| 2026 | AAAI | Efficient Reinforcement Learning for Zero-Shot Coordination in Evolving Games. | Bingyu Hui, Lebin Yu, Quanming Yao, Yunpeng Qu, Xudong Zhang, Jian Wang |
| 2026 | ICPR | SigRef: Verification-Driven Reflection for Faithful Paper-to-Code Development. | Mingyang Zhou, Quanming Yao, Lun Du, Lanning Wei, Da Zheng |
| 2026 | PAKDD | Opportunities for AutoML in the Agentic Era. | Zhenqian Shen, Kelly Chandra Wijaya, Quanming Yao |
| 2026 | PAKDD | Distillation-Based Scenario-Adaptive Mixture-of-Experts for the Matching Stage of Multi-scenario Recommendation. | Ruibing Wang, Shuhan Guo, Haotong Du, Quanming Yao |
| 2026 | WWW | DA-RAG: Dynamic Attributed Community Search for Retrieval-Augmented Generation. | Xingyuan Zeng, Zuohan Wu, Yue Wang, Chen Zhang, Quanming Yao, Libin Zheng, Jian Yin |
| 2025 | ACL | Nested-Refinement Metamorphosis: Reflective Evolution for Efficient Optimization of Networking Problems. | Shuhan Guo, Nan Yin, James Kwok, Quanming Yao |
| 2025 | ACL | Think Both Ways: Teacher-Student Bidirectional Reasoning Enhances MCQ Generation and Distractor Quality. | Yimiao Qiu, Yang Deng, Quanming Yao, Zhimeng Zhang, Zhiang Dong, Chang Yao, Jingyuan Chen |
| 2025 | EMNLP | Superpose Task-specific Features for Model Merging. | Haiquan Qiu, You Wu, Dong Li, Jianmin Guo, Quanming Yao |
| 2025 | ICDE | Explore the Disentanglement Mechanism for Deep Learning. | Haiquan Qiu, Quanming Yao |
| 2025 | ICLR | Why In-Context Learning Models are Good Few-Shot Learners? | Shiguang Wu, Yaqing Wang, Quanming Yao |
| 2025 | ICLR | Erasing Concept Combination from Text-to-Image Diffusion Model. | Hongyi Nie, Quanming Yao, Yang Liu, Zhen Wang, Yatao Bian |
| 2025 | ICLR | Curriculum-aware Training for Discriminating Molecular Property Prediction Models. | Hansi Yang, Quanming Yao, James Kwok |
| 2025 | ICML | Hierarchical Graph Tokenization for Molecule-Language Alignment. | Yongqiang Chen, Quanming Yao, Juzheng Zhang, James Cheng, Yatao Bian |
| 2025 | IJCAI | Unified Molecule-Text Language Model with Discrete Token Representation. | Shuhan Guo, Yatao Bian, Ruibing Wang, Nan Yin, Zhen Wang, Quanming Yao |
| 2025 | IJCAI | Automated Decision-Making on Networks with LLMs through Knowledge-Guided Evolution. | Xiaohan Zheng, Lanning Wei, Yong Li, Quanming Yao |
| 2025 | KDD | PERSCEN: Learning Personalized Interaction Pattern and Scenario Preference for Multi-Scenario Matching. | Haotong Du, Yaqing Wang, Fei Xiong, Lei Shao, Ming Liu, Hao Gu, Quanming Yao, Zhen Wang |
| 2024 | AAAI | Towards Human-like Learning from Relational Structured Data. | Quanming Yao |
| 2024 | AAAI | Robust Communicative Multi-Agent Reinforcement Learning with Active Defense. | Lebin Yu, Yunbo Qiu, Quanming Yao, Yuan Shen, Xudong Zhang, Jian Wang |
| 2024 | DASFAA | Relation-Entity Hybrid Learning Graph Model for Few-Shot Temporal Knowledge Graph Forecasting. | Shiqi Fan, Hongyi Nie, Ruibing Wang, Quanming Yao, Haotong Du, Yang Liu, Zhen Wang |
