| 2026 | AAAI | Point Cloud Semantic Scene Completion with Prototype-Guided Transformer. | Chenghao Fang, Jianqing Liang, Jiye Liang, Zijin Du, Feilong Cao |
| 2026 | AAAI | Semantic Guided Part Relation-aware Network for Point Cloud Completion. | Zhensheng Zhou, Jianqing Liang, Jiye Liang, Zijin Du, Chenghao Fang |
| 2026 | WWW | Graph Adversarial Defense via Hilbert-Schmidt Independence Criterion against Influence Maximization Attacks. | Yuxing Guo, Jianqing Liang, Kaixuan Yao, Zhihao Guo, Jiye Liang |
| 2025 | AAAI | Graph Segmentation and Contrastive Enhanced Explainer for Graph Neural Networks. | Zhiqiang Wang, Jiayu Guo, Jianqing Liang, Jiye Liang, Shiying Cheng, Jiarong Zhang |
| 2025 | AAAI | Label Noise Correction via Fuzzy Learning Machine. | Jiye Liang, Yixiao Li, Junbiao Cui |
| 2025 | AAAI | GNN-Transformer Cooperative Architecture for Trustworthy Graph Contrastive Learning. | Jianqing Liang, Xinkai Wei, Min Chen, Zhiqiang Wang, Jiye Liang |
| 2025 | AAAI | Improving Generalization in Offline Reinforcement Learning via Latent Distribution Representation Learning. | Da Wang, Lin Li, Wei Wei, Qixian Yu, Jianye Hao, Jiye Liang |
| 2025 | CVPR | Learning Textual Prompts for Open-World Semi-Supervised Learning. | Yuxin Fan, Junbiao Cui, Jiye Liang |
| 2025 | DASFAA | Explaining Black-Box Language Models with Knowledge Probing Systems: A Post-hoc Explanation Perspective. | Yunxiao Zhao, Hao Xu, Zhiqiang Wang, Xiaoli Li, Jiye Liang, Ru Li |
| 2025 | ECAI | Cross-Channel Graph Attention Mechanism for Deep Convolutional Neural Networks. | Kaixuan Yao, Mingxu Zhang, Jiao Zhao, Junbiao Cui, Jiye Liang |
| 2025 | ICML | EduLLM: Leveraging Large Language Models and Framelet-Based Signed Hypergraph Neural Networks for Student Performance Prediction. | Ming Li, Yukang Cheng, Lu Bai, Feilong Cao, Ke Lv, Jiye Liang, Pietro Lio |
| 2025 | ICML | Human Cognition-Inspired Hierarchical Fuzzy Learning Machine. | Junbiao Cui, Qin Yue, Jianqing Liang, Jiye Liang |
| 2025 | ICML | Federated Causal Structure Learning with Non-identical Variable Sets. | Yunxia Wang, Fuyuan Cao, Kui Yu, Jiye Liang |
| 2025 | ICML | Counterfactual Contrastive Learning with Normalizing Flows for Robust Treatment Effect Estimation. | Jiaxuan Zhang, Emadeldeen Eldele, Fuyuan Cao, Yang Wang, Xiaoli Li, Jiye Liang |
| 2025 | IJCAI | Open-World Semi-Supervised Learning with Class Semantic Correlations. | Yuxin Fan, Junbiao Cui, Jiye Liang, Jianqing Liang |
| 2025 | IJCAI | Multi-Modal Point Cloud Completion with Interleaved Attention Enhanced Transformer. | Chenghao Fang, Jianqing Liang, Jiye Liang, Hangkun Wang, Kaixuan Yao, Feilong Cao |
| 2025 | IJCAI | Uncertainty-guided Graph Contrastive Learning from a Unified Perspective. | Zhiqiang Li, Jie Wang, Jianqing Liang, Junbiao Cui, Xingwang Zhao, Jiye Liang |
| 2025 | IJCAI | MATCH: Modality-Calibrated Hypergraph Fusion Network for Conversational Emotion Recognition. | Jiandong Shi, Ming Li, Lu Bai, Feilong Cao, Ke Lu, Jiye Liang |
| 2025 | IJCNN | Multimodal enhanced Explainable Recommendation with Contrastive Learning. | Kaihan Zhang, Zixuan Wang, Kangchi Liu, Ping Chen, Peng Song, Jiye Liang |
| 2025 | SIGIR | Hyperbolic Multi-Criteria Rating Recommendation. | Zhihao Guo, Ting Han, Peng Song, Chenjiao Feng, Kaixuan Yao, Jiye Liang |
| 2025 | WSDM | Hawkes Point Process-enhanced Dynamic Graph Neural Network. | Zhiqiang Wang, Baijing Hu, Kaixuan Yao, Jiye Liang |
| 2024 | ACL | FRVA: Fact-Retrieval and Verification Augmented Entailment Tree Generation for Explainable Question Answering. | Yue Fan, Hu Zhang, Ru Li, Yujie Wang, Hongye Tan, Jiye Liang |
| 2024 | ACL | InstructEd: Soft-Instruction Tuning for Model Editing with Hops. | Xiaoqi Han, Ru Li, Xiaoli Li, Jiye Liang, Zifang Zhang, Jeff Z. Pan |
