Rank Consistency based Multi-View Learning: A Privacy-Preserving Approach. - Han-Jia Ye; De-Chuan Zhan; Yuan Miao 002; Yuan Jiang 001; Zhi-Hua Zhou (CIKM, 2015)

Auxiliary Information Regularized Machine for Multiple Modality Feature Learning. - Yang Yang 074; Han-Jia Ye; De-Chuan Zhan; Yuan Jiang 001 (IJCAI, 2015)

Instance Specific Metric Subspace Learning: A Bayesian Approach. - Han-Jia Ye; De-Chuan Zhan; Yuan Jiang 001 (AAAI, 2016)

Learning Feature Aware Metric. - Han-Jia Ye; De-Chuan Zhan; Xue-Min Si; Yuan Jiang 001 (ACML, 2016)

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 001 (ICDM, 2016)

What Makes Objects Similar: A Unified Multi-Metric Learning Approach. - Han-Jia Ye; De-Chuan Zhan; Xue-Min Si; Yuan Jiang 001; Zhi-Hua Zhou (NIPS, 2016)

Learning Mahalanobis Distance Metric: Considering Instance Disturbance Helps. - Han-Jia Ye; De-Chuan Zhan; Xue-Min Si; Yuan Jiang 001 (IJCAI, 2017)

Rectify Heterogeneous Models with Semantic Mapping. - Han-Jia Ye; De-Chuan Zhan; Yuan Jiang 001; Zhi-Hua Zhou (ICML, 2018)

Distance Metric Facilitated Transportation between Heterogeneous Domains. - Han-Jia Ye; Xiang-Rong Sheng; De-Chuan Zhan; Peng He (IJCAI, 2018)

Learning Embedding Adaptation for Few-Shot Learning. - Han-Jia Ye; Hexiang Hu; De-Chuan Zhan; Fei Sha (CoRR, 2018)

Learning Classifier Synthesis for Generalized Few-Shot Learning. - Han-Jia Ye; Hexiang Hu; De-Chuan Zhan; Fei Sha (CoRR, 2019)

Fast generalization rates for distance metric learning. - Han-Jia Ye; De-Chuan Zhan; Yuan Jiang 001 (Mach. Learn., 2019)

What Makes Objects Similar: A Unified Multi-Metric Learning Approach. - Han-Jia Ye; De-Chuan Zhan; Yuan Jiang 001; Zhi-Hua Zhou (IEEE Trans. Pattern Anal. Mach. Intell., 2019)

Few-Shot Learning via Embedding Adaptation With Set-to-Set Functions. - Han-Jia Ye; Hexiang Hu; De-Chuan Zhan; Fei Sha (CVPR, 2020)

Distilling Cross-Task Knowledge via Relationship Matching. - Han-Jia Ye; Su Lu; De-Chuan Zhan (CVPR, 2020)

Identifying and Compensating for Feature Deviation in Imbalanced Deep Learning. - Han-Jia Ye; Hong-You Chen; De-Chuan Zhan; Wei-Lun Chao (CoRR, 2020)

Revisiting Meta-Learning as Supervised Learning. - Wei-Lun Chao; Han-Jia Ye; De-Chuan Zhan; Mark E. Campbell; Kilian Q. Weinberger (CoRR, 2020)

Novelty-Prepared Few-Shot Classification. - Chao Wang; Ruo-Ze Liu; Han-Jia Ye; Yang Yu 001 (CoRR, 2020)

Revisiting Unsupervised Meta-Learning: Amplifying or Compensating for the Characteristics of Few-Shot Tasks. - Han-Jia Ye; Lu Han; De-Chuan Zhan (CoRR, 2020)

Few-shot learning with adaptively initialized task optimizer: a practical meta-learning approach. - Han-Jia Ye; Xiang-Rong Sheng; De-Chuan Zhan (Mach. Learn., 2020)