| 2024 | ICDE | Knowledge-Enhanced Recommendation with User-Centric Subgraph Network. | Guangyi Liu, Quanming Yao, Yongqi Zhang, Lei Chen |
| 2024 | ICLR | Understanding Expressivity of GNN in Rule Learning. | Haiquan Qiu, Yongqi Zhang, Yong Li, Quanming Yao |
| 2024 | ICLR | Less is More: One-shot Subgraph Reasoning on Large-scale Knowledge Graphs. | Zhanke Zhou, Yongqi Zhang, Jiangchao Yao, Quanming Yao, Bo Han |
| 2024 | IJCAI | PACIA: Parameter-Efficient Adapter for Few-Shot Molecular Property Prediction. | Shiguang Wu, Yaqing Wang, Quanming Yao |
| 2024 | KDD | Warming Up Cold-Start CTR Prediction by Learning Item-Specific Feature Interactions. | Yaqing Wang, Hongming Piao, Daxiang Dong, Quanming Yao, Jingbo Zhou |
| 2024 | KDD | Heuristic Learning with Graph Neural Networks: A Unified Framework for Link Prediction. | Juzheng Zhang, Lanning Wei, Zhen Xu, Quanming Yao |
| 2023 | CIKM | Positive-Unlabeled Node Classification with Structure-aware Graph Learning. | Hansi Yang, Yongqi Zhang, Quanming Yao, James T. Kwok |
| 2023 | EMNLP | Relation-aware Ensemble Learning for Knowledge Graph Embedding. | Ling Yue, Yongqi Zhang, Quanming Yao, Yong Li, Xian Wu, Ziheng Zhang, Zhenxi Lin, Yefeng Zheng |
| 2023 | ICIP | Combining Self-Supervised and Supervised Learning with Noisy Labels. | Yongqi Zhang, Hui Zhang, Quanming Yao, Jun Wan |
| 2023 | ICLR | Learning Symbolic Models for Graph-structured Physical Mechanism. | Hongzhi Shi, Jingtao Ding, Yufan Cao, Quanming Yao, Li Liu, Yong Li |
| 2023 | ICLR | Combating Exacerbated Heterogeneity for Robust Models in Federated Learning. | Jianing Zhu, Jiangchao Yao, Tongliang Liu, Quanming Yao, Jianliang Xu, Bo Han |
| 2023 | ICML | On Strengthening and Defending Graph Reconstruction Attack with Markov Chain Approximation. | Zhanke Zhou, Chenyu Zhou, Xuan Li, Jiangchao Yao, Quanming Yao, Bo Han |
| 2023 | KDD | Automated 3D Pre-Training for Molecular Property Prediction. | Xu Wang, Huan Zhao, Wei-Wei Tu, Quanming Yao |
| 2023 | KDD | AdaProp: Learning Adaptive Propagation for Graph Neural Network based Knowledge Graph Reasoning. | Yongqi Zhang, Zhanke Zhou, Quanming Yao, Xiaowen Chu, Bo Han |
| 2023 | WWW | Learning to Simulate Crowd Trajectories with Graph Networks. | Hongzhi Shi, Quanming Yao, Yong Li |
| 2023 | WWW | Search to Capture Long-range Dependency with Stacking GNNs for Graph Classification. | Lanning Wei, Zhiqiang He, Huan Zhao, Quanming Yao |
| 2023 | WWW | ColdNAS: Search to Modulate for User Cold-Start Recommendation. | Shiguang Wu, Yaqing Wang, Qinghe Jing, Daxiang Dong, Dejing Dou, Quanming Yao |
| 2022 | ACL | Efficient Hyper-parameter Search for Knowledge Graph Embedding. | Yongqi Zhang, Zhanke Zhou, Quanming Yao, Yong Li |
| 2022 | ECCV | Spectrum-Aware and Transferable Architecture Search for Hyperspectral Image Restoration. | Wei He, Quanming Yao, Naoto Yokoya, Tatsumi Uezato, Hongyan Zhang, Liangpei Zhang |
