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.

6 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
    Resistive Memory based Efficient Machine Unlearning and Continual LearningNing Lin, Jichang Yang, Yangu He … Zhongrui WangarXiv
  3. 2024
    Self-Distillation Bridges Distribution Gap in Language Model Fine-TuningZhaorui Yang, Tianyu Pang, Haozhe Feng … Qian LiuACL
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  4. 2022
    Ask Question First for Enhancing Lifelong Language LearningHan Wang, Ruiliu Fu, Xuejun Zhang … Qingwei ZhaoCOLING
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  5. 2022
    Reminding the incremental language model via data-free self-distillationHan Wang, Ruiliu Fu, Chengzhang Li … Qingwei ZhaoApplied Intelligence · Chinese Academy of Sciences · Institute of Acoustics · +1
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  6. 2022
    RVAE-LAMOL: Residual Variational Autoencoder to Enhance Lifelong Language LearningHan Wang, Ruiliu Fu, Xuejun Zhang, Jun ZhouIJCNN · Chinese Academy of Sciences · Institute of Acoustics · +1
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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. By default it shows the papers we have a reason to trust: published at a venue like NeurIPS, ICML, ICLR, CVPR or TPAMI, or written by someone who has published there, or cited a few hundred times. The rest are one click away under “All papers”. 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.