Adversarial Network Embedding. - Quanyu Dai; Qiang Li 024; Jian Tang; Dan Wang 002 (AAAI, 2018)

Regularized Adversarial Sampling and Deep Time-aware Attention for Click-Through Rate Prediction. - Yikai Wang 001; Liang Zhang; Quanyu Dai; Fuchun Sun 001; Bo Zhang 010; Yang He; Weipeng Yan; Yongjun Bao (CIKM, 2019)

Metadata-driven Task Relation Discovery for Multi-task Learning. - Zimu Zheng; Yuqi Wang; Quanyu Dai; Huadi Zheng; Dan Wang 002 (IJCAI, 2019)

Ranking Network Embedding via Adversarial Learning. - Quanyu Dai; Qiang Li 024; Liang Zhang; Dan Wang 002 (PAKDD (3), 2019)

Adversarial Training Methods for Network Embedding. - Quanyu Dai; Xiao Shen 001; Liang Zhang; Qiang Li 024; Dan Wang 002 (WWW, 2019)

Network Transfer Learning via Adversarial Domain Adaptation with Graph Convolution. - Quanyu Dai; Xiao Shen 001; Xiao-Ming Wu 003; Dan Wang 002 (CoRR, 2019)

Adversarial Deep Network Embedding for Cross-Network Node Classification. - Xiao Shen 001; Quanyu Dai; Fu-Lai Chung; Wei Lu 006; Kup-Sze Choi (AAAI, 2020)

Adversarial Learning for Overlapping Community Detection and Network Embedding. - Junyang Chen 001; Zhiguo Gong; Quanyu Dai; Chunyuan Yuan; Weiwen Liu (ECAI, 2020)

An Attention-based Model for Conversion Rate Prediction with Delayed Feedback via Post-click Calibration. - Yumin Su; Liang Zhang; Quanyu Dai; Bo Zhang 086; Jinyao Yan; Dan Wang 002; Yongjun Bao; Sulong Xu; Yang He; Weipeng Yan (IJCAI, 2020)

Contextual Anomaly Detection in Solder Paste Inspection with Multi-Task Learning. - Zimu Zheng; Jie Pu; Linghui Liu; Dan Wang 002; Xiangming Mei; Sen Zhang; Quanyu Dai (ACM Trans. Intell. Syst. Technol., 2020)

SimpleX: A Simple and Strong Baseline for Collaborative Filtering. - Kelong Mao; Jieming Zhu; Jinpeng Wang; Quanyu Dai; Zhenhua Dong; Xi Xiao; Xiuqiang He 001 (CIKM, 2021)

Top-N Recommendation with Counterfactual User Preference Simulation. - Mengyue Yang; Quanyu Dai; Zhenhua Dong; Xu Chen 017; Xiuqiang He 001; Jun Wang 012 (CIKM, 2021)

Dimensionwise Separable 2-D Graph Convolution for Unsupervised and Semi-Supervised Learning on Graphs. - Qimai Li; Xiaotong Zhang 003; Han Liu 008; Quanyu Dai; Xiao-Ming Wu 003 (KDD, 2021)

Dual Sequence Transformer for Query-based Interactive Recommendation. - Guohao Cai; Xiaoguang Li; Quanyu Dai; Gang Wang 056; Zhenhua Dong; Chaoliang Zhang; Xiuqiang He 001; Lifeng Shang (MDM, 2021)

Adversarial training regularization for negative sampling based network embedding. - Quanyu Dai; Xiao Shen 001; Zimu Zheng; Liang Zhang; Qiang Li 024; Dan Wang 002 (Inf. Sci., 2021)

Network Together: Node Classification via Cross-Network Deep Network Embedding. - Xiao Shen 001; Quanyu Dai; Sitong Mao; Fu-Lai Chung; Kup-Sze Choi (IEEE Trans. Neural Networks Learn. Syst., 2021)

LCD: Adaptive Label Correction for Denoising Music Recommendation. - Quanyu Dai; Yalei Lv; Jieming Zhu; Junjie Ye; Zhenhua Dong; Rui Zhang 003; Shu-Tao Xia; Ruiming Tang (CIKM, 2022)

Boosting Deep CTR Prediction with a Plug-and-Play Pre-trainer for News Recommendation. - Qijiong Liu; Jieming Zhu; Quanyu Dai; Xiaoming Wu 003 (COLING, 2022)

On the Opportunity of Causal Learning in Recommendation Systems: Foundation, Estimation, Prediction and Challenges. - Peng Wu 012; Haoxuan Li 001; Yuhao Deng; Wenjie Hu; Quanyu Dai; Zhenhua Dong; Jie Sun 007; Rui Zhang; Xiao-Hua Zhou (IJCAI, 2022)

