Related work

The foundational work on continual learning, 1991 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

15 papers of 4,574Sort Recent · Most cited
  1. 2025
    Rethinking Class-Incremental Learning from a Dynamic Imbalanced Learning PerspectiveLeyuan Wang, Liuyu Xiang, Yunlong Wang … Zhaofeng HeIEEE Trans. Multimedia · Beijing University of Posts and Telecommunications · Chinese Academy of Sciences · +2
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  2. 2025
    Adversarial Robust Memory-Based Continual LearnerXiaoyue Mi, Fan Tang, Zonghan Yang … Yang LiuICCV · Chinese Academy of Sciences · Institute of Computing Technology · +1
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  3. 2025
    Progressive Homeostatic and Plastic Prompt Tuning for Audio-Visual Multi-Task Incremental LearningJiong Yin, Li Li, Jiehua Zhang … Xichun ShengICCV · Hangzhou Dianzi University · Chinese Academy of Sciences · +3
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  4. 2025
    Federated Class-Incremental Learning with New-Class Augmented Self-DistillationZhiyuan Wu, Tianliu He, Sheng Sun … Xuefeng JiangJournal of Computer Science and Technology · Chinese Academy of Sciences · Institute of Computing Technology · +2
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  5. 2025
    CD^2: Constrained Dataset Distillation for Few-Shot Class-Incremental LearningKexin Bao, Daichi Zhang, Hansong Zhang … Shiming GeIJCAI · Chinese Academy of Sciences · Institute of Information Engineering · +1
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  6. 2025
    Synthetic Data is an Elegant GIFT for Continual Vision-Language ModelsWu Bin, Wuxuan Shi, Jinqiao Wang, Mang YeCVPR · Wuhan University · Chinese Academy of Sciences · +1
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  7. 2025
    Multi-Granularity Class Prototype Topology Distillation for Class-Incremental Source-Free Unsupervised Domain AdaptationPeihua Deng, Jiehua Zhang, Xichun Sheng … L. LiCVPR · Hangzhou Dianzi University · Xi'an Jiaotong University · +4
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  8. 2025
    PASS++: A Dual Bias Reduction Framework for Non-Exemplar Class-Incremental LearningFei Zhu, Xu-Yao Zhang, Zhen Cheng, Cheng‐Lin LiuTPAMI · Chinese University of Hong Kong, Shenzhen · Chinese Academy of Sciences · +1
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  9. 2025
    Low-redundancy distillation for continual learningRuiqi Liu, Boyu Diao, Libo Huang … Yongjun XuPattern Recognition · Chinese Academy of Sciences · Institute of Computing Technology · +1
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  10. 2025
    Pseudo Informative Episode Construction for Few-Shot Class-Incremental LearningChaofan Chen, Xiaoshan Yang, Changsheng XuAAAI · Chinese Academy of Sciences · Beijing Academy of Artificial Intelligence · +1
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  11. 2025
    Dynamic Object Queries for Transformer-based Incremental Object DetectionJichuan Zhang, Wei Li, Shuang Cheng … Shengjin WangICASSP · Tsinghua University · Chinese Academy of Sciences
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  12. 2025
    IOR: Inversed Objects Replay for Incremental Object DetectionZijia An, Boyu Diao, Libo Huang … Yongjun XuICASSP · Chinese Academy of Sciences · Institute of Computing Technology
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  13. 2025
    Prompt Customization for Continual LearningYong Dai, Xiaopeng Hong, Yabin Wang … Yaowei WangIEEE TAI · Shenzhen Polytechnic University · Peng Cheng Laboratory · +6
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  14. 2025
    MuseumMaker: Continual Style Customization Without Catastrophic ForgettingChanglan Liu, Gan Sun, Wenqi Liang … Yang CongTIP · Shenyang Institute of Automation · Chinese Academy of Sciences · +3
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  15. 2025
    Similarity-based context aware continual learning for spiking neural networksBing Han, Feifei Zhao, Yang Li … Yi ZengNeural Networks · Center for Excellence in Brain Science and Intelligence Technology · Beijing Academy of Artificial Intelligence · +3
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About this index

We keep this list because we read the field and wanted one place to see it. It covers work on continual learning itself, in the core areas of machine learning, and leaves out papers that apply it inside another field, such as medical imaging or fault diagnosis. It lists only papers we have a reason to trust: published at a venue like NeurIPS, ICML, ICLR, CVPR or TPAMI, or led by someone who has published there, or cited a few hundred times, and only papers with a PDF we can point you at, so every title opens the paper itself. Preprints that later get accepted, and authors who later publish at those venues, are picked up by the weekly run. It is seeded from the community lists kept by ContinualAI and by Xialei Liu, then filled out from OpenAlex, and every week a script looks for new papers on OpenAlex and arXiv. A model reads each candidate and decides whether it belongs; a person reviews the additions before they go live. Authors and affiliations come from OpenAlex, so a recent preprint can lack its institutions for a week or two.

Missing something, or filed under the wrong venue? Write to hello@unify.ai with the arXiv id or DOI.