Related work

The foundational work on continual learning, 1988 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

14 papers of 6,984Sort Recent · Most cited
  1. 2025
    MoTiC: Momentum Tightness and Contrast for Few-Shot Class-Incremental LearningZeyu He, Shuai Huang, Yuwu Lu, Ming ZhaoPattern Recognition · Guilin University of Electronic Technology · South China Normal University
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  2. 2025
    Dual-Attention based prompt generation and catalyzing for instance-wise continual learningYong Dai, Xiaopeng Hong, Yabin Wang … Yaowei WangPattern Recognition · Shenzhen Polytechnic University · Peng Cheng Laboratory · +5
  3. 2025
    Class-aware prototype augmentation and decoupled feature distillation for class-incremental learningChengdong Wang, Yangjun Ou, Xianfang Tang … Rui YanPattern Recognition · Hefei University of Technology · Wuhan Textile University · +2
  4. 2025
    Buffer-free Class-Incremental Learning with Out-of-Distribution DetectionSrishti Gupta, Daniele Angioni, Maura Pintor … Battista BiggioPattern Recognition · University of Cagliari · Sapienza University of Rome · +3
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  5. 2025
    You look from old classes: Towards accurate few shot class-incremental learningYijie Hu, Kaizhu Huang, Wei Wang … Qiufeng WangPattern Recognition · University of Liverpool · Xi’an Jiaotong-Liverpool University · +1
  6. 2025
    TIPS: Two-level prompt selection for more stability-plasticity balance in continual learningZhikun Feng, Liang Peng, Kang Dang … Jionglong SuPattern Recognition · University of Electronic Science and Technology of China · Chengdu University of Information Technology · +3
  7. 2025
    GaitAdapt: Continual Learning for Evolving Gait RecognitionJingjie Wang, Shun-Li Zhang, Xiang Wei, Senmao TianPattern Recognition
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  8. 2025
    Slowly expanding neural network for class incremental learningZhengjin Xu, Xuyang Li, Xiaobin Chang … Ruixuan WangPattern Recognition · Sun Yat-sen University · Key Laboratory of Guangdong Province · +2
  9. 2025
    Towards Redundancy-Free Sub-networks in Continual LearningCheng Chen, Lianli Gao, Pengpeng Zeng … Heng Tao ShenPattern Recognition · University of Electronic Science and Technology of China · Tongji University
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  10. 2025
    Online task-free continual learning via Expansible Vision TransformerFei Ye, Adrian G. BorşPattern Recognition · University of Electronic Science and Technology of China · University of York
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  11. 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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  12. 2025
    CIT: Rethinking Class-incremental Semantic Segmentation with a Class Independent TransformationJinchao Ge, Bowen Zhang, Akide Liu … Yang ZhaoPattern Recognition · The University of Adelaide · Monash University · +1
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  13. 2025
    LoRA-Based Continual Learning with Constraints on Critical Parameter ChangesShimou Ling, Liang Zhang, Jiangwei Zhao … Hongliang LiPattern Recognition
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  14. 2025
    FILP-3D: Enhancing 3D few-shot class-incremental learning with pre-trained vision-language modelsWan Xu, Tianyu Huang, Tianyuan Qu … Wangmeng ZuoPattern Recognition · Harbin Institute of Technology
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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. 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.