for the Accuracy-Bias Tradeoff in Recommendation. - Dugang Liu; Yang Qiao; Xing Tang 007; Liang Chen 009; Xiuqiang He 001; Weike Pan; Zhong Ming 001 (DASFAA (4), 2023)

Robustness-enhanced Uplift Modeling with Adversarial Feature Desensitization. - Zexu Sun; Bowei He; Ming Ma; Jiakai Tang; Yuchen Wang; Chen Ma 001; Dugang Liu (ICDM, 2023)

Explicit Feature Interaction-aware Uplift Network for Online Marketing. - Dugang Liu; Xing Tang 007; Han Gao; Fuyuan Lyu; Xiuqiang He 001 (KDD, 2023)

Prior-Guided Accuracy-Bias Tradeoff Learning for CTR Prediction in Multimedia Recommendation. - Dugang Liu; Yang Qiao; Xing Tang 007; Liang Chen 009; Xiuqiang He 001; Zhong Ming 001 (ACM Multimedia, 2023)

Towards Hybrid-grained Feature Interaction Selection for Deep Sparse Network. - Fuyuan Lyu; Xing Tang 007; Dugang Liu; Chen Ma 001; Weihong Luo; Liang Chen 009; Xiuqiang He 001; Xue (Steve) Liu (NeurIPS, 2023)

OptMSM: Optimizing Multi-Scenario Modeling for Click-Through Rate Prediction. - Xing Tang 007; Yang Qiao; Yuwen Fu; Fuyuan Lyu; Dugang Liu; Xiuqiang He 001 (ECML/PKDD (6), 2023)

Pairwise Intent Graph Embedding Learning for Context-Aware Recommendation. - Dugang Liu; Yuhao Wu; Weixin Li; Xiaolian Zhang; Hao Wang 140; Qinjuan Yang; Zhong Ming 001 (RecSys, 2023)

DIWIFT: Discovering Instance-wise Influential Features for Tabular Data. - Dugang Liu; Pengxiang Cheng 002; Hong Zhu 003; Xing Tang 007; Yanyu Chen; Xiaoting Wang; Weike Pan; Zhong Ming 001; Xiuqiang He 001 (WWW, 2023)

Optimizing Feature Set for Click-Through Rate Prediction. - Fuyuan Lyu; Xing Tang 007; Dugang Liu; Liang Chen 009; Xiuqiang He 001; Xue Liu 001 (WWW, 2023)

Feature Representation Learning for Click-through Rate Prediction: A Review and New Perspectives. - Fuyuan Lyu; Xing Tang 007; Dugang Liu; Haolun Wu; Chen Ma 001; Xiuqiang He 001; Xue Liu 001 (CoRR, 2023)

Debiased Representation Learning in Recommendation via Information Bottleneck. - Dugang Liu; Pengxiang Cheng 002; Hong Zhu 003; Zhenhua Dong; Xiuqiang He 001; Weike Pan; Zhong Ming 001 (Trans. Recomm. Syst., 2023)

KDCRec: Knowledge Distillation for Counterfactual Recommendation via Uniform Data. - Dugang Liu; Pengxiang Cheng 002; Zinan Lin 004; Jinwei Luo; Zhenhua Dong; Xiuqiang He 001; Weike Pan; Zhong Ming 001 (IEEE Trans. Knowl. Data Eng., 2023)

Bounding System-Induced Biases in Recommender Systems with a Randomized Dataset. - Dugang Liu; Pengxiang Cheng 002; Zinan Lin 004; Xiaolian Zhang; Zhenhua Dong; Rui Zhang 003; Xiuqiang He 001; Weike Pan; Zhong Ming 001 (ACM Trans. Inf. Syst., 2023)

Transfer learning for collaborative recommendation with biased and unbiased data. - Zinan Lin 004; Dugang Liu; Weike Pan; Qiang Yang 001; Zhong Ming 001 (Artif. Intell., 2023)

A Cooperative Co-Evolution Algorithm with Variable-Importance Grouping for Large-Scale Optimization. - Yongfeng Li; Yuze Zhang; Lijia Ma; Junkai Ji; Dugang Liu; Victor C. M. Leung; Jianqiang Li 001 (CEC, 2024)

OptDist: Learning Optimal Distribution for Customer Lifetime Value Prediction. - Yunpeng Weng; Xing Tang 007; Zhenhao Xu; Fuyuan Lyu; Dugang Liu; Zexu Sun; Xiuqiang He 001 (CIKM, 2024)

Large Language Models for Generative Recommendation: A Survey and Visionary Discussions. - Lei Li 042; Yongfeng Zhang; Dugang Liu; Li Chen 009 (LREC/COLING, 2024)

Towards Effective and Efficient Multi-valued Treatment Uplift Modeling in Online Marketing. - Zexu Sun; Dugang Liu; Xing Tang 007; Yunpeng Weng; Xiuqiang He 001 (DASFAA (7), 2024)

Masked Random Noise for Communication-Efficient Federated Learning. - Shiwei Li 002; Yingyi Cheng; Haozhao Wang; Xing Tang 007; Shijie Xu; Weihong Luo; Yuhua Li 003; Dugang Liu; Xiuqiang He 001; Ruixuan Li 001 (ACM Multimedia, 2024)

Touch the Core: Exploring Task Dependence Among Hybrid Targets for Recommendation. - Xing Tang 007; Yang Qiao; Fuyuan Lyu; Dugang Liu; Xiuqiang He 001 (RecSys, 2024)

