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.

6 papers of 8,653Sort Recent · Most cited
  1. 2026
    Estimating Representation Drift for Prompt-Based Class-Incremental LearningYuting Hou, Rongyu Zhu, Junjie Liu, Kedian MuSpringer LNCS · Peking University
  2. 2026
    FS-LoRA: Fast and Slow Low-Rank Adaptation for Class Incremental LearningY Hou, Xuefei Tong, Kedian MuICASSP · Peking University
  3. 2024
    Prompting to Prompt for Rehearsal-Free Class Incremental LearningGuangzhi Zhao, Yuting Hou, Kedian MuICASSP · Peking University
  4. 2026
    AdaHAT: Adaptive Hard Attention to the Task in Task-Incremental LearningPengxiang Wang, Hongbo Bo, Jun Hong … Kedian MuSpringer LNCS · Peking University · University of Bristol · +2
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  5. 2023
    Mutually Promoted Hierarchical Learning for Incremental Implicitly-Refined ClassificationGuangzhi Zhao, Yuting Hou, Kedian MuIJCNN · Peking University
  6. 2023
    Connection-Based Knowledge Transfer for Class Incremental LearningGuangzhi Zhao, Kedian MuIJCNN · Peking University
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.