| 2026 | AAAI | M²VAE: Multi-Modal Multi-View Variational Autoencoder for Cold-start Item Recommendation. | Chuan He, Yongchao Liu, Qiang Li, Chuntao Hong, Wenliang Zhong, Xin-Wei Yao |
| 2026 | AAAI | Learning from Guidelines: Structured Prompt Optimization for Expert Annotation Tasks. | Wenliang Zhong, Haiqing Li, Thao M. Dang, Feng Jiang, Hehuan Ma, Yuzhi Guo, Jean Gao, Junzhou Huang |
| 2026 | ACL | Guidelines as Environments: A World Model Approach to Rule Following. | Haiqing Li, Wenliang Zhong, Yinhao Wu, Hehuan Ma, Yuzhi Guo, Thao M. Dang, Junzhou Huang |
| 2026 | SIGIR | SCOPE: Scalable Cross-Task Orthogonal Progressive Experts for Multi-Task Learning in Recommendations. | Zixian Yang, Wei Xu, Li Li, Zhaokai Huang, You Li, Jianbin Lin, Wenliang Zhong, Can Ye |
| 2025 | CVPR | Towards Stable and Storage-efficient Dataset Distillation: Matching Convexified Trajectory. | Wenliang Zhong, Haoyu Tang, Qinghai Zheng, Mingzhu Xu, Yupeng Hu, Weili Guan |
| 2025 | ICCV | Zero-Shot Composed Image Retrieval via Dual-Stream Instruction-Aware Distillation. | Wenliang Zhong, Robert A. Barton, Weizhi An, Feng Jiang, Hehuan Ma, Yuzhi Guo, Abhishek Dan, Shioulin Sam, Karim Bouyarmane, Junzhou Huang |
| 2025 | KDD | Put Teacher in Student's Shoes: Cross-Distillation for Ultra-compact Model Compression Framework. | Maolin Wang, Jun Chu, Sicong Xie, Xiaoling Zang, Yao Zhao, Wenliang Zhong, Xiangyu Zhao |
| 2025 | SIGIR | Towards Principled Learning for Re-ranking in Recommender Systems. | Qunwei Li, Linghui Li, Jianbin Lin, Wenliang Zhong |
| 2024 | CVPR | Towards Efficient Replay in Federated Incremental Learning. | Yichen Li, Qunwei Li, Haozhao Wang, Ruixuan Li, Wenliang Zhong, Guannan Zhang |
| 2024 | ECCV | Causal Subgraphs and Information Bottlenecks: Redefining OOD Robustness in Graph Neural Networks. | Weizhi An, Wenliang Zhong, Feng Jiang, Hehuan Ma, Junzhou Huang |
| 2024 | MICCAI | PathM3: A Multimodal Multi-task Multiple Instance Learning Framework for Whole Slide Image Classification and Captioning. | Qifeng Zhou, Wenliang Zhong, Yuzhi Guo, Michael Xiao, Hehuan Ma, Junzhou Huang |
| 2024 | SIGIR | Exploring Multi-Scenario Multi-Modal CTR Prediction with a Large Scale Dataset. | Zhaoxin Huan, Ke Ding, Ang Li, Xiaolu Zhang, Xu Min, Yong He, Liang Zhang, Jun Zhou, Linjian Mo, Jinjie Gu, Zhongyi Liu, Wenliang Zhong, Guannan Zhang, Chenliang Li, Fajie Yuan |
| 2024 | WACV | MIVC: Multiple Instance Visual Component for Visual-Language Models. | Wenyi Wu, Qi Li, Wenliang Zhong, Junzhou Huang |
| 2024 | WSDM | PEACE: Prototype lEarning Augmented transferable framework for Cross-domain rEcommendation. | Chunjing Gan, Bo Huang, Binbin Hu, Jian Ma, Zhiqiang Zhang, Jun Zhou, Guannan Zhang, Wenliang Zhong |
| 2023 | ICDM | ChatGraph: Interpretable Text Classification by Converting ChatGPT Knowledge to Graphs. | Yucheng Shi, Hehuan Ma, Wenliang Zhong, Qiaoyu Tan, Gengchen Mai, Xiang Li, Tianming Liu, Junzhou Huang |
