| 2026 | AAAI | BOFA: Bridge-Layer Orthogonal Low-Rank Fusion for CLIP-Based Class-Incremental Learning. | Lan Li, Tao Hu, Da-Wei Zhou, Jia-Qi Yang, Han-Jia Ye, De-Chuan Zhan |
| 2026 | EACL | Logits-Based Block Pruning with Affine Transformations for Large Language Models. | Zekun Hu, Yichu Xu, De-Chuan Zhan |
| 2025 | AAAI | MIETT: Multi-Instance Encrypted Traffic Transformer for Encrypted Traffic Classification. | Xu-Yang Chen, Lu Han, De-Chuan Zhan, Han-Jia Ye |
| 2025 | AAAI | MOS: Model Surgery for Pre-Trained Model-Based Class-Incremental Learning. | Hai-Long Sun, Da-Wei Zhou, Hanbin Zhao, Le Gan, De-Chuan Zhan, Han-Jia Ye |
| 2025 | AAAI | Capability Instruction Tuning. | Yi-Kai Zhang, De-Chuan Zhan, Han-Jia Ye |
| 2025 | ACL | Maximizing the Effectiveness of Larger BERT Models for Compression. | Wen-Shu Fan, Su Lu, Shangyu Xing, Xin-Chun Li, De-Chuan Zhan |
| 2025 | CVPR | Dual Consolidation for Pre-Trained Model-Based Domain-Incremental Learning. | Da-Wei Zhou, Zi-Wen Cai, Han-Jia Ye, Lijun Zhang, De-Chuan Zhan |
| 2025 | CVPR | Task-Agnostic Guided Feature Expansion for Class-Incremental Learning. | Bowen Zheng, Da-Wei Zhou, Han-Jia Ye, De-Chuan Zhan |
| 2025 | EMNLP | DART: Distilling Autoregressive Reasoning to Silent Thought. | Nan Jiang, Ziming Wu, De-Chuan Zhan, Fuming Lai, Shaobing Lian |
| 2025 | ICCV | External Knowledge Injection for CLIP-Based Class-Incremental Learning. | Da-Wei Zhou, Kai-Wen Li, Jingyi Ning, Han-Jia Ye, Lijun Zhang, De-Chuan Zhan |
| 2025 | ICLR | Revisiting Nearest Neighbor for Tabular Data: A Deep Tabular Baseline Two Decades Later. | Han-Jia Ye, Huai-Hong Yin, De-Chuan Zhan, Wei-Lun Chao |
| 2025 | ICLR | ZooProbe: A Data Engine for Evaluating, Exploring, and Evolving Large-scale Training Data for Multimodal LLMs. | Yi-Kai Zhang, Shiyin Lu, Qing-Guo Chen, De-Chuan Zhan, Han-Jia Ye |
| 2025 | ICML | Addressing Imbalanced Domain-Incremental Learning through Dual-Balance Collaborative Experts. | Lan Li, Da-Wei Zhou, Han-Jia Ye, De-Chuan Zhan |
| 2025 | ICML | Improving LLMs for Recommendation with Out-Of-Vocabulary Tokens. | Ting-Ji Huang, Jia-Qi Yang, Chunxu Shen, Kai-Qi Liu, De-Chuan Zhan, Han-Jia Ye |
| 2025 | ICML | Compositional Condition Question Answering in Tabular Understanding. | Jun-Peng Jiang, Tao Zhou, De-Chuan Zhan, Han-Jia Ye |
| 2025 | ICML | Parrot: Multilingual Visual Instruction Tuning. | Hai-Long Sun, Da-Wei Zhou, Yang Li, Shiyin Lu, Chao Yi, Qing-Guo Chen, Zhao Xu, Weihua Luo, Kaifu Zhang, De-Chuan Zhan, Han-Jia Ye |
| 2025 | ICML | FOUNDER: Grounding Foundation Models in World Models for Open-Ended Embodied Decision Making. | Yucen Wang, Rui Yu, Shenghua Wan, Le Gan, De-Chuan Zhan |