A Generalized Doubly Robust Learning Framework for Debiasing Post-Click Conversion Rate Prediction. - Quanyu Dai; Haoxuan Li 001; Peng Wu 012; Zhenhua Dong; Xiao-Hua Zhou; Rui Zhang 079; Rui Zhang 003; Jie Sun 007 (KDD, 2022)

Counteracting User Attention Bias in Music Streaming Recommendation via Reward Modification. - Xiao Zhang 034; Sunhao Dai; Jun Xu 001; Zhenhua Dong; Quanyu Dai; Ji-Rong Wen (KDD, 2022)

ReLoop: A Self-Correction Continual Learning Loop for Recommender Systems. - Guohao Cai; Jieming Zhu; Quanyu Dai; Zhenhua Dong; Xiuqiang He 001; Ruiming Tang; Rui Zhang 003 (SIGIR, 2022)

BARS: Towards Open Benchmarking for Recommender Systems. - Jieming Zhu; Quanyu Dai; Liangcai Su; Rong Ma; Jinyang Liu 002; Guohao Cai; Xi Xiao; Rui Zhang 003 (SIGIR, 2022)

Causal Analysis Framework for Recommendation. - Peng Wu 012; Haoxuan Li 001; Yuhao Deng; Wenjie Hu; Quanyu Dai; Zhenhua Dong; Jie Sun 007; Rui Zhang; Xiao-Hua Zhou (CoRR, 2022)

A Semi-Synthetic Dataset Generation Framework for Causal Inference in Recommender Systems. - Yan Lyu; Sunhao Dai; Peng Wu 012; Quanyu Dai; Yuhao Deng; Wenjie Hu; Zhenhua Dong; Jun Xu 001; Shengyu Zhu 001; Xiao-Hua Zhou (CoRR, 2022)

Sequential Recommendation with Causal Behavior Discovery. - Zhenlei Wang; Xu Chen 017; Zhenhua Dong; Quanyu Dai; Ji-Rong Wen (CoRR, 2022)

Recommendation with User Active Disclosing Willingness. - Lei Wang 198; Xu Chen 017; Quanyu Dai; Zhenhua Dong (CoRR, 2022)

Personalized knowledge-aware recommendation with collaborative and attentive graph convolutional networks. - Quanyu Dai; Xiao-Ming Wu 003; Lu Fan; Qimai Li; Han Liu 008; Xiaotong Zhang 003; Dan Wang 002; Guli Lin; Keping Yang (Pattern Recognit., 2022)

Social Attentive Deep Q-Networks for Recommender Systems. - Yu Lei 004; Zhitao Wang; Wenjie Li 002; Hongbin Pei; Quanyu Dai (IEEE Trans. Knowl. Data Eng., 2022)

Debiased recommendation with neural stratification. - Quanyu Dai; Zhenhua Dong; Xu Chen 017 (AI Open, 2022)

Multiple Robust Learning for Recommendation. - Haoxuan Li 001; Quanyu Dai; Yuru Li; Yan Lyu; Zhenhua Dong; Xiao-Hua Zhou; Peng Wu 012 (AAAI, 2023)

Sequential Recommendation with User Causal Behavior Discovery. - Zhenlei Wang; Xu Chen 017; Rui Zhou; Quanyu Dai; Zhenhua Dong; Ji-Rong Wen (ICDE, 2023)

Out-of-distribution Detection with Implicit Outlier Transformation. - Qizhou Wang; Junjie Ye; Feng Liu 003; Quanyu Dai; Marcus Kalander; Tongliang Liu; Jianye Hao; Bo Han 003 (ICLR, 2023)

REASONER: An Explainable Recommendation Dataset with Comprehensive Labeling Ground Truths. - Xu Chen 017; Jingsen Zhang; Lei Wang 198; Quanyu Dai; Zhenhua Dong; Ruiming Tang; Rui Zhang 003; Li Chen; Xin Zhao 018; Ji-Rong Wen (NeurIPS, 2023)

Optimal Transport for Treatment Effect Estimation. - Hao Wang 049; Jiajun Fan; Zhichao Chen 001; Haoxuan Li 001; Weiming Liu 005; Tianqiao Liu; Quanyu Dai; Yichao Wang 002; Zhenhua Dong; Ruiming Tang (NeurIPS, 2023)

Robust Causal Inference for Recommender System to Overcome Noisy Confounders. - Zhiheng Zhang; Quanyu Dai; Xu Chen 017; Zhenhua Dong; Ruiming Tang (SIGIR, 2023)

