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.

4 papers of 8,653Sort Recent · Most cited
  1. 2026
    R-Tuning: Wavelet-Decomposed Replay and Semantic Alignment for Continual Adaptation of Pretrained Time-Series ModelsTianyi Yin, Jingwei Wang, Chenze Wang … Weiming ShenAAAI · Tongji University · Moscow State University of Printing Arts · +2
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  2. 2026
    Random Amalgamation of Adapters for Flatter Loss Landscapes: Towards Class-Incremental Learning with Better StabilityYao Deng, Xiang Xiang, Jiaqi GuiAAAI · Huazhong University of Science and Technology
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  3. 2025
    Adaptive Prototype Replay for Class Incremental Semantic SegmentationGuilin Zhu, Dongyue Wu, Changxin Gao … Nong SangAAAI · Huazhong University of Science and Technology · Hunan Normal University
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  4. 2023
    Non-exemplar Online Class-Incremental Continual Learning via Dual-Prototype Self-Augment and RefinementFushuo Huo, Wenchao Xu, Jingcai Guo … Yunfeng FanAAAI · Hong Kong Polytechnic University · Huazhong University of Science and 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 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.