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.

5 papers of 11,817Sort Recent · Most cited
  1. 2026
    A Curriculum-Guided Multi-Task Learning Fine-Tuning Framework: Enhancing Low-Resource Machine Translation with Large Language ModelsZong-Xu Luo, Wenzhong Yang, Ya-Bo Yin … Junjiang ChenInternational Conference on Computer Supported Cooperativ…
  2. 2026
    A Framework for Addressing Catastrophic Forgetting and Noisy Labeling in Continual LearningZhonghe Wei, Xiaodan Li, Hongsheng Yin … Jihang YinInternational Conference on Computer Supported Cooperativ…
  3. 2026
    CAHGAC: Contrastive-Augmented Heterogeneous Graph-Based Access ControlYu Zhang, Hao-Xiang Huang, Yanjun Qin … Lie-Jun WangInternational Conference on Computer Supported Cooperativ…
  4. 2026
    Federated Unlearning via Sparsity-Aware Gradient AscentLinfen Zhang, Jiayi Zheng, Si-guang ChenInternational Conference on Computer Supported Cooperativ…
  5. 2026
    Incremental Learning for XGBoost via Knowledge ConsolidationT. Ning, Dan Luo, Fang ZhaoInternational Conference on Computer Supported Cooperativ…
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.