| 2026 | AAAI | LGAN: An Efficient High-Order Graph Neural Network via the Line Graph Aggregation. | Lin Du, Lu Bai, Jincheng Li, Lixin Cui, Hangyuan Du, Lichi Zhang, Yuting Chen, Zhao Li |
| 2026 | AAAI | GCIB: Causal Intervention Guided Graph Information Bottleneck Framework. | Hangyuan Du, Rong Wang, Lixin Cui, Gaoxia Jiang, Liang Bai, Wenjian Wang |
| 2026 | AAAI | Self-Supervised Hypergraph Learning with Substructure Awareness for Hyperedge Prediction. | Ming Li, Huiting Wang, Yuting Chen, Lu Bai, Lixin Cui, Feilong Cao, Ke Lv |
| 2026 | AAAI | Multi-Granular Graph Learning with Fine-Grained Behavioral Pattern Awareness for Session-Based Recommendation. | Ming Li, Zihao Yan, Yuting Chen, Lixin Cui, Lu Bai, Feilong Cao, Ke Lv, Zhao Li |
| 2026 | AAAI | HyperNoRA: Hyperedge Prediction via Node-Level Relation-Aware Self-Supervised Hypergraph Learning. | Ming Li, Zhanle Zhu, Xinyi Li, Lu Bai, Lixin Cui, Feilong Cao, Ke Lv |
| 2026 | AAAI | HyperAim: Hypergraph Contrastive Learning with Adaptive Multi-frequency Filters. | Ming Li, Ruiting Zhao, Zihao Yan, Lu Bai, Lixin Cui, Feilong Cao |
| 2026 | AAAI | SSHPool: The Separated Subgraph-based Hierarchical Pooling. | Zhuo Xu, Lu Bai, Lixin Cui, Ming Li, Hangyuan Du, Ziyu Lyu, Yue Wang, Edwin R. Hancock |
| 2026 | ACL | Please refuse to answer me! Mitigating Over-Refusal in Large Language Models via Adaptive Contrastive Decoding. | Yupeng Qi, Ziyu Lyu, Lixin Cui, Lu Bai, Feng Xia |
| 2026 | ISKE | Entropy-Based Graph Embedding for Credit Risk Evaluation Incorporating Sample Correlations. | Mingyu Liu, Lixin Cui, Xin Jin, Zhipeng Cui, Lu Bai |
| 2026 | WWW | RAIE: Region-Aware Incremental Preference Editing with LoRA for LLM-based Recommendation. | Jin Zeng, Yupeng Qi, Hui Li, Chengming Li, Ziyu Lyu, Lixin Cui, Lu Bai |
| 2025 | AAAI | DHAKR: Learning Deep Hierarchical Attention-Based Kernelized Representations for Graph Classification. | Feifei Qian, Lu Bai, Lixin Cui, Ming Li, Ziyu Lyu, Hangyuan Du, Edwin R. Hancock |
| 2025 | EMNLP | MidPO: Dual Preference Optimization for Safety and Helpfulness in Large Language Models via a Mixture of Experts Framework. | Yupeng Qi, Ziyu Lyu, Min Yang, Yanlin Wang, Lu Bai, Lixin Cui |
| 2025 | ICDE | AEGK: Aligned Entropic Graph Kernels Through Continuous-Time Quantum Walks: (Extended Abstract). | Lu Bai, Lixin Cui, Ming Li, Peng Ren, Yue Wang, Lichi Zhang, Philip S. Yu, Edwin R. Hancock |
| 2025 | ICDE | HAQJSK: Hierarchical-Aligned Quantum Jensen-Shannon Kernels for Graph Classification (Extended Abstract). | Lu Bai, Lixin Cui, Yue Wang, Ming Li, Jing Li, Philip S. Yu, Edwin R. Hancock |
| 2025 | ICDM | Detecting Intent Drift in Continuous Conversation via Temporal Transition Accumulation. | Yue Wang, Dehang Fu, Jie Tan, Junxiao Han, Yao Wan, Lixin Cui, Lu Bai, Philip S. Yu |
| 2025 | ICML | ENAHPool: The Edge-Node Attention-based Hierarchical Pooling for Graph Neural Networks. | Zhehan Zhao, Lu Bai, Lixin Cui, Ming Li, Ziyu Lyu, Lixiang Xu, Yue Wang, Edwin R. Hancock |
| 2025 | IJCAI | AKBR: Learning Adaptive Kernel-based Representations for Graph Classification. | Lu Bai, Feifei Qian, Lixin Cui, Ming Li, Hangyuan Du, Yue Wang, Edwin R. Hancock |
| 2025 | IJCAI | Exploring the Over-smoothing Problem of Graph Neural Networks for Graph Classification: An Entropy-based Viewpoint. | Feifei Qian, Lu Bai, Lixin Cui, Ming Li, Hangyuan Du, Yue Wang, Edwin R. Hancock |
| 2025 | IJCAI | HA-SCN: Learning Hierarchical Aligned Subtree Convolutional Networks for Graph Classification. | Xinya Qin, Lu Bai, Lixin Cui, Ming Li, Hangyuan Du, Yue Wang, Edwin R. Hancock |
| 2025 | IJCAI | DHTAGK: Deep Hierarchical Transitive-Aligned Graph Kernels for Graph Classification. | Xinya Qin, Lu Bai, Lixin Cui, Ming Li, Ziyu Lyu, Hangyuan Du, Edwin R. Hancock |
| 2025 | IJCAI | An End-to-End Simple Clustering Hierarchical Pooling Operation for Graph Learning Based on Top-K Node Selection. | Zhehan Zhao, Lu Bai, Ming Li, Lixin Cui, Hangyuan Du, Yue Wang, Edwin R. Hancock |