| 2022 | EMNLP | Search to Pass Messages for Temporal Knowledge Graph Completion. | Zhen Wang, Haotong Du, Quanming Yao, Xuelong Li |
| 2022 | EMNLP | Simplified Graph Learning for Inductive Short Text Classification. | Kaixin Zheng, Yaqing Wang, Quanming Yao, Dejing Dou |
| 2022 | ICML | Fast and Provable Nonconvex Tensor RPCA. | Haiquan Qiu, Yao Wang, Shaojie Tang, Deyu Meng, Quanming Yao |
| 2022 | WWW | Knowledge Graph Reasoning with Relational Digraph. | Yongqi Zhang, Quanming Yao |
| 2021 | CIKM | Pooling Architecture Search for Graph Classification. | Lanning Wei, Huan Zhao, Quanming Yao, Zhiqiang He |
| 2021 | EMNLP | Hierarchical Heterogeneous Graph Representation Learning for Short Text Classification. | Yaqing Wang, Song Wang, Quanming Yao, Dejing Dou |
| 2021 | ICDE | Efficient Relation-aware Scoring Function Search for Knowledge Graph Embedding. | Shimin Di, Quanming Yao, Yongqi Zhang, Lei Chen |
| 2021 | ICDE | Search to aggregate neighborhood for graph neural network. | Huan Zhao, Quanming Yao, Weiwei Tu |
| 2021 | KDD | DiffMG: Differentiable Meta Graph Search for Heterogeneous Graph Neural Networks. | Yuhui Ding, Quanming Yao, Huan Zhao, Tong Zhang |
| 2021 | KDD | Efficient Data-specific Model Search for Collaborative Filtering. | Chen Gao, Quanming Yao, Depeng Jin, Yong Li |
| 2021 | WWW | Searching to Sparsify Tensor Decomposition for N-ary Relational Data. | Shimin Di, Quanming Yao, Lei Chen |
| 2021 | WWW | Role-Aware Modeling for N-ary Relational Knowledge Bases. | Yu Liu, Quanming Yao, Yong Li |
| 2021 | WWW | A Scalable, Adaptive and Sound Nonconvex Regularizer for Low-rank Matrix Learning. | Yaqing Wang, Quanming Yao, James T. Kwok |
| 2020 | AAAI | Efficient Neural Architecture Search via Proximal Iterations. | Quanming Yao, Ju Xu, Wei-Wei Tu, Zhanxing Zhu |
| 2020 | CIKM | Simplifying Architecture Search for Graph Neural Network. | Huan Zhao, Lanning Wei, Quanming Yao |
| 2020 | ECCV | AutoSTR: Efficient Backbone Search for Scene Text Recognition. | Hui Zhang, Quanming Yao, Mingkun Yang, Yongchao Xu, Xiang Bai |
| 2020 | ICDE | Predicting Origin-Destination Flow via Multi-Perspective Graph Convolutional Network. | Hongzhi Shi, Quanming Yao, Qi Guo, Yaguang Li, Lingyu Zhang, Jieping Ye, Yong Li, Yan Liu |
| 2020 | ICDE | AutoSF: Searching Scoring Functions for Knowledge Graph Embedding. | Yongqi Zhang, Quanming Yao, Wenyuan Dai, Lei Chen |
| 2020 | ICML | SIGUA: Forgetting May Make Learning with Noisy Labels More Robust. | Bo Han, Gang Niu, Xingrui Yu, Quanming Yao, Miao Xu, Ivor W. Tsang, Masashi Sugiyama |
| 2020 | ICML | Searching to Exploit Memorization Effect in Learning with Noisy Labels. | Quanming Yao, Hansi Yang, Bo Han, Gang Niu, James Tin-Yau Kwok |
| 2020 | KDD | Advances in Recommender Systems: From Multi-stakeholder Marketplaces to Automated RecSys. | Rishabh Mehrotra, Ben Carterette, Yong Li, Quanming Yao, Chen Gao, James T. Kwok, Qiang Yang, Isabelle Guyon |
