Related work

The foundational work on continual learning, 1988 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

4 papers of 6,984Sort Recent · Most cited
  1. 2026
    Crafting Your Evolving Dreams: Concept-Incremental Versatile CustomizationJiahua Dong, Wenqi Liang, Hongliu Li … Fahad Shahbaz KhanTPAMI · Mohamed bin Zayed University of Artificial Intelligence · University of Trento · +5
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  2. 2026
    Learning From Each Other: Generalized Federated Incremental Semantic SegmentationJiahua Dong, Wenqi Liang, Yang Cong … Luc Van GoolTPAMI · Mohamed bin Zayed University of Artificial Intelligence · Shenyang Institute of Automation · +5
  3. 2026
    IAP: Improving Continual Learning of Vision-Language Models via Instance-Aware PromptingHao Fu, Hanbin Zhao, Jiahua Dong … Hui QianTIP · Zhejiang University of Science and Technology · Mohamed bin Zayed University of Artificial Intelligence · +1
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  4. 2026
    CRISP: Contrastive Residual Injection and Semantic Prompting for Continual Video Instance SegmentationBaichen Liu, Qi Lyu, Xudong Wang … Zhi HanTIP · Shenyang Institute of Automation · Mohamed bin Zayed University of Artificial Intelligence
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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 led 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.