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.

5 papers of 8,653Sort Recent · Most cited
  1. 2026
    From Offline to Online Memory-Free and Task-Free Continual Learning via Fine-Grained HypergradientsNicolas Michel, Maorong Wang, Jiangpeng He, Toshihiko YamasakiTMLR
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  2. 2024
    Reward Incremental Learning in Text-to-Image GenerationMaorong Wang, Jiafeng Mao, Xueting Wang, Toshihiko YamasakiarXiv
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  3. 2024
    Dealing with Synthetic Data Contamination in Online Continual LearningMaorong Wang, Nicolas Michel, Jiafeng Mao, Toshihiko YamasakiNeurIPS
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  4. 2024
    Improving Plasticity in Online Continual Learning via Collaborative LearningMaorong Wang, Nicolas Michel, Ling Xiao, Toshihiko YamasakiCVPR · The University of Tokyo · Université Gustave Eiffel
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  5. 2024
    Rethinking Momentum Knowledge Distillation in Online Continual LearningNicolas Michel, Maorong Wang, Ling Xiao, Toshihiko YamasakiICML
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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.