| 2020 | WWW | Generalizing Tensor Decomposition for N-ary Relational Knowledge Bases. | Yu Liu, Quanming Yao, Yong Li |
| 2020 | WWW | Efficient Neural Interaction Function Search for Collaborative Filtering. | Quanming Yao, Xiangning Chen, James T. Kwok, Yong Li, Cho-Jui Hsieh |
| 2019 | CVPR | Non-Local Meets Global: An Integrated Paradigm for Hyperspectral Denoising. | Wei He, Quanming Yao, Chao Li, Naoto Yokoya, Qibin Zhao |
| 2019 | ICDE | NSCaching: Simple and Efficient Negative Sampling for Knowledge Graph Embedding. | Yongqi Zhang, Quanming Yao, Yingxia Shao, Lei Chen |
| 2019 | ICML | Efficient Nonconvex Regularized Tensor Completion with Structure-aware Proximal Iterations. | Quanming Yao, James Tin-Yau Kwok, Bo Han |
| 2019 | IJCAI | Robust Learning from Noisy Side-information by Semidefinite Programming. | En-Liang Hu, Quanming Yao |
| 2019 | IJCAI | Privacy-Preserving Stacking with Application to Cross-organizational Diabetes Prediction. | Quanming Yao, Xiawei Guo, James T. Kwok, Wei-Wei Tu, Yuqiang Chen, Wenyuan Dai, Qiang Yang |
| 2019 | KDD | AutoCross: Automatic Feature Crossing for Tabular Data in Real-World Applications. | Yuanfei Luo, Mengshuo Wang, Hao Zhou, Quanming Yao, Wei-Wei Tu, Yuqiang Chen, Wenyuan Dai, Qiang Yang |
| 2019 | KDD | State-Sharing Sparse Hidden Markov Models for Personalized Sequences. | Hongzhi Shi, Chao Zhang, Quanming Yao, Yong Li, Funing Sun, Depeng Jin |
| 2018 | ICML | Online Convolutional Sparse Coding with Sample-Dependent Dictionary. | Yaqing Wang, Quanming Yao, James Tin-Yau Kwok, Lionel M. Ni |
| 2017 | AAAI | Efficient Sparse Low-Rank Tensor Completion Using the Frank-Wolfe Algorithm. | Xiawei Guo, Quanming Yao, James Tin-Yau Kwok |
| 2017 | ICDM | Collaborative Filtering with Social Local Models. | Huan Zhao, Quanming Yao, James T. Kwok, Dik Lun Lee |
| 2017 | ICLR | Loss-aware Binarization of Deep Networks. | Lu Hou, Quanming Yao, James T. Kwok |
| 2017 | IJCAI | Efficient Inexact Proximal Gradient Algorithm for Nonconvex Problems. | Quanming Yao, James T. Kwok, Fei Gao, Wei Chen, Tie-Yan Liu |
| 2017 | IJCNN | Zero-shot learning with a partial set of observed attributes. | Yaqing Wang, James T. Kwok, Quanming Yao, Lionel M. Ni |
| 2017 | KDD | Meta-Graph Based Recommendation Fusion over Heterogeneous Information Networks. | Huan Zhao, Quanming Yao, Jianda Li, Yangqiu Song, Dik Lun Lee |
| 2016 | ICML | Efficient Learning with a Family of Nonconvex Regularizers by Redistributing Nonconvexity. | Quanming Yao, James T. Kwok |
| 2016 | IJCAI | Greedy Learning of Generalized Low-Rank Models. | Quanming Yao, James T. Kwok |
| 2015 | AAAI | Colorization by Patch-Based Local Low-Rank Matrix Completion. | Quanming Yao, James T. Kwok |
| 2015 | ICDM | Fast Low-Rank Matrix Learning with Nonconvex Regularization. | Quanming Yao, James T. Kwok, Wenliang Zhong |
| 2015 | IJCAI | Accelerated Inexact Soft-Impute for Fast Large-Scale Matrix Completion. | Quanming Yao, James T. Kwok |