| 2025 | IJCAI | Reward Models in Deep Reinforcement Learning: A Survey. | Rui Yu, Shenghua Wan, Yucen Wang, Chen-Xiao Gao, Le Gan, Zongzhang Zhang, De-Chuan Zhan |
| 2024 | AAAI | Twice Class Bias Correction for Imbalanced Semi-supervised Learning. | Lan Li, Bowen Tao, Lu Han, De-Chuan Zhan, Han-Jia Ye |
| 2024 | CVPR | Expandable Subspace Ensemble for Pre-Trained Model-Based Class-Incremental Learning. | Da-Wei Zhou, Hai-Long Sun, Han-Jia Ye, De-Chuan Zhan |
| 2024 | CVPR | Leveraging Cross-Modal Neighbor Representation for Improved CLIP Classification. | Chao Yi, Lu Ren, De-Chuan Zhan, Han-Jia Ye |
| 2024 | ECAI | Weight Scope Alignment: A Frustratingly Easy Method for Model Merging. | Yichu Xu, Xin-Chun Li, Le Gan, De-Chuan Zhan |
| 2024 | ICASSP | CLAF: Contrastive Learning with Augmented Features for Imbalanced Semi-Supervised Learning. | Bowen Tao, Lan Li, Xin-Chun Li, De-Chuan Zhan |
| 2024 | ICML | Revisit the Essence of Distilling Knowledge through Calibration. | Wen-Shu Fan, Su Lu, Xin-Chun Li, De-Chuan Zhan, Le Gan |
| 2024 | ICML | SIN: Selective and Interpretable Normalization for Long-Term Time Series Forecasting. | Lu Han, Han-Jia Ye, De-Chuan Zhan |
| 2024 | ICML | Tabular Insights, Visual Impacts: Transferring Expertise from Tables to Images. | Jun-Peng Jiang, Han-Jia Ye, Leye Wang, Yang Yang, Yuan Jiang, De-Chuan Zhan |
| 2024 | ICML | Enhancing Class-Imbalanced Learning with Pre-Trained Guidance through Class-Conditional Knowledge Distillation. | Lan Li, Xin-Chun Li, Han-Jia Ye, De-Chuan Zhan |
| 2024 | ICML | MLI Formula: A Nearly Scale-Invariant Solution with Noise Perturbation. | Bowen Tao, Xin-Chun Li, De-Chuan Zhan |
| 2024 | ICML | SeMOPO: Learning High-quality Model and Policy from Low-quality Offline Visual Datasets. | Shenghua Wan, Ziyuan Chen, Le Gan, Shuai Feng, De-Chuan Zhan |
| 2024 | ICML | AD3: Implicit Action is the Key for World Models to Distinguish the Diverse Visual Distractors. | Yucen Wang, Shenghua Wan, Le Gan, Shuai Feng, De-Chuan Zhan |
| 2024 | ICML | Multi-layer Rehearsal Feature Augmentation for Class-Incremental Learning. | Bowen Zheng, Da-Wei Zhou, Han-Jia Ye, De-Chuan Zhan |
| 2024 | IJCAI | Continual Learning with Pre-Trained Models: A Survey. | Da-Wei Zhou, Hai-Long Sun, Jingyi Ning, Han-Jia Ye, De-Chuan Zhan |
| 2024 | IJCAI | MOSER: Learning Sensory Policy for Task-specific Viewpoint via View-conditional World Model. | Shenghua Wan, Hai-Hang Sun, Le Gan, De-Chuan Zhan |
| 2024 | MICCAI | CS3: Cascade SAM for Sperm Segmentation. | Yi Shi, Xu-Peng Tian, Yun-Kai Wang, Tie-Yi Zhang, Bing Yao, Hui Wang, Yong Shao, Cen-Cen Wang, Rong Zeng, De-Chuan Zhan |
| 2024 | UAI | RE-SORT: Removing Spurious Correlation in Multilevel Interaction for CTR Prediction. | Songli Wu, Liang Du, Jiaqi Yang, Yuai Wang, De-Chuan Zhan, Shuang Zhao, Zixun Sun |
