Adaptive Deep Models for Incremental Learning: Considering Capacity Scalability and Sustainability. - Yang Yang 074; Da-Wei Zhou 001; De-Chuan Zhan; Hui Xiong 001; Yuan Jiang 001 (KDD, 2019)

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

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

Detecting Sequentially Novel Classes with Stable Generalization Ability. - Da-Wei Zhou 001; Yang Yang 074; De-Chuan Zhan (PAKDD (1), 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)

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)

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)

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)

Learning to Classify With Incremental New Class. - Da-Wei Zhou 001; Yang Yang 074; De-Chuan Zhan (IEEE Trans. Neural Networks Learn. Syst., 2022)

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)

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)

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

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)

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)

RF-Badge: Vital Sign-Based Authentication via RFID Tag Array on Badges. - Jingyi Ning; Lei Xie 004; Chuyu Wang; Yanling Bu; Fengyuan Xu; Da-Wei Zhou 001; Sanglu Lu; Baoliu Ye (IEEE Trans. Mob. Comput., 2023)

Cost-Effective Incremental Deep Model: Matching Model Capacity With the Least Sampling. - Yang Yang 074; Da-Wei Zhou 001; De-Chuan Zhan; Hui Xiong 001; Yuan Jiang 001; Jian Yang 003 (IEEE Trans. Knowl. Data Eng., 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)

Graph of Logic: Enhancing LLM Reasoning with Graphs and Symbolic Logic. - Fatimah Alotaibi; Adithya Kulkarni; Dawei Zhou 001 (IEEE Big Data, 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)

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)

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)

LW2G: Learning Whether to Grow for Prompt-based Continual Learning. - Qian Feng; Dawei Zhou 001; Hanbin Zhao; Chao Zhang 001; Hui Qian 001 (CoRR, 2024)

Rethinking the Uncertainty: A Critical Review and Analysis in the Era of Large Language Models. - Mohammad Beigi; Sijia Wang; Ying Shen 006; Zihao Lin 003; Adithya Kulkarni; Jianfeng He; Feng Chen 001; Ming Jin 002; Jin-Hee Cho; Dawei Zhou 001; Chang-Tien Lu; Lifu Huang (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)

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)

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)

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)

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)

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)

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)

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)

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)

DISPROTBENCH: A Disorder-Aware, Task-Rich Benchmark for Evaluating Protein Structure Prediction in Realistic Biological Contexts. - Xinyue Zeng; Tuo Wang; Adithya Kulkarni; Alexander Lu; Alexandra Ni; Phoebe Xing; Junhan Zhao; Siwei Chen; Dawei Zhou 001 (CoRR, 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)