| 2023 | KDD | Commonsense Knowledge Graph towards Super APP and Its Applications in Alipay. | Xiaoling Zang, Binbin Hu, Jun Chu, Zhiqiang Zhang, Guannan Zhang, Jun Zhou, Wenliang Zhong |
| 2023 | SIGIR | Which Matters Most in Making Fund Investment Decisions? A Multi-granularity Graph Disentangled Learning Framework. | Chunjing Gan, Binbin Hu, Bo Huang, Tianyu Zhao, Yingru Lin, Wenliang Zhong, Zhiqiang Zhang, Jun Zhou, Chuan Shi |
| 2023 | SIGIR | Edge-cloud Collaborative Learning with Federated and Centralized Features. | Zexi Li, Qunwei Li, Yi Zhou, Wenliang Zhong, Guannan Zhang, Chao Wu |
| 2023 | SIGIR | COUPA: An Industrial Recommender System for Online to Offline Service Platforms. | Sicong Xie, Binbin Hu, Fengze Li, Ziqi Liu, Zhiqiang Zhang, Wenliang Zhong, Jun Zhou |
| 2022 | CIKM | Prototypical Contrastive Learning and Adaptive Interest Selection for Candidate Generation in Recommendations. | Ningning Li, Qunwei Li, Xichen Ding, Shaohu Chen, Wenliang Zhong |
| 2022 | ICML | Multi-slots Online Matching with High Entropy. | Xingyu Lu, Qintong Wu, Wenliang Zhong |
| 2022 | KDD | Non-stationary Time-aware Kernelized Attention for Temporal Event Prediction. | Yu Ma, Zhining Liu, Chenyi Zhuang, Yize Tan, Yi Dong, Wenliang Zhong, Jinjie Gu |
| 2022 | SIGIR | Denoising Time Cycle Modeling for Recommendation. | Sicong Xie, Qunwei Li, Weidi Xu, Kaiming Shen, Shaohu Chen, Wenliang Zhong |
| 2022 | SIGIR | Progressive Self-Attention Network with Unsymmetrical Positional Encoding for Sequential Recommendation. | Yuehua Zhu, Bo Huang, Shaohua Jiang, Muli Yang, Yanhua Yang, Wenliang Zhong |
| 2021 | AAAI | Learning Graph Neural Networks with Approximate Gradient Descent. | Qunwei Li, Shaofeng Zou, Wenliang Zhong |
| 2019 | CIKM | Graph Representation Learning for Merchant Incentive Optimization in Mobile Payment Marketing. | Ziqi Liu, Dong Wang, Qianyu Yu, Zhiqiang Zhang, Yue Shen, Jian Ma, Wenliang Zhong, Jinjie Gu, Jun Zhou, Shuang Yang, Yuan Qi |
| 2015 | ICDM | Fast Low-Rank Matrix Learning with Nonconvex Regularization. | Quanming Yao, James T. Kwok, Wenliang Zhong |
| 2015 | KDD | Stock Constrained Recommendation in Tmall. | Wenliang Zhong, Rong Jin, Cheng Yang, Xiaowei Yan, Qi Zhang, Qiang Li |
| 2014 | AAAI | Gradient Descent with Proximal Average for Nonconvex and Composite Regularization. | Wenliang Zhong, James T. Kwok |
| 2014 | AISTATS | Accelerated Stochastic Gradient Method for Composite Regularization. | Wenliang Zhong, James Tin-Yau Kwok |
| 2014 | ICML | Fast Stochastic Alternating Direction Method of Multipliers. | Wenliang Zhong, James Tin-Yau Kwok |
| 2013 | IJCAI | Accurate Probability Calibration for Multiple Classifiers. | Wenliang Zhong, James T. Kwok |
| 2012 | ICML | Convex Multitask Learning with Flexible Task Clusters. | Wenliang Zhong, James Tin-Yau Kwok |
| 2011 | ICML | Efficient Sparse Modeling with Automatic Feature Grouping. | Wenliang Zhong, James T. Kwok |