| 2023 | CVPR | Learning Debiased Representations via Conditional Attribute Interpolation. | Yi-Kai Zhang, Qi-Wei Wang, De-Chuan Zhan, Han-Jia Ye |
| 2023 | ICLR | A Model or 603 Exemplars: Towards Memory-Efficient Class-Incremental Learning. | Da-Wei Zhou, Qi-Wei Wang, Han-Jia Ye, De-Chuan Zhan |
| 2023 | ICLR | Augmentation Component Analysis: Modeling Similarity via the Augmentation Overlaps. | Lu Han, Han-Jia Ye, De-Chuan Zhan |
| 2023 | ICLR | BEEF: Bi-Compatible Class-Incremental Learning via Energy-Based Expansion and Fusion. | Fu-Yun Wang, Da-Wei Zhou, Liu Liu, Han-Jia Ye, Yatao Bian, De-Chuan Zhan, Peilin Zhao |
| 2023 | ICLR | One Important Thing To Do Before Federated Training. | Yichu Xu, Wenqian Li, Yinchuan Li, Yunfeng Shao, Yan Pang, De-Chuan Zhan |
| 2023 | ICML | SeMAIL: Eliminating Distractors in Visual Imitation via Separated Models. | Shenghua Wan, Yucen Wang, Minghao Shao, Ruying Chen, De-Chuan Zhan |
| 2023 | KDD | IDToolkit: A Toolkit for Benchmarking and Developing Inverse Design Algorithms in Nanophotonics. | Jia-Qi Yang, Yucheng Xu, Jia-Lei Shen, Ke-Bin Fan, De-Chuan Zhan, Yang Yang |
| 2023 | MICCAI | A Multi-task Method for Immunofixation Electrophoresis Image Classification. | Yi Shi, Rui-Xiang Li, Wen-Qi Shao, Xincen Duan, Han-Jia Ye, De-Chuan Zhan, Bai-Shen Pan, Beili Wang, Wei Guo, Yuan Jiang |
| 2022 | AAAI | RID-Noise: Towards Robust Inverse Design under Noisy Environments. | Jia-Qi Yang, Ke-Bin Fan, Hao Ma, De-Chuan Zhan |
| 2022 | CVPR | Forward Compatible Few-Shot Class-Incremental Learning. | Da-Wei Zhou, Fu-Yun Wang, Han-Jia Ye, Liang Ma, Shiliang Pu, De-Chuan Zhan |
| 2022 | CVPR | Federated Learning with Position-Aware Neurons. | Xin-Chun Li, Yichu Xu, Shaoming Song, Bingshuai Li, Yinchuan Li, Yunfeng Shao, De-Chuan Zhan |
| 2022 | CVPR | Identifying Ambiguous Similarity Conditions via Semantic Matching. | Han-Jia Ye, Yi Shi, De-Chuan Zhan |
| 2022 | ECCV | FOSTER: Feature Boosting and Compression for Class-Incremental Learning. | Fu-Yun Wang, Da-Wei Zhou, Han-Jia Ye, De-Chuan Zhan |
| 2022 | ICASSP | Exploring Transferability Measures and Domain Selection in Cross-Domain Slot Filling. | Xin-Chun Li, Yan-Jia Wang, Le Gan, De-Chuan Zhan |
| 2022 | Interspeech | Avoid Overfitting User Specific Information in Federated Keyword Spotting. | Xin-Chun Li, Jin-Lin Tang, Shaoming Song, Bingshuai Li, Yinchuan Li, Yunfeng Shao, Le Gan, De-Chuan Zhan |
| 2022 | Interspeech | Audio-Visual Generalized Few-Shot Learning with Prototype-Based Co-Adaptation. | Yi-Kai Zhang, Da-Wei Zhou, Han-Jia Ye, De-Chuan Zhan |
| 2022 | KDD | Streaming Hierarchical Clustering Based on Point-Set Kernel. | Xin Han, Ye Zhu, Kai Ming Ting, De-Chuan Zhan, Gang Li |