Learning Multiple Local Metrics: Global Consideration Helps. - Han-Jia Ye; De-Chuan Zhan; Nan Li 019; Yuan Jiang 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2020)

DecAug: Out-of-Distribution Generalization via Decomposed Feature Representation and Semantic Augmentation. - Haoyue Bai 001; Rui Sun; Lanqing Hong; Fengwei Zhou; Nanyang Ye 001; Han-Jia Ye; S.-H. Gary Chan; Zhenguo Li (AAAI, 2021)

Tailoring Embedding Function to Heterogeneous Few-Shot Tasks by Global and Local Feature Adaptors. - Su Lu; Han-Jia Ye; De-Chuan Zhan (AAAI, 2021)

Task Cooperation for Semi-Supervised Few-Shot Learning. - Han-Jia Ye; Xin-Chun Li; De-Chuan Zhan (AAAI, 2021)

Learning Placeholders for Open-Set Recognition. - Da-Wei Zhou 001; Han-Jia Ye; De-Chuan Zhan (CVPR, 2021)

Procrustean Training for Imbalanced Deep Learning. - Han-Jia Ye; De-Chuan Zhan; Wei-Lun Chao (ICCV, 2021)

MULL'21: First International Workshop on Multimedia Understanding with Less Labeling. - Xiu-Shen Wei; Jufeng Yang; Han-Jia Ye; Jian Yang 003 (ACM Multimedia, 2021)

Co-Transport for Class-Incremental Learning. - Da-Wei Zhou 001; Han-Jia Ye; De-Chuan Zhan (ACM Multimedia, 2021)

Towards Enabling Meta-Learning from Target Models. - Su Lu; Han-Jia Ye; Le Gan; De-Chuan Zhan (NeurIPS, 2021)

A$^2$-Net: Learning Attribute-Aware Hash Codes for Large-Scale Fine-Grained Image Retrieval. - Xiu-Shen Wei; Yang Shen; Xuhao Sun; Han-Jia Ye; Jian Yang 003 (NeurIPS, 2021)

Support-Target Protocol for Meta-Learning. - Su Lu; Han-Jia Ye; De-Chuan Zhan (CoRR, 2021)

Few-Shot Action Recognition with Compromised Metric via Optimal Transport. - Su Lu; Han-Jia Ye; De-Chuan Zhan (CoRR, 2021)

Contextualizing Multiple Tasks via Learning to Decompose. - Han-Jia Ye; Da-Wei Zhou 001; Lanqing Hong; Zhenguo Li; Xiu-Shen Wei; De-Chuan Zhan (CoRR, 2021)

Learning Adaptive Classifiers Synthesis for Generalized Few-Shot Learning. - Han-Jia Ye; Hexiang Hu; De-Chuan Zhan (Int. J. Comput. Vis., 2021)

Heterogeneous Few-Shot Model Rectification With Semantic Mapping. - Han-Jia Ye; De-Chuan Zhan; Yuan Jiang 001; Zhi-Hua Zhou (IEEE Trans. Pattern Anal. Mach. Intell., 2021)

Multi-Instance Learning With Emerging Novel Class. - Xiu-Shen Wei; Han-Jia Ye; Xin Mu; Jianxin Wu 001; Chunhua Shen; Zhi-Hua Zhou (IEEE Trans. Knowl. Data Eng., 2021)

Forward Compatible Few-Shot Class-Incremental Learning. - Da-Wei Zhou 001; Fu-Yun Wang; Han-Jia Ye; Liang Ma; Shiliang Pu; De-Chuan Zhan (CVPR, 2022)

Identifying Ambiguous Similarity Conditions via Semantic Matching. - Han-Jia Ye; Yi Shi; De-Chuan Zhan (CVPR, 2022)

FOSTER: Feature Boosting and Compression for Class-Incremental Learning. - Fu-Yun Wang; Da-Wei Zhou 001; Han-Jia Ye; De-Chuan Zhan (ECCV (25), 2022)

