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.

13 papers of 8,653Sort Recent · Most cited
  1. 2025
    Multi-modality integrated class incremental learning networks for 3D object recognitionYufei Zhang, Dongyun Lin, Xiao Zhang … Huiping ZhuangKnowledge-Based Systems · Nanyang Technological University · Wuyi University · +4
  2. 2025PDF ↗
  3. 2025
    Probabilistic Mixture of Hyperbolic Mamba for Few-Shot Class-Incremental LearningYawen Cui, Wenbin Zou, Huiping Zhuang … Lap‐Pui ChauACM International Conference on Multimedia · Hong Kong Polytechnic University · South China University of Technology
  4. 2025
    Any-SSR: How Recursive Least Squares Works in Continual Learning of Large Language ModelsKai Tong, Kang Pan, Xiao Zhang … Huiping ZhuangICCV · South China University of Technology · Xiaomi (China) · +1
  5. 2025PDF ↗
  6. 2025
    CALM: A Ubiquitous Crowdsourced Analytic Learning Mechanism for Continual Service Construction with Data Privacy PreservationKejia Fan, Yajiang Huang, Jingyu He … Yunhuai LiuACM on Interactive Mobile Wearable and Ubiquitous Technol… · Central South University · University of Pennsylvania · +6
  7. 2025PDF ↗
  8. 2025
    AFCL: Analytic Federated Continual Learning for Spatio-Temporal Invariance of Non-IID DataJianheng Tang, Huiping Zhuang, Jingyu He … Yunhuai LiuarXiv
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  9. 2025
    Towards Efficient and Exact Forgetting Services in Pre-Trained-Model-based Continual LearningYajiang Huang, Jianheng Tang, Di Fang … Houbing Herbert SongarXiv
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  10. 2025PDF ↗
  11. 2025
    ALMM: Analytic Learning and Model Merging for Class Incremental LearningHe Han, Huiping ZhuangWorld Conference on Computing and Communication Technolog… · South China University of Technology
  12. 2025PDF ↗
  13. 2025PDF ↗
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.