| 2026 | ACL | HSUGA: LLM-Enhanced Recommendation with Hierarchical Semantic Understanding and Group-Aware Alignment. | Guorui Li, Dugang Liu, Lei Li, Xing Tang, Zhong Ming |
| 2026 | ACL | Learning from Cognition: Enhancing RL Efficiency for LLM Reasoning via Hierarchical Metacognitive Decomposition and Refinement. | Zexu Sun, Yongcheng Zeng, Erxue Min, Heyang Gao, Bokai Ji, Dugang Liu, Xing Tang, Xiuqiang He, Xu Chen |
| 2026 | ACL | Formally Specifying the Intended Behavior of the Program: LLM-Driven Neuro-Symbolic Program Specification Synthesis. | Cheng Wen, Junjie Hu, YiKun Hu, Jie Su, Bin Yu, Dugang Liu, Zhiwu Xu, Weidi Sun, Shengchao Qin, Cong Tian |
| 2026 | WWW | Data-Driven Function Calling Improvements in Large Language Model for Online Financial QA. | Xing Tang, Hao Chen, Shiwei Li, Fuyuan Lyu, Weijie Shi, Lingjie Li, Dugang Liu, Weihong Luo, Xiku Du, Xiuqiang He |
| 2026 | SIGIR | FedMM: Federated Collaborative Signal Quantization for Multi-Market CTR Prediction. | Jun Zhang, Dugang Liu, Xing Tang, Xiuqiang He, Zhong Ming |
| 2026 | WSDM | Automated Information Flow Selection for Multi-scenario Multi-task Recommendation. | Chaohua Yang, Dugang Liu, Shiwei Li, Yuwen Fu, Xing Tang, Weihong Luo, Xiangyu Zhao, Xiuqiang He, Zhong Ming |
| 2026 | TASE | Enhancing LLM-Based Proof Synthesis for Rust Programs via Semantic Chunking and Hierarchical Context Expansion. | Yuchen Zhang, Cheng Wen, Zhiwu Xu, Dugang Liu, Jialun Cao, Yuwei Liu, Shengchao Qin, Cong Tian |
| 2025 | DASFAA | A Predict-Then-Optimize Customer Allocation Framework for Online Fund Recommendation. | Xing Tang, Yunpeng Weng, Fuyuan Lyu, Dugang Liu, Xiuqiang He |
| 2025 | ICML | Invariant Deep Uplift Modeling for Incentive Assignment in Online Marketing via Probability of Necessity and Sufficiency. | Zexu Sun, Qiyu Han, Hao Yang, Anpeng Wu, Minqin Zhu, Dugang Liu, Chen Ma, Yunpeng Weng, Xing Tang, Xiuqiang He |
| 2025 | KDD | Retrieval Augmented Cross-Domain LifeLong Behavior Modeling for Enhancing Click-through Rate Prediction. | Xing Tang, Chaohua Yang, Yuwen Fu, Dongyang Ao, Shiwei Li, Fuyuan Lyu, Dugang Liu, Xiuqiang He |
| 2025 | KDD | Scenario Shared Instance Modeling for Click-through Rate Prediction. | Dugang Liu, Chaohua Yang, Yuwen Fu, Xing Tang, Gongfu Li, Fuyuan Lyu, Xiuqiang He, Zhong Ming |
| 2025 | KDD | Robust Uplift Modeling with Large-Scale Contexts for Real-time Marketing. | Zexu Sun, Qiyu Han, Minqin Zhu, Hao Gong, Dugang Liu, Chen Ma |
| 2025 | KSEM | Masked Aggregation Learning for Enhancing Distributed Gradient Boosting Decision Trees. | Yuting Zha, Chao Lin, Xinyi Huang, Dugang Liu |
| 2025 | SIGIR | Comprehending Knowledge Graphs with Large Language Models for Recommender Systems. | Ziqiang Cui, Yunpeng Weng, Xing Tang, Fuyuan Lyu, Dugang Liu, Xiuqiang He, Chen Ma |
| 2025 | SIGIR | Multi-scenario Instance Embedding Learning for Deep Recommender Systems. | Chaohua Yang, Dugang Liu, Xing Tang, Yuwen Fu, Xiuqiang He, Xiangyu Zhao, Zhong Ming |
| 2025 | WSDM | Fusion Matters: Learning Fusion in Deep Click-through Rate Prediction Models. | Kexin Zhang, Fuyuan Lyu, Xing Tang, Dugang Liu, Chen Ma, Kaize Ding, Xiuqiang He, Xue Liu |
| 2024 | CEC | 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 |
| 2024 | CIKM | OptDist: Learning Optimal Distribution for Customer Lifetime Value Prediction. | Yunpeng Weng, Xing Tang, Zhenhao Xu, Fuyuan Lyu, Dugang Liu, Zexu Sun, Xiuqiang He |
