Related work

The foundational work on continual learning, 1959 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

8 papers of 11,817Sort Recent · Most cited
  1. 2026
    On-Policy Replay for Continual Supervised Fine-TuningYan Chen, Taojie Zhu, Meng Zhang … Yizhi WangarXiv
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  2. 2026PDF ↗
  3. 2026
    An Efficient Website Fingerprinting for New Websites Emerging Based on Incremental LearningZhengge Yi, Teng-Yao Li, Meng Zhang … Xiangyang LuoIEEE Transactions
  4. 2025
    Gaussian-Augmented Prototypical Network for Class-Incremental Few-Shot Relation ClassificationChenxi Hu, Yi-Fan Hu, Yun-Xiang Zhao … Yang-Yi HuACM Transactions
  5. 2024
    Resource-Efficient Heterogenous Federated Continual Learning on EdgeZhao Yang, Shengbing Zhang, Chuxi Li … Meng ZhangDesign, Automation and Test in Europe
  6. 2024
    Efficient knowledge management for heterogeneous federated continual learning on resource-constrained edge devicesZhao Yang, Shengbing Zhang, Chuxi Li … Meng ZhangFuture generations computer systems
  7. 2021
    Incremental Learning Algorithm Based on Graph Regularized Non-negative Matrix Factorization with Sparseness ConstraintsJintao Wang, Meng Zhang, Xusheng Hu, Tianwei NiInternational Conference on Artificial Intelligence and B… · Anhui University of Technology
  8. 2019
    RBER-Aware Lifetime Prediction Scheme for 3D-TLC NAND Flash MemoryRuixiang Ma, Fei Wu, Meng Zhang … Changsheng XieIEEE Access · Wuhan National Laboratory for Optoelectronics · Huazhong University of Science and Technology · +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.