Related work

The foundational work on continual learning, 1980 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

41 papers of 8,653Sort Recent · Most cited
  1. 2026PDF ↗
  2. 2026
    LCA: Local Classifier Alignment for Continual LearningTung Anh Tran, Danilo Vasconcellos Vargas, Khoat ThanICLR
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  4. 2026
    IDER: IDempotent Experience Replay for Reliable Continual LearningZhanwang Liu, Yuting Li, Haoyuan Gao … Weiran HuangICLR
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    Revisiting Weight Regularization for Low-Rank Continual LearningYaoyue Zheng, Yin Zhang, Joost van de Weijer … Zhiqiang TianICLR
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    KeepLoRA: Continual Learning with Residual Gradient AdaptationMao-Lin Luo, Zihao Zhou, Yi-Lin Zhang … Min-Ling ZhangICLR
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    MERGETUNE: Continued fine-tuning of vision-language modelsWenqing Wang, Da Li, Xiatian Zhu, Josef KittlerICLR
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  31. 2026
    Heads collapse, features stay: Why Replay needs big buffersLanzillotta, Giulia, Meier, Damiano, Hofmann, ThomasICLR
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  37. 2026
    Rethinking Continual Learning with Progressive Neural CollapseZheng Wang, Wenhua Yu, Yang Li, Sen LinICLR
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  40. 2026
    Sculpting Subspaces: Constrained Full Fine-Tuning in LLMs for Continual LearningN. Nayak, Krishnateja Killamsetty, Ligong Han … Akash SrivastavaICLR
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  41. 2026
    Enhanced Continual Learning of Vision-Language Models with Model FusionHaoyuan Gao, Zicong Zhang, Wei, Yuqi … Weiran HuangICLR
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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 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.