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.

20 papers of 11,817Sort Recent · Most cited
  1. 2026PDF ↗
  2. 2026
    LLM QLoRA Fine-Tuning of Llama, DeepSeek, and Qwen: A Skyrim Case StudyM. E. Monteiro, Marcos Talau, H. LopesIEEE Access
  3. 2026
    Enhancing Random Forest Using Genetic Algorithm for Lifelong Machine LearningTahira Salwa Rabbi Nishat, Shaibal Barua, M. Ahmed, S. BegumIEEE Access
  4. 2026
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    A Data Stream Approach to Predicting Risk: An Incremental Learning ModelDonghui Shi, Ji-Fei Cheng, Ya-Kun Sun … W. KarwowskiIEEE Access
  6. 2026
    Continual Test-Time Adaptation via Low-Frequency ModulationBoyuan Zhang, Jie Pan, Shuai Yang, Lichuan GuIEEE Access
  7. 2026
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    Learning Discriminative Prompts for Continual Image RestorationPeijun Zhao, Tongjun Wang, Wei Wang … Songnan ChenIEEE Access
  14. 2026
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  19. 2026
    TILES: Transformer-Based Incremental Learning for Expanding SegmenterHejer Ammar, Saad Lahlali, Romaric AudigierIEEE Access
  20. 2026
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.