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.

7 papers of 6,984Sort Recent · Most cited
  1. 2025
    Task-Agnostic Guided Feature Expansion for Class-Incremental LearningBowen Zheng, Da-Wei Zhou, Han-Jia Ye, De‐Chuan ZhanCVPR · Nanjing University
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  2. 2025
    Enhancing Few-Shot Class-Incremental Learning via Training-Free Bi-Level Modality CalibrationYiyang Chen, Tianyu Ding, Lei Wang … Wenbin LiCVPR · Nanjing University · Microsoft (United States) · +1
  3. 2024
    InfLoRA: Interference-Free Low-Rank Adaptation for Continual LearningYan-Shuo Liang, Wu-Jun LiCVPR · Nanjing University
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  4. 2024
    Expandable Subspace Ensemble for Pre-Trained Model-Based Class-Incremental LearningDa-Wei Zhou, Hailong Sun, Han-Jia Ye, De-Chuan ZhanCVPR · Nanjing University
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  5. 2024
    Towards Backward-Compatible Continual Learning of Image CompressionZhihao Duan, Ming Lu, Justin Yang … Fengqing ZhuCVPR · Purdue University West Lafayette · Nanjing University
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  6. 2023
    Adaptive Plasticity Improvement for Continual LearningYan-Shuo Liang, Wu-Jun LiCVPR · Nanjing University
  7. 2022
    Forward Compatible Few-Shot Class-Incremental LearningDa-Wei Zhou, Fuyun Wang, Han-Jia Ye … De‐Chuan ZhanCVPR · Nanjing University
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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.