| 2021 | AAAI | Tailoring Embedding Function to Heterogeneous Few-Shot Tasks by Global and Local Feature Adaptors. | Su Lu, Han-Jia Ye, De-Chuan Zhan |
| 2021 | AAAI | Capturing Delayed Feedback in Conversion Rate Prediction via Elapsed-Time Sampling. | Jia-Qi Yang, Xiang Li, Shuguang Han, Tao Zhuang, De-Chuan Zhan, Xiaoyi Zeng, Bin Tong |
| 2021 | AAAI | Task Cooperation for Semi-Supervised Few-Shot Learning. | Han-Jia Ye, Xin-Chun Li, De-Chuan Zhan |
| 2021 | CVPR | Learning Placeholders for Open-Set Recognition. | Da-Wei Zhou, Han-Jia Ye, De-Chuan Zhan |
| 2021 | ICCV | Procrustean Training for Imbalanced Deep Learning. | Han-Jia Ye, De-Chuan Zhan, Wei-Lun Chao |
| 2021 | IJCAI | Rethinking Label-Wise Cross-Modal Retrieval from A Semantic Sharing Perspective. | Yang Yang, Chubing Zhang, Yi-Chu Xu, Dianhai Yu, De-Chuan Zhan, Jian Yang |
| 2021 | IJCNN | Multi-Modal Multi-Instance Multi-Label Learning with Graph Convolutional Network. | Cheng Hang, Wei Wang, De-Chuan Zhan |
| 2021 | KDD | FedRS: Federated Learning with Restricted Softmax for Label Distribution Non-IID Data. | Xin-Chun Li, De-Chuan Zhan |
| 2021 | PAKDD | Detecting Sequentially Novel Classes with Stable Generalization Ability. | Da-Wei Zhou, Yang Yang, De-Chuan Zhan |
| 2020 | CVPR | Few-Shot Learning via Embedding Adaptation With Set-to-Set Functions. | Han-Jia Ye, Hexiang Hu, De-Chuan Zhan, Fei Sha |
| 2020 | CVPR | Distilling Cross-Task Knowledge via Relationship Matching. | Han-Jia Ye, Su Lu, De-Chuan Zhan |
| 2020 | PAKDD | Towards Understanding Transfer Learning Algorithms Using Meta Transfer Features. | Xin-Chun Li, De-Chuan Zhan, Jia-Qi Yang, Yi Shi, Cheng Hang, Yi Lu |
| 2020 | PAKDD | Bottom-Up and Top-Down Graph Pooling. | Jia-Qi Yang, De-Chuan Zhan, Xin-Chun Li |
| 2019 | AAAI | Multi-View Anomaly Detection: Neighborhood in Locality Matters. | Xiang-Rong Sheng, De-Chuan Zhan, Su Lu, Yuan Jiang |
| 2019 | AAAI | Deep Robust Unsupervised Multi-Modal Network. | Yang Yang, Yi-Feng Wu, De-Chuan Zhan, Zhi-Bin Liu, Yuan Jiang |
| 2019 | IJCAI | Automatic Successive Reinforcement Learning with Multiple Auxiliary Rewards. | Zhao-Yang Fu, De-Chuan Zhan, Xin-Chun Li, Yi-Xing Lu |
| 2019 | IJCAI | Comprehensive Semi-Supervised Multi-Modal Learning. | Yang Yang, Ke-Tao Wang, De-Chuan Zhan, Hui Xiong, Yuan Jiang |
| 2019 | KDD | Adaptive Deep Models for Incremental Learning: Considering Capacity Scalability and Sustainability. | Yang Yang, Da-Wei Zhou, De-Chuan Zhan, Hui Xiong, Yuan Jiang |
| 2018 | ICDM | Learning Semantic Features for Software Defect Prediction by Code Comments Embedding. | Xuan Huo, Yang Yang, Ming Li, De-Chuan Zhan |