FINAL: Factorized Interaction Layer for CTR Prediction. - Jieming Zhu; Qinglin Jia; Guohao Cai; Quanyu Dai; Jingjie Li; Zhenhua Dong; Ruiming Tang; Rui Zhang 003 (SIGIR, 2023)

Task Adaptive Multi-learner Network for Joint CTR and CVR Estimation. - Xiaofan Liu; Qinglin Jia; Chuhan Wu; Jingjie Li; Quanyu Dai; Lin Bo; Rui Zhang 003; Ruiming Tang (WWW (Companion Volume), 2023)

Recommendation with Causality enhanced Natural Language Explanations. - Jingsen Zhang; Xu Chen 017; Jiakai Tang; Weiqi Shao; Quanyu Dai; Zhenhua Dong; Rui Zhang 003 (WWW, 2023)

REASONER: An Explainable Recommendation Dataset with Multi-aspect Real User Labeled Ground Truths Towards more Measurable Explainable Recommendation. - Xu Chen 017; Jingsen Zhang; Lei Wang 198; Quanyu Dai; Zhenhua Dong; Ruiming Tang; Rui Zhang 003; Li Chen; Ji-Rong Wen (CoRR, 2023)

Only Encode Once: Making Content-based News Recommender Greener. - Qijiong Liu; Jieming Zhu; Quanyu Dai; Xiao-Ming Wu 003 (CoRR, 2023)

Adversarially regularized graph attention networks for inductive learning on partially labeled graphs. - Jiaren Xiao; Quanyu Dai; Xiaochen Xie; James Lam; Ka-Wai Kwok (Knowl. Based Syst., 2023)

Domain Adaptive Graph Infomax via Conditional Adversarial Networks. - Jiaren Xiao; Quanyu Dai; Xiaochen Xie; Qi Dou 001; Ka-Wai Kwok; James Lam (IEEE Trans. Netw. Sci. Eng., 2023)

Graph Transfer Learning via Adversarial Domain Adaptation With Graph Convolution. - Quanyu Dai; Xiao-Ming Wu 003; Jiaren Xiao; Xiao Shen 001; Dan Wang 002 (IEEE Trans. Knowl. Data Eng., 2023)

Would You Like Your Data to Be Trained? A User Controllable Recommendation Framework. - Lei Wang 198; Xu Chen 017; Zhenhua Dong; Quanyu Dai (AAAI, 2024)

UniEmbedding: Learning Universal Multi-Modal Multi-Domain Item Embeddings via User-View Contrastive Learning. - Boqi Dai; Zhaocheng Du; Jieming Zhu; Jintao Xu; Deqing Zou; Quanyu Dai; Zhenhua Dong; Rui Zhang 003; Hai-Tao Zheng 002 (CIKM, 2024)

Active Explainable Recommendation with Limited Labeling Budgets. - Jingsen Zhang; Xiaohe Bo; Chenxi Wang; Quanyu Dai; Zhenhua Dong; Ruiming Tang; Xu Chen 017 (ICASSP, 2024)

Modeling User Attention in Music Recommendation. - Sunhao Dai; Ninglu Shao; Jieming Zhu; Xiao Zhang 034; Zhenhua Dong; Jun Xu 001; Quanyu Dai; Ji-Rong Wen (ICDE, 2024)

Multimodal Pretraining, Adaptation, and Generation for Recommendation: A Survey. - Qijiong Liu; Jieming Zhu; Yanting Yang; Quanyu Dai; Zhaocheng Du; Xiao-Ming Wu 003; Zhou Zhao 001; Rui Zhang 003; Zhenhua Dong (KDD, 2024)

MAJL: A Model-Agnostic Joint Learning Framework for Music Source Separation and Pitch Estimation. - Haojie Wei; Jun Yuan 008; Rui Zhang 003; Quanyu Dai; Yueguo Chen (ACM Multimedia, 2024)

Reflective Multi-Agent Collaboration based on Large Language Models. - Xiaohe Bo; Zeyu Zhang 007; Quanyu Dai; Xueyang Feng; Lei Wang 198; Rui Li 086; Xu Chen 017; Ji-Rong Wen (NeurIPS, 2024)

Benchmarking News Recommendation in the Era of Green AI. - Qijiong Liu; Jieming Zhu; Quanyu Dai; Xiao-Ming Wu 003 (WWW (Companion Volume), 2024)

A Survey on the Memory Mechanism of Large Language Model based Agents. - Zeyu Zhang 007; Xiaohe Bo; Chen Ma 001; Rui Li 086; Xu Chen 017; Quanyu Dai; Jieming Zhu; Zhenhua Dong; Ji-Rong Wen (CoRR, 2024)