| 2024 | ACL | Hyperspherical Multi-Prototype with Optimal Transport for Event Argument Extraction. | Guangjun Zhang, Hu Zhang, Yujie Wang, Ru Li, Hongye Tan, Jiye Liang |
| 2024 | ACL | AGR: Reinforced Causal Agent-Guided Self-explaining Rationalization. | Yunxiao Zhao, Zhiqiang Wang, Xiaoli Li, Jiye Liang, Ru Li |
| 2024 | ICML | Graph External Attention Enhanced Transformer. | Jianqing Liang, Min Chen, Jiye Liang |
| 2024 | ICML | Improving Generalization in Offline Reinforcement Learning via Adversarial Data Splitting. | Da Wang, Lin Li, Wei Wei, Qixian Yu, Jianye Hao, Jiye Liang |
| 2024 | MICCAI | Uncertainty-Aware Multi-view Learning for Prostate Cancer Grading with DWI. | Zhicheng Dong, Xiaodong Yue, Yufei Chen, Xujing Zhou, Jiye Liang |
| 2023 | ACL | Dynamic Heterogeneous-Graph Reasoning with Language Models and Knowledge Representation Learning for Commonsense Question Answering. | Yujie Wang, Hu Zhang, Jiye Liang, Ru Li |
| 2023 | ICML | A General Representation Learning Framework with Generalization Performance Guarantees. | Junbiao Cui, Jianqing Liang, Qin Yue, Jiye Liang |
| 2023 | ICML | How Powerful are Shallow Neural Networks with Bandlimited Random Weights? | Ming Li, Sho Sonoda, Feilong Cao, Yu Guang Wang, Jiye Liang |
| 2023 | ICML | Set-membership Belief State-based Reinforcement Learning for POMDPs. | Wei Wei, Lijun Zhang, Lin Li, Huizhong Song, Jiye Liang |
| 2023 | WSDM | Graph Neural Networks with Interlayer Feature Representation for Image Super-Resolution. | Shenggui Tang, Kaixuan Yao, Jianqing Liang, Zhiqiang Wang, Jiye Liang |
| 2022 | AAAI | Controlling Underestimation Bias in Reinforcement Learning via Quasi-median Operation. | Wei Wei, Yujia Zhang, Jiye Liang, Lin Li, Yuze Li |
| 2022 | AAAI | Instance Selection: A Bayesian Decision Theory Perspective. | Qingqiang Chen, Fuyuan Cao, Ying Xing, Jiye Liang |
| 2022 | AAAI | Efficient Causal Structure Learning from Multiple Interventional Datasets with Unknown Targets. | Yunxia Wang, Fuyuan Cao, Kui Yu, Jiye Liang |
| 2022 | KDD | Dual Bidirectional Graph Convolutional Networks for Zero-shot Node Classification. | Qin Yue, Jiye Liang, Junbiao Cui, Liang Bai |
| 2022 | WSDM | Multi-Scale Variational Graph AutoEncoder for Link Prediction. | Zhihao Guo, Feng Wang, Kaixuan Yao, Jiye Liang, Zhiqiang Wang |
| 2020 | AAAI | A Three-Level Optimization Model for Nonlinearly Separable Clustering. | Liang Bai, Jiye Liang |
| 2020 | AAAI | A Cluster-Weighted Kernel K-Means Method for Multi-View Clustering. | Jing Liu, Fuyuan Cao, Xiao-Zhi Gao, Liqin Yu, Jiye Liang |
| 2020 | ICML | Sparse Subspace Clustering with Entropy-Norm. | Liang Bai, Jiye Liang |
| 2017 | ICDM | Local Bayes Risk Minimization Based Stopping Strategy for Hierarchical Classification. | Yu Wang, Qinghua Hu, Yucan Zhou, Hong Zhao, Yuhua Qian, Jiye Liang |
| 2015 | ICMLC | Multigranulation information fusion: A dempster-shafer evidence theory based clustering ensemble method. | Feijiang Li, Yuhua Qian, Jieting Wang, Jiye Liang |
| 2012 | GRC | Feature selection for large-scale data sets in GrC. | Jiye Liang |
| 2012 | GRC | Variable precision multi-granulation rough set. | Wei Wei, Jiye Liang, Yuhua Qian, Feng Wang |
| 2011 | SMC | How to organize data with measurement errors? | Yuhua Qian, Jiye Liang |
| 2010 | GRC | On Partial Order Relations in Granular Computing. | Hongxing Chen, Yuhua Qian, Jiye Liang, Wei Wei |
| 2010 | ICMLC | A heuristic method to attribute reduction for concept lattice. | Junhong Wang, Jiye Liang, Yuhua Qian |
| 2008 | GRC | Granulation Operators on a Knowledge Base. | Yuhua Qian, Jiye Liang, Wei Wei |
| 2008 | GRC | Change Mechanism of a Decision Table's Decision Performance caused by Attribute Reductions. | Wei Wei, Jiye Liang, Yuhua Qian |
| 2007 | GRC | MGRS in Incomplete Information Systems. | Yuhua Qian, Jiye Liang, Chuangyin Dang |