End-to-End Cost-Effective Incentive Recommendation under Budget Constraint with Uplift Modeling. - Zexu Sun; Hao Yang 045; Dugang Liu; Yunpeng Weng; Xing Tang 007; Xiuqiang He 001 (RecSys, 2024)

AutoDCS: Automated Decision Chain Selection in Deep Recommender Systems. - Dugang Liu; Shenxian Xian; Yuhao Wu; Chaohua Yang; Xing Tang 007; Xiuqiang He 001; Zhong Ming 001 (SIGIR, 2024)

MultiFS: Automated Multi-Scenario Feature Selection in Deep Recommender Systems. - Dugang Liu; Chaohua Yang; Xing Tang 007; Yejing Wang; Fuyuan Lyu; Weihong Luo; Xiuqiang He 001; Zhong Ming 001; Xiangyu Zhao 001 (WSDM, 2024)

Expected Transaction Value Optimization for Precise Marketing in FinTech Platforms. - Yunpeng Weng; Xing Tang 007; Liang Chen 009; Dugang Liu; Xiuqiang He 001 (CoRR, 2024)

A Practice-Friendly Two-Stage LLM-Enhanced Paradigm in Sequential Recommendation. - Dugang Liu; Shenxian Xian; Xiaolin Lin; Xiaolian Zhang; Hong Zhu 003; Yuan Fang; Zhen Chen; Zhong Ming 001 (CoRR, 2024)

Benchmarking for Deep Uplift Modeling in Online Marketing. - Dugang Liu; Xing Tang 007; Yang Qiao; Miao Liu 006; Zexu Sun; Xiuqiang He 001; Zhong Ming 001 (CoRR, 2024)

Masked Random Noise for Communication Efficient Federaetd Learning. - Shiwei Li 002; Yingyi Cheng; Haozhao Wang; Xing Tang 007; Shijie Xu; Weihong Luo; Yuhua Li 003; Dugang Liu; Xiuqiang He 001; Ruixuan Li 001 (CoRR, 2024)

End-to-End Cost-Effective Incentive Recommendation under Budget Constraint with Uplift Modeling. - Zexu Sun; Hao Yang; Dugang Liu; Yunpeng Weng; Xing Tang 007; Xiuqiang He 001 (CoRR, 2024)

Automatically Inspecting Thousands of Static Bug Warnings with Large Language Model: How Far Are We? - Cheng Wen 002; Yuandao Cai; Bin Zhang; Jie Su 002; Zhiwu Xu 001; Dugang Liu; Shengchao Qin; Zhong Ming 001; Cong Tian (ACM Trans. Knowl. Discov. Data, 2024)

Teaching content recommendations in music appreciation courses via graph embedding learning. - Dugang Liu; Xiaolin Lin; Lingjie Li; Zishan Ming (Int. J. Mach. Learn. Cybern., 2024)

Scenario Shared Instance Modeling for Click-through Rate Prediction. - Dugang Liu; Chaohua Yang; Yuwen Fu; Xing Tang 007; Gongfu Li; Fuyuan Lyu; Xiuqiang He 001; Zhong Ming 001 (KDD (1), 2025)

Robust Uplift Modeling with Large-Scale Contexts for Real-time Marketing. - Zexu Sun; Qiyu Han; Minqin Zhu; Hao Gong; Dugang Liu; Chen Ma 001 (KDD (1), 2025)

Comprehending Knowledge Graphs with Large Language Models for Recommender Systems. - Ziqiang Cui; Yunpeng Weng; Xing Tang 007; Fuyuan Lyu; Dugang Liu; Xiuqiang He 001; Chen Ma 001 (SIGIR, 2025)

Multi-scenario Instance Embedding Learning for Deep Recommender Systems. - Chaohua Yang; Dugang Liu; Xing Tang 007; Yuwen Fu; Xiuqiang He 001; Xiangyu Zhao 001; Zhong Ming 001 (SIGIR, 2025)

Fusion Matters: Learning Fusion in Deep Click-through Rate Prediction Models. - Kexin Zhang 007; Fuyuan Lyu; Xing Tang 007; Dugang Liu; Chen Ma 001; Kaize Ding; Xiuqiang He 001; Xue Liu 001 (WSDM, 2025)

A Predict-Then-Optimize Customer Allocation Framework for Online Fund Recommendation. - Xing Tang 007; Yunpeng Weng; Fuyuan Lyu; Dugang Liu; Xiuqiang He 001 (CoRR, 2025)

Semantic Retrieval Augmented Contrastive Learning for Sequential Recommendation. - Ziqiang Cui; Yunpeng Weng; Xing Tang 007; Xiaokun Zhang 001; Dugang Liu; Shiwei Li 002; Peiyang Liu; Bowei He; Weihong Luo; Xiuqiang He 001; Chen Ma 001 (CoRR, 2025)

BoRA: Towards More Expressive Low-Rank Adaptation with Block Diversity. - Shiwei Li 002; Xiandi Luo; Haozhao Wang; Xing Tang 007; Ziqiang Cui; Dugang Liu; Yuhua Li 003; Xiuqiang He 001; Ruixuan Li 001 (CoRR, 2025)

Pairwise Intent Graph Embedding Learning for Context-aware Recommendation with Knowledge Graph. - Dugang Liu; Shenxian Xian; Yuhao Wu; Xiaolian Zhang; Zhong Ming 001 (Trans. Recomm. Syst., 2025)