How to Train Your MAML to Excel in Few-Shot Classification. - Han-Jia Ye; Wei-Lun Chao (ICLR, 2022)

Audio-Visual Generalized Few-Shot Learning with Prototype-Based Co-Adaptation. - Yi-Kai Zhang; Da-Wei Zhou 001; Han-Jia Ye; De-Chuan Zhan (INTERSPEECH, 2022)

Few-Shot Class-Incremental Learning by Sampling Multi-Phase Tasks. - Da-Wei Zhou 001; Han-Jia Ye; De-Chuan Zhan (CoRR, 2022)

Faculty Distillation with Optimal Transport. - Su Lu; Han-Jia Ye; De-Chuan Zhan (CoRR, 2022)

Contrastive Principal Component Learning: Modeling Similarity by Augmentation Overlap. - Lu Han; Han-Jia Ye; De-Chuan Zhan (CoRR, 2022)

On Pseudo-Labeling for Class-Mismatch Semi-Supervised Learning. - Lu Han; Han-Jia Ye; De-Chuan Zhan (Trans. Mach. Learn. Res., 2022)

Change Point Detection via Synthetic Signals. - Ting-Ji Huang; Qi-Le Zhou; Han-Jia Ye; De-Chuan Zhan (AALTD@ECML/PKDD, 2023)

Learning Debiased Representations via Conditional Attribute Interpolation. - Yi-Kai Zhang; Qi-Wei Wang; De-Chuan Zhan; Han-Jia Ye (CVPR, 2023)

A Model or 603 Exemplars: Towards Memory-Efficient Class-Incremental Learning. - Da-Wei Zhou 001; Qi-Wei Wang; Han-Jia Ye; De-Chuan Zhan (ICLR, 2023)

Augmentation Component Analysis: Modeling Similarity via the Augmentation Overlaps. - Lu Han; Han-Jia Ye; De-Chuan Zhan (ICLR, 2023)

BEEF: Bi-Compatible Class-Incremental Learning via Energy-Based Expansion and Fusion. - Fu-Yun Wang; Da-Wei Zhou 001; Liu Liu 014; Han-Jia Ye; Yatao Bian; De-Chuan Zhan; Peilin Zhao (ICLR, 2023)

Improved Dynamic Spatial-Temporal Attention Network for Early Anticipation of Traffic Accidents. - Chao Yi; Ting-Ji Huang; Han-Jia Ye; De-Chuan Zhan (ICME Workshops, 2023)

Preserving Locality in Vision Transformers for Class Incremental Learning. - Bowen Zheng; Da-Wei Zhou 001; Han-Jia Ye; De-Chuan Zhan (ICME, 2023)

A Multi-task Method for Immunofixation Electrophoresis Image Classification. - Yi Shi; Rui-Xiang Li; Wen-Qi Shao; Xin-Cen Duan; Han-Jia Ye; De-Chuan Zhan; Bai-Shen Pan; Bei-Li Wang; Wei Guo; Yuan Jiang 001 (MICCAI (6), 2023)

Few-Shot Class-Incremental Learning via Training-Free Prototype Calibration. - Qi-Wei Wang; Da-Wei Zhou 001; Yi-Kai Zhang; De-Chuan Zhan; Han-Jia Ye (NeurIPS, 2023)

Model Spider: Learning to Rank Pre-Trained Models Efficiently. - Yi-Kai Zhang; Ting-Ji Huang; Yao-Xiang Ding 001; De-Chuan Zhan; Han-Jia Ye (NeurIPS, 2023)

Transductive Fire-Affected Area Segmentation Using False-Color Composite Data. - Chao Yi; Xu-Yang Chen; Lu Ren; Han-Jia Ye; De-Chuan Zhan (PKDD/ECML Workshops (5), 2023)

On Transferring Expert Knowledge from Tabular Data to Images. - Jun-Peng Jiang; Han-Jia Ye; Leye Wang; Yang Yang 074; Yuan Jiang 001; De-Chuan Zhan (UniReps, 2023)