| 2025 | SIGIR | FairWork: A Generic Framework For Evaluating Fairness In LLM-Based Job Recommender System. | Yuhan Hu, Ziyu Lyu, Lu Bai, Lixin Cui |
| 2024 | ICML | QBMK: Quantum-based Matching Kernels for Un-attributed Graphs. | Lu Bai, Lixin Cui, Ming Li, Yue Wang, Edwin R. Hancock |
| 2022 | ICDE | Learning Graph Convolutional Networks based on Quantum Vertex Information Propagation (Extended Abstract). | Lu Bai, Yuhang Jiao, Lixin Cui, Luca Rossi, Yue Wang, Philip S. Yu, Edwin R. Hancock |
| 2022 | ICML | A Hierarchical Transitive-Aligned Graph Kernel for Un-attributed Graphs. | Lu Bai, Lixin Cui, Edwin R. Hancock |
| 2022 | ICPR | ABDPool: Attention-based Differentiable Pooling. | Yue Liu, Lixin Cui, Yue Wang, Lu Bai |
| 2021 | PRICAI | ABAE: Utilize Attention to Boost Graph Auto-Encoder. | Tianyu Liu, Yifan Li, Yujie Sun, Lixin Cui, Lu Bai |
| 2020 | ICPR | Cross-Supervised Joint-Event-Extraction with Heterogeneous Information Networks. | Yue Wang, Zhuo Xu, Lu Bai, Yao Wan, Lixin Cui, Qian Zhao, Edwin R. Hancock, Philip S. Yu |
| 2020 | IJCAI | A Quantum-inspired Entropic Kernel for Multiple Financial Time Series Analysis. | Lu Bai, Lixin Cui, Yue Wang, Yuhang Jiao, Edwin R. Hancock |
| 2020 | SSPR | Alzheimer's Brain Network Analysis Using Sparse Learning Feature Selection. | Lixin Cui, Lichi Zhang, Lu Bai, Yue Wang, Edwin R. Hancock |
| 2020 | SSPR | LGL-GNN: Learning Global and Local Information for Graph Neural Networks. | Huan Li, Boyuan Wang, Lixin Cui, Lu Bai, Edwin R. Hancock |
| 2020 | SSPR | Graph Transformer: Learning Better Representations for Graph Neural Networks. | Boyuan Wang, Lixin Cui, Lu Bai, Edwin R. Hancock |
| 2019 | ICDM | Competitive Multi-agent Deep Reinforcement Learning with Counterfactual Thinking. | Yue Wang, Yao Wan, Chenwei Zhang, Lu Bai, Lixin Cui, Philip S. Yu |
| 2019 | ISPA | Finding Potential Empathizers in an Online Mental Health Community: A Deep Graph Embedding Approach. | Yibo Chai, Yahu Cong, Rui Sun, Fengyang Wu, Zhongliang Zhang, Yexing Wan, Lixin Cui |
| 2018 | ICPR | A Deep Hybrid Graph Kernel Through Deep Learning Networks. | Lixin Cui, Lu Bai, Luca Rossi, Yue Wang, Yuhang Jiao, Edwin R. Hancock |
| 2018 | ICPR | Depth-based Subgraph Convolutional Neural Networks. | Chuanyu Xu, Dong Wang, Zhihong Zhang, Beizhan Wang, Da Zhou, Guijun Ren, Lu Bai, Lixin Cui, Edwin R. Hancock |
| 2018 | SSPR | A Preliminary Survey of Analyzing Dynamic Time-Varying Financial Networks Using Graph Kernels. | Lixin Cui, Lu Bai, Luca Rossi, Zhihong Zhang, Yuhang Jiao, Edwin R. Hancock |
| 2018 | SSPR | A Mixed Entropy Local-Global Reproducing Kernel for Attributed Graphs. | Lixin Cui, Lu Bai, Luca Rossi, Zhihong Zhang, Lixiang Xu, Edwin R. Hancock |
| 2018 | SSPR | Analyzing Time Series from Chinese Financial Market Using a Linear-Time Graph Kernel. | Yuhang Jiao, Lixin Cui, Lu Bai, Yue Wang |
| 2018 | SSPR | Directed Network Analysis Using Transfer Entropy Component Analysis. | Meihong Wu, Yangbin Zeng, Zhihong Zhang, Haiyun Hong, Zhuobin Xu, Lixin Cui, Lu Bai, Edwin R. Hancock |
| 2018 | SSPR | Single Image Super Resolution via Neighbor Reconstruction. | Zhihong Zhang, Zhuobin Xu, Zhiling Ye, Yiqun Hu, Lixin Cui, Lu Bai |
| 2017 | ICNC | The bounds of premium and a fuzzy insurance model under risk aversion utility preference. | Ying Liu, Xiaozhong Li, Dan Wang, Lixin Cui |
| 2016 | ICPR | A transitive aligned Weisfeiler-Lehman subtree kernel. | Lu Bai, Luca Rossi, Lixin Cui, Edwin R. Hancock |
| 2016 | ICPR | A novel entropy-based graph signature from the average mixing matrix. | Lu Bai, Luca Rossi, Lixin Cui, Edwin R. Hancock |
| 2016 | ICPR | An edge-based matching kernel on commute-time spanning trees. | Lu Bai, Lixin Cui, Francisco Escolano, Edwin R. Hancock |
| 2016 | ICPR | Shape classification with a vertex clustering graph kernel. | Lu Bai, Lixin Cui, Yue Wang, Xin Jin, Xiao Bai, Edwin R. Hancock |
| 2016 | SSPR | P2P Lending Analysis Using the Most Relevant Graph-Based Features. | Lixin Cui, Lu Bai, Yue Wang, Xiao Bai, Zhihong Zhang, Edwin R. Hancock |