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.

7 papers of 8,653Sort Recent · Most cited
  1. 2026
    Structure-aware federated hypergraph continual learningYanxin Hu, Xiaoman Liu, Zhenzhen Xie … Chao ChengInformation Sciences · Changchun University of Technology · Shandong University of Science and Technology · +3
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  2. 2026
    KTR: Structure-aware replay for continual learning on hypergraphsYanxin Hu, Zhenzhen Xie, Junjie Pang, Chao ChengKnowledge-Based Systems · Changchun University of Science and Technology · Changchun University · +3
  3. 2025
    FedMTL: Adaptive multi-teacher knowledge distillation for federated continual learningLeiming Chen, Dehai Zhao, Yongbiao Gao … Chee Wei TanKnowledge-Based Systems · Jining University · China University of Petroleum, East China · +5
  4. 2025
    Exploring continual learning in code intelligence with domain-wise distilled promptsShuo Liu, Jacky Keung, Zhen Yang … Yicheng SunInformation and Software Technology · City University of Hong Kong · Beihang University · +1
  5. 2024
    SCARF: Scalable Continual Learning Framework for Memory‐efficient Multiple Neural Radiance FieldsYuze Wang, Junyi Wang, Chen Wang … Yue QiComputer Graphics Forum · Beihang University · Shandong University of Science and Technology · +3
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  6. 2024
    Class Incremental Learning Method Based on Dynamic Structure Extension and Feature enhancementZhenghu Li, Baishun ShiJournal of Computing and Electronic Information Management · Qingdao University of Science and Technology · Qingdao University of Technology · +1
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  7. 2017
    Dual Track Multimodal Automatic Learning through Human-Robot InteractionShuqiang Jiang, Weiqing Min, Xue Li … Jiaqi ZhouIJCAI · Institute of Computing Technology · University of Chinese Academy of Sciences · +1
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.