Deep Class-Incremental Learning: A Survey. - Da-Wei Zhou 001; Qi-Wei Wang; Zhi-Hong Qi; Han-Jia Ye; De-Chuan Zhan; Ziwei Liu 002 (CoRR, 2023)

Revisiting Class-Incremental Learning with Pre-Trained Models: Generalizability and Adaptivity are All You Need. - Da-Wei Zhou 001; Han-Jia Ye; De-Chuan Zhan; Ziwei Liu 002 (CoRR, 2023)

Gen-L-Video: Multi-Text to Long Video Generation via Temporal Co-Denoising. - Fu-Yun Wang; Wenshuo Chen; Guanglu Song; Han-Jia Ye; Yu Liu 015; Hongsheng Li 001 (CoRR, 2023)

Learning without Forgetting for Vision-Language Models. - Da-Wei Zhou 001; Yuanhan Zhang; Jingyi Ning; Han-Jia Ye; De-Chuan Zhan; Ziwei Liu 002 (CoRR, 2023)

Streaming CTR Prediction: Rethinking Recommendation Task for Real-World Streaming Data. - Qi-Wei Wang; Hongyu Lu; Yu Chen; Da-Wei Zhou 001; De-Chuan Zhan; Ming Chen; Han-Jia Ye (CoRR, 2023)

ZhiJian: A Unifying and Rapidly Deployable Toolbox for Pre-trained Model Reuse. - Yi-Kai Zhang; Lu Ren; Chao Yi; Qi-Wei Wang; De-Chuan Zhan; Han-Jia Ye (CoRR, 2023)

Unlocking the Transferability of Tokens in Deep Models for Tabular Data. - Qi-Le Zhou; Han-Jia Ye; Leye Wang; De-Chuan Zhan (CoRR, 2023)

Training-Free Generalization on Heterogeneous Tabular Data via Meta-Representation. - Han-Jia Ye; Qi-Le Zhou; De-Chuan Zhan (CoRR, 2023)

Learning Robust Precipitation Forecaster by Temporal Frame Interpolation. - Lu Han; Xu-Yang Chen; Han-Jia Ye; De-Chuan Zhan (CoRR, 2023)

Generalized Knowledge Distillation via Relationship Matching. - Han-Jia Ye; Su Lu; De-Chuan Zhan (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Revisiting Unsupervised Meta-Learning via the Characteristics of Few-Shot Tasks. - Han-Jia Ye; Lu Han; De-Chuan Zhan (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

PyCIL: a Python toolbox for class-incremental learning. - Da-Wei Zhou 001; Fu-Yun Wang; Han-Jia Ye; De-Chuan Zhan (Sci. China Inf. Sci., 2023)

Few-Shot Class-Incremental Learning by Sampling Multi-Phase Tasks. - Da-Wei Zhou 001; Han-Jia Ye; Liang Ma; Di Xie; Shiliang Pu; De-Chuan Zhan (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Learning Only When It Matters: Cost-Aware Long-Tailed Classification. - Yu-Cheng He; Yao-Xiang Ding 001; Han-Jia Ye; Zhi-Hua Zhou (AAAI, 2024)

Twice Class Bias Correction for Imbalanced Semi-supervised Learning. - Lan Li 001; Bowen Tao; Lu Han; De-Chuan Zhan; Han-Jia Ye (AAAI, 2024)

Expandable Subspace Ensemble for Pre-Trained Model-Based Class-Incremental Learning. - Da-Wei Zhou 001; Hai-Long Sun; Han-Jia Ye; De-Chuan Zhan (CVPR, 2024)

Leveraging Cross-Modal Neighbor Representation for Improved CLIP Classification. - Chao Yi; Lu Ren; De-Chuan Zhan; Han-Jia Ye (CVPR, 2024)

SIN: Selective and Interpretable Normalization for Long-Term Time Series Forecasting. - Lu Han; Han-Jia Ye; De-Chuan Zhan (ICML, 2024)