MemSim: A Bayesian Simulator for Evaluating Memory of LLM-based Personal Assistants. - Zeyu Zhang 007; Quanyu Dai; Luyu Chen; Zeren Jiang; Rui Li 086; Jieming Zhu; Xu Chen 017; Yi Xie; Zhenhua Dong; Ji-Rong Wen (CoRR, 2024)

Semi-supervised domain adaptation on graphs with contrastive learning and minimax entropy. - Jiaren Xiao; Quanyu Dai; Xiao Shen 001; Xiaochen Xie; Jing Dai; James Lam; Ka-Wai Kwok (Neurocomputing, 2024)

Expectation Confirmation Preference Optimization for Multi-Turn Conversational Recommendation Agent. - Xueyang Feng; Jingsen Zhang; Jiakai Tang; Wei Li; Guohao Cai; Xu Chen 017; Quanyu Dai; Yue Zhu; Zhenhua Dong (ACL (Findings), 2025)

MemBench: Towards More Comprehensive Evaluation on the Memory of LLM-based Agents. - Haoran Tan; Zeyu Zhang 007; Chen Ma 001; Xu Chen 017; Quanyu Dai; Zhenhua Dong (ACL (Findings), 2025)

SocialEval: Evaluating Social Intelligence of Large Language Models. - Jinfeng Zhou; Yuxuan Chen; Yihan Shi; Xuanming Zhang; Leqi Lei; Yi Feng; Zexuan Xiong; Miao Yan; Xunzhi Wang; Yaru Cao; Jianing Yin; Shuai Wang; et al. (ACL (1), 2025)

Improving Retrospective Language Agents via Joint Policy Gradient Optimization. - Xueyang Feng; Bo Lan; Quanyu Dai; Lei Wang 198; Jiakai Tang; Xu Chen 017; Zhenhua Dong; Ji-Rong Wen (NAACL (Long Papers), 2025)

RecUserSim: A Realistic and Diverse User Simulator for Evaluating Conversational Recommender Systems. - Luyu Chen; Quanyu Dai; Zeyu Zhang 007; Xueyang Feng; Mingyu Zhang; Pengcheng Tang; Xu Chen 017; Yue Zhu; Zhenhua Dong (WWW (Companion Volume), 2025)

MCNet: Monotonic Calibration Networks for Expressive Uncertainty Calibration in Online Advertising. - Quanyu Dai; Jiaren Xiao; Zhaocheng Du; Jieming Zhu; Chengxiao Luo; Xiao-Ming Wu 003; Zhenhua Dong (WWW, 2025)

EAGER-LLM: Enhancing Large Language Models as Recommenders through Exogenous Behavior-Semantic Integration. - Minjie Hong; Yan Xia 006; Zehan Wang 001; Jieming Zhu; Ye Wang 018; Sihang Cai; Xiaoda Yang; Quanyu Dai; Zhenhua Dong; Zhimeng Zhang; Zhou Zhao 001 (WWW, 2025)

MemEngine: A Unified and Modular Library for Developing Advanced Memory of LLM-based Agents. - Zeyu Zhang 007; Quanyu Dai; Xu Chen 017; Rui Li 086; Zhongyang Li; Zhenhua Dong (WWW (Companion Volume), 2025)

Evaluating Conversational Recommender Systems with Large Language Models: A User-Centric Evaluation Framework. - Nuo Chen 004; Quanyu Dai; Xiaoyu Dong; Xiao-Ming Wu 003; Zhenhua Dong (CoRR, 2025)

A Survey of Personalized Large Language Models: Progress and Future Directions. - Jiahong Liu 001; Zexuan Qiu; Zhongyang Li; Quanyu Dai; Jieming Zhu; Minda Hu; Menglin Yang 005; Irwin King (CoRR, 2025)

Beyond Single-Point Judgment: Distribution Alignment for LLM-as-a-Judge. - Luyu Chen; Zeyu Zhang 007; Haoran Tan; Quanyu Dai; Hao Yang; Zhenhua Dong; Xu Chen 017 (CoRR, 2025)

KnowTrace: Bootstrapping Iterative Retrieval-Augmented Generation with Structured Knowledge Tracing. - Rui Li 086; Quanyu Dai; Zeyu Zhang 007; Xu Chen 017; Zhenhua Dong; Ji-Rong Wen (CoRR, 2025)

Enhancing the Preference Extractor in Multi-turn Dialogues: From Annotating Disasters to Accurate Preference Extraction. - Cheng Wang; Ziru Liu; Pengcheng Tang; Mingyu Zhang; Quanyu Dai; Yue Zhu (CoRR, 2025)