| 2024 | COLING | Large Language Models for Generative Recommendation: A Survey and Visionary Discussions. | Lei Li, Yongfeng Zhang, Dugang Liu, Li Chen |
| 2024 | DASFAA | Towards Effective and Efficient Multi-valued Treatment Uplift Modeling in Online Marketing. | Zexu Sun, Dugang Liu, Xing Tang, Yunpeng Weng, Xiuqiang He |
| 2024 | RecSys | Touch the Core: Exploring Task Dependence Among Hybrid Targets for Recommendation. | Xing Tang, Yang Qiao, Fuyuan Lyu, Dugang Liu, Xiuqiang He |
| 2024 | RecSys | End-to-End Cost-Effective Incentive Recommendation under Budget Constraint with Uplift Modeling. | Zexu Sun, Hao Yang, Dugang Liu, Yunpeng Weng, Xing Tang, Xiuqiang He |
| 2024 | SIGIR | AutoDCS: Automated Decision Chain Selection in Deep Recommender Systems. | Dugang Liu, Shenxian Xian, Yuhao Wu, Chaohua Yang, Xing Tang, Xiuqiang He, Zhong Ming |
| 2024 | WSDM | MultiFS: Automated Multi-Scenario Feature Selection in Deep Recommender Systems. | Dugang Liu, Chaohua Yang, Xing Tang, Yejing Wang, Fuyuan Lyu, Weihong Luo, Xiuqiang He, Zhong Ming, Xiangyu Zhao |
| 2023 | DASFAA | Self-Sampling Training and Evaluation for the Accuracy-Bias Tradeoff in Recommendation. | Dugang Liu, Yang Qiao, Xing Tang, Liang Chen, Xiuqiang He, Weike Pan, Zhong Ming |
| 2023 | ICDM | Robustness-enhanced Uplift Modeling with Adversarial Feature Desensitization. | Zexu Sun, Bowei He, Ming Ma, Jiakai Tang, Yuchen Wang, Chen Ma, Dugang Liu |
| 2023 | KDD | Explicit Feature Interaction-aware Uplift Network for Online Marketing. | Dugang Liu, Xing Tang, Han Gao, Fuyuan Lyu, Xiuqiang He |
| 2023 | RecSys | Pairwise Intent Graph Embedding Learning for Context-Aware Recommendation. | Dugang Liu, Yuhao Wu, Weixin Li, Xiaolian Zhang, Hao Wang, Qinjuan Yang, Zhong Ming |
| 2023 | WWW | DIWIFT: Discovering Instance-wise Influential Features for Tabular Data. | Dugang Liu, Pengxiang Cheng, Hong Zhu, Xing Tang, Yanyu Chen, Xiaoting Wang, Weike Pan, Zhong Ming, Xiuqiang He |
| 2023 | WWW | Optimizing Feature Set for Click-Through Rate Prediction. | Fuyuan Lyu, Xing Tang, Dugang Liu, Liang Chen, Xiuqiang He, Xue Liu |
| 2022 | COLING | Augmenting Legal Judgment Prediction with Contrastive Case Relations. | Dugang Liu, Weihao Du, Lei Li, Weike Pan, Zhong Ming |
| 2022 | DSAA | ALTRec: Adversarial Learning for Autoencoder-based Tail Recommendation. | Jixiong Liu, Dugang Liu, Weike Pan, Zhong Ming |
| 2022 | IJCNN | SQL-Rank++: A Novel Listwise Approach for Collaborative Ranking with Implicit Feedback. | Zheng Yuan, Dugang Liu, Weike Pan, Zhong Ming |
| 2022 | KDD | User-Event Graph Embedding Learning for Context-Aware Recommendation. | Dugang Liu, Mingkai He, Jinwei Luo, Jiangxu Lin, Meng Wang, Xiaolian Zhang, Weike Pan, Zhong Ming |
| 2021 | RecSys | Transfer Learning in Collaborative Recommendation for Bias Reduction. | Zinan Lin, Dugang Liu, Weike Pan, Zhong Ming |
| 2021 | RecSys | Mitigating Confounding Bias in Recommendation via Information Bottleneck. | Dugang Liu, Pengxiang Cheng, Hong Zhu, Zhenhua Dong, Xiuqiang He, Weike Pan, Zhong Ming |
| 2020 | SIGIR | A General Knowledge Distillation Framework for Counterfactual Recommendation via Uniform Data. | Dugang Liu, Pengxiang Cheng, Zhenhua Dong, Xiuqiang He, Weike Pan, Zhong Ming |
| 2019 | WSDM | Spiral of Silence in Recommender Systems. | Dugang Liu, Chen Lin, Zhilin Zhang, Yanghua Xiao, Hanghang Tong |