Tabular Insights, Visual Impacts: Transferring Expertise from Tables to Images. - Jun-Peng Jiang; Han-Jia Ye; Leye Wang; Yang Yang 074; Yuan Jiang 001; De-Chuan Zhan (ICML, 2024)

Enhancing Class-Imbalanced Learning with Pre-Trained Guidance through Class-Conditional Knowledge Distillation. - Lan Li 001; Xin-Chun Li; Han-Jia Ye; De-Chuan Zhan (ICML, 2024)

Multi-layer Rehearsal Feature Augmentation for Class-Incremental Learning. - Bowen Zheng; Da-Wei Zhou 001; Han-Jia Ye; De-Chuan Zhan (ICML, 2024)

Continual Learning with Pre-Trained Models: A Survey. - Da-Wei Zhou 001; Hai-Long Sun; Jingyi Ning; Han-Jia Ye; De-Chuan Zhan (IJCAI, 2024)

SOFTS: Efficient Multivariate Time Series Forecasting with Series-Core Fusion. - Han Lu; Xu-Yang Chen; Han-Jia Ye; De-Chuan Zhan (NeurIPS, 2024)

Bridge the Modality and Capability Gaps in Vision-Language Model Selection. - Chao Yi; Yuhang He; De-Chuan Zhan; Han-Jia Ye (NeurIPS, 2024)

Wings: Learning Multimodal LLMs without Text-only Forgetting. - Yi-Kai Zhang; Shiyin Lu; Yang Li; Yanqing Ma; Qingguo Chen; Zhao Xu; Weihua Luo; Kaifu Zhang; De-Chuan Zhan; Han-Jia Ye (NeurIPS, 2024)

Graph Contrastive Learning with Cohesive Subgraph Awareness. - Yucheng Wu 002; Leye Wang; Xiao Han 001; Han-Jia Ye (WWW, 2024)

Bridge the Modality and Capacity Gaps in Vision-Language Model Selection. - Chao Yi; De-Chuan Zhan; Han-Jia Ye (CoRR, 2024)

SOFTS: Efficient Multivariate Time Series Forecasting with Series-Core Fusion. - Lu Han; Xu-Yang Chen; Han-Jia Ye; De-Chuan Zhan (CoRR, 2024)

Ovis: Structural Embedding Alignment for Multimodal Large Language Model. - Shiyin Lu; Yang Li; Qing-Guo Chen; Zhao Xu; Weihua Luo; Kaifu Zhang; Han-Jia Ye (CoRR, 2024)

Parrot: Multilingual Visual Instruction Tuning. - Hai-Long Sun; Da-Wei Zhou 001; Yang Li; Shiyin Lu; Chao Yi; Qing-Guo Chen; Zhao Xu; Weihua Luo; Kaifu Zhang; De-Chuan Zhan; Han-Jia Ye (CoRR, 2024)

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 (CoRR, 2024)

A Closer Look at Deep Learning on Tabular Data. - Han-Jia Ye; Si-Yang Liu; Hao-Run Cai; Qi-Le Zhou; De-Chuan Zhan (CoRR, 2024)

Modern Neighborhood Components Analysis: A Deep Tabular Baseline Two Decades Later. - Han-Jia Ye; Huai-Hong Yin; De-Chuan Zhan (CoRR, 2024)

TALENT: A Tabular Analytics and Learning Toolbox. - Si-Yang Liu; Hao-Run Cai; Qi-Le Zhou; Han-Jia Ye (CoRR, 2024)

OmniEvalKit: A Modular, Lightweight Toolbox for Evaluating Large Language Model and its Omni-Extensions. - Yi-Kai Zhang; Xu-Xiang Zhong; Shiyin Lu; Qing-Guo Chen; De-Chuan Zhan; Han-Jia Ye (CoRR, 2024)

