Related work

The foundational work on continual learning, 1989 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

7 papers of 5,456Sort Recent · Most cited
  1. 2026
    Lifelong Learner: Discovering Versatile Neural Solvers for Vehicle Routing ProblemsShaodi Feng, Zhuoyi Lin, Jianan Zhou … Yew-Soon OngIEEE T-ITS · National Yang Ming Chiao Tung University · Agency for Science, Technology and Research · +2
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  2. 2025
    Exemplar Masking for Multimodal Incremental LearningYi-Lun Lee, Chen-Yu Lee, Wei-Chen Chiu, Yi–Hsuan TsaiCVPR · National Yang Ming Chiao Tung University · Google (United States) · +1
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  3. 2024
    Continual Gated Adapter for Bilingual Codec Text-to-SpeechLi-Jen Yang, Jen‐Tzung ChienConference of the Oriental COCOSDA International Committe… · National Yang Ming Chiao Tung University
  4. 2023
    Data Efficient Incremental Learning via Attentive Knowledge ReplayYi-Lun Lee, Dian-Shan Chen, Chen-Yu Lee … Wei-Chen ChiuIEEE International Conference on Systems, Man, and Cybern… · National Yang Ming Chiao Tung University · Google (United States)
  5. 2023
    Continually-Adapted Margin and Multi-Anchor Distillation for Class-Incremental LearningYi‐Hsin Chen, Dian-Shan Chen, Ying-Chieh Weng … Wei-Chen ChiuIEEE International Conference on Systems, Man, and Cybern… · National Yang Ming Chiao Tung University
  6. 2023
    Mitigating Forgetting in Continual Learning via Contrasting Semantically Distinct AugmentationsSheng–Feng Yu, Wei-Chen ChiuIEEE International Conference on Systems, Man, and Cybern… · National Yang Ming Chiao Tung University
  7. 2021
    Few-Shot and Continual Learning with Attentive Independent MechanismsEugene Lee, Cheng‐Han Huang, Chen‐Yi LeeICCV · National Yang Ming Chiao Tung 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 written 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.