| 2018 | ICML | Rectify Heterogeneous Models with Semantic Mapping. | Han-Jia Ye, De-Chuan Zhan, Yuan Jiang, Zhi-Hua Zhou |
| 2018 | IJCAI | Semi-Supervised Multi-Modal Learning with Incomplete Modalities. | Yang Yang, De-Chuan Zhan, Xiang-Rong Sheng, Yuan Jiang |
| 2018 | IJCAI | Distance Metric Facilitated Transportation between Heterogeneous Domains. | Han-Jia Ye, Xiang-Rong Sheng, De-Chuan Zhan, Peng He |
| 2018 | KDD | Complex Object Classification: A Multi-Modal Multi-Instance Multi-Label Deep Network with Optimal Transport. | Yang Yang, Yi-Feng Wu, De-Chuan Zhan, Zhi-Bin Liu, Yuan Jiang |
| 2018 | PAKDD | Multi-network User Identification via Graph-Aware Embedding. | Yang Yang, De-Chuan Zhan, Yi-Feng Wu, Yuan Jiang |
| 2018 | PRICAI | Deep Multi-modal Learning with Cascade Consensus. | Yang Yang, Yi-Feng Wu, De-Chuan Zhan, Yuan Jiang |
| 2017 | AAAI | Deep Learning for Fixed Model Reuse. | Yang Yang, De-Chuan Zhan, Ying Fan, Yuan Jiang, Zhi-Hua Zhou |
| 2017 | ACML | Instance Specific Discriminative Modal Pursuit: A Serialized Approach. | Yang Yang, De-Chuan Zhan, Ying Fan, Yuan Jiang |
| 2017 | IJCAI | Modal Consistency based Pre-Trained Multi-Model Reuse. | Yang Yang, De-Chuan Zhan, Xiang-Yu Guo, Yuan Jiang |
| 2017 | IJCAI | Learning Mahalanobis Distance Metric: Considering Instance Disturbance Helps. | Han-Jia Ye, De-Chuan Zhan, Xue-Min Si, Yuan Jiang |
| 2016 | AAAI | Instance Specific Metric Subspace Learning: A Bayesian Approach. | Han-Jia Ye, De-Chuan Zhan, Yuan Jiang |
| 2016 | AAAI | Learning Expected Hitting Time Distance. | De-Chuan Zhan, Peng Hu, Zui Chu, Zhi-Hua Zhou |
| 2016 | ACML | Learning Feature Aware Metric. | Han-Jia Ye, De-Chuan Zhan, Xue-Min Si, Yuan Jiang |
| 2016 | ICDM | College Student Scholarships and Subsidies Granting: A Multi-modal Multi-label Approach. | Han-Jia Ye, De-Chuan Zhan, Xiaolin Li, Zhen-Chuan Huang, Yuan Jiang |
| 2016 | IJCAI | Learning by Actively Querying Strong Modal Features. | Yang Yang, De-Chuan Zhan, Yuan Jiang |
| 2015 | CIKM | Rank Consistency based Multi-View Learning: A Privacy-Preserving Approach. | Han-Jia Ye, De-Chuan Zhan, Yuan Miao, Yuan Jiang, Zhi-Hua Zhou |
| 2015 | IJCAI | Auxiliary Information Regularized Machine for Multiple Modality Feature Learning. | Yang Yang, Han-Jia Ye, De-Chuan Zhan, Yuan Jiang |
| 2013 | IJCAI | Multi-Modal Image Annotation with Multi-Instance Multi-Label LDA. | Cam-Tu Nguyen, De-Chuan Zhan, Zhi-Hua Zhou |
| 2009 | ICML | Learning instance specific distances using metric propagation. | De-Chuan Zhan, Ming Li, Yufeng Li, Zhi-Hua Zhou |
| 2007 | AAAI | Semi-Supervised Learning with Very Few Labeled Training Examples. | Zhi-Hua Zhou, De-Chuan Zhan, Qiang Yang |
| 2006 | PAKDD | Neighbor Line-Based Locally Linear Embedding. | De-Chuan Zhan, Zhi-Hua Zhou |