Contextualizing Meta-Learning via Learning to Decompose. - Han-Jia Ye; Da-Wei Zhou 001; Lanqing Hong; Zhenguo Li; Xiu-Shen Wei; De-Chuan Zhan (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

Few-Shot Learning With a Strong Teacher. - Han-Jia Ye; Lu Ming; De-Chuan Zhan; Wei-Lun Chao (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

TV100: a TV series dataset that pre-trained CLIP has not seen. - Da-Wei Zhou 001; Zhi-Hong Qi; Han-Jia Ye; De-Chuan Zhan (Frontiers Comput. Sci., 2024)

The Capacity and Robustness Trade-Off: Revisiting the Channel Independent Strategy for Multivariate Time Series Forecasting. - Lu Han; Han-Jia Ye; De-Chuan Zhan (IEEE Trans. Knowl. Data Eng., 2024)

Class-Incremental Learning: A Survey. - Da-Wei Zhou 001; Qi-Wei Wang; Zhi-Hong Qi; Han-Jia Ye; De-Chuan Zhan; Ziwei Liu 002 (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

MIETT: Multi-Instance Encrypted Traffic Transformer for Encrypted Traffic Classification. - Xu-Yang Chen; Lu Han; De-Chuan Zhan; Han-Jia Ye (AAAI, 2025)

MOS: Model Surgery for Pre-Trained Model-Based Class-Incremental Learning. - Hai-Long Sun; Da-Wei Zhou 001; Hanbin Zhao; Le Gan; De-Chuan Zhan; Han-Jia Ye (AAAI, 2025)

Capability Instruction Tuning. - Yi-Kai Zhang; De-Chuan Zhan; Han-Jia Ye (AAAI, 2025)

Mitigating Visual Forgetting via Take-along Visual Conditioning for Multi-modal Long CoT Reasoning. - Hai-Long Sun; Zhun Sun; Houwen Peng; Han-Jia Ye (ACL (1), 2025)

Dual Consolidation for Pre-Trained Model-Based Domain-Incremental Learning. - Dawei Zhou 001; Zi-Wen Cai; Han-Jia Ye; Lijun Zhang; De-Chuan Zhan (CVPR, 2025)

Task-Agnostic Guided Feature Expansion for Class-Incremental Learning. - Bowen Zheng; Da-Wei Zhou 001; Han-Jia Ye; De-Chuan Zhan (CVPR, 2025)

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 (ICLR, 2025)

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 (ICLR, 2025)

PILOT: a pre-trained model-based continual learning toolbox. - Hai-Long Sun; Da-Wei Zhou 001; De-Chuan Zhan; Han-Jia Ye (Sci. China Inf. Sci., 2025)

Abductive multi-instance multi-label learning for periodontal disease classification with prior domain knowledge. - Zi-Yuan Wu; Wei Guo; Wei Zhou; Han-Jia Ye; Yuan Jiang 001; Houxuan Li; Zhi-Hua Zhou (Medical Image Anal., 2025)

Efficient Sampling-based Gaussian Processes for few-shot semantic segmentation. - Xin-Yi Zhang; Xian-Kai Lu; Yi-Long Yin; Han-Jia Ye; De-Chuan Zhan (Pattern Recognit., 2025)

Revisiting multi-dimensional classification from a dimension-wise perspective. - Yi Shi; Han-Jia Ye; Dongliang Man; Xiaoxu Han; De-Chuan Zhan; Yuan Jiang 001 (Frontiers Comput. Sci., 2025)

TabPFN Unleashed: A Scalable and Effective Solution to Tabular Classification Problems. - Si-Yang Liu; Han-Jia Ye (CoRR, 2025)

Capability Instruction Tuning: A New Paradigm for Dynamic LLM Routing. - Yi-Kai Zhang; De-Chuan Zhan; Han-Jia Ye (CoRR, 2025)

A Closer Look at TabPFN v2: Strength, Limitation, and Extension. - Han-Jia Ye; Si-Yang Liu; Wei-Lun Chao (CoRR, 2025)

