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.

6 papers of 11,817Sort Recent · Most cited
  1. 2025
    FedPTR: Enhancing Federated Prompt Learning with Server-Side Retraining for Non-IID DataYufeng Chen, Min Liu, Sheng Sun, Zhongcheng LiIEEE International Joint Conference on Neural Network
  2. 2025PDF ↗
  3. 2025
    Multi-Stage LLM Fine-Tuning with a Continual Learning SettingChanghao Guan, Chao Huang, Hongliang Li … Jian LiuNAACL
  4. 2025
    CCKA: Continual Cross-Domain Knowledge Adaptation for Multi-Domain Machine TranslationZhibo Man, Yu-Jie Zhang, Yuan-Meng Chen … Jinan XuIEEE TASLP
  5. 2024
  6. 2024
    ICL: Iterative Continual Learning for Multi-domain Neural Machine TranslationZhibo Man, Kaiyu Huang, Yu-Jie Zhang … Jinan XuEMNLP
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.