Understanding the Limits of Deep Tabular Methods with Temporal Shift. - Hao-Run Cai; Han-Jia Ye (CoRR, 2025)

FedDyMem: Efficient Federated Learning with Dynamic Memory and Memory-Reduce for Unsupervised Image Anomaly Detection. - Silin Chen; Kangjian Di; Yichu Xu; Han-Jia Ye; Wenhan Luo; Ningmu Zou (CoRR, 2025)

SeqFusion: Sequential Fusion of Pre-Trained Models for Zero-Shot Time-Series Forecasting. - Ting-Ji Huang; Xu-Yang Chen; Han-Jia Ye (CoRR, 2025)

External Knowledge Injection for CLIP-Based Class-Incremental Learning. - Da-Wei Zhou 001; Kai-Wen Li; Jingyi Ning; Han-Jia Ye; Lijun Zhang; De-Chuan Zhan (CoRR, 2025)

Model Assembly Learning with Heterogeneous Layer Weight Merging. - Yi-Kai Zhang; Jin Wang; Xu-Xiang Zhong; De-Chuan Zhan; Han-Jia Ye (CoRR, 2025)

Revisiting Class-Incremental Learning with Pre-Trained Models: Generalizability and Adaptivity are All You Need. - Da-Wei Zhou 001; Zi-Wen Cai; Han-Jia Ye; De-Chuan Zhan; Ziwei Liu 002 (Int. J. Comput. Vis., 2025)

Adaptive adapter routing for long-tailed class-incremental learning. - Zhi-Hong Qi; Da-Wei Zhou 001; Yiran Yao; Han-Jia Ye; De-Chuan Zhan (Mach. Learn., 2025)

Efficient Evaluation of Large Language Models via Collaborative Filtering. - Xu-Xiang Zhong; Chao Yi; Han-Jia Ye (CoRR, 2025)

Representation Learning for Tabular Data: A Comprehensive Survey. - Jun-Peng Jiang; Si-Yang Liu; Hao-Run Cai; Qi-Le Zhou; Han-Jia Ye (CoRR, 2025)

Make Still Further Progress: Chain of Thoughts for Tabular Data Leaderboard. - Si-Yang Liu; Qile Zhou; Han-Jia Ye (CoRR, 2025)

Generalized Conditional Similarity Learning via Semantic Matching. - Yi Shi; Rui-Xiang Li; Le Gan; De-Chuan Zhan; Han-Jia Ye (IEEE Trans. Pattern Anal. Mach. Intell., 2025)

Multimodal Tabular Reasoning with Privileged Structured Information. - Jun-Peng Jiang; Yu Xia; Hai-Long Sun; Shiyin Lu; Qing-Guo Chen; Weihua Luo; Kaifu Zhang; De-Chuan Zhan; Han-Jia Ye (CoRR, 2025)

UniCA: Adapting Time Series Foundation Model to General Covariate-Aware Forecasting. - Lu Han; Yu Liu 015; Qiwen Deng; Jian Jiang; Yinbo Sun; Zhe Yu; Binfeng Wang; Xingyu Lu; Lintao Ma; Han-Jia Ye; De-Chuan Zhan (CoRR, 2025)

Learning Without Forgetting for Vision-Language Models. - Da-Wei Zhou 001; Yuanhan Zhang; Yan Wang; Jingyi Ning; Han-Jia Ye; De-Chuan Zhan; Ziwei Liu 002 (IEEE Trans. Pattern Anal. Mach. Intell., 2025)

Addressing Imbalanced Domain-Incremental Learning through Dual-Balance Collaborative Experts. - Lan Li 001; Da-Wei Zhou 001; Han-Jia Ye; De-Chuan Zhan (CoRR, 2025)

Integrating Task-Specific and Universal Adapters for Pre-Trained Model-based Class-Incremental Learning. - Yan Wang; Da-Wei Zhou 001; Han-Jia Ye (CoRR, 2025)