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.

16 papers of 11,817Sort Recent · Most cited
  1. 2026
    Pattern in Motion: Retrieval-Augmented Learning for Dynamic Spatio-Temporal Graphs.Haoyu Zhang, Xinke Jiang, Wentao Zhang … Heqing HuangTPAMI
  2. 2026
  3. 2026
  4. 2026
    Continual Low-Rank Adaptation Via Cumulative Unified Optimization.Yue Lu, Shizhou Zhang, De Cheng … Yanning ZhangTPAMI
  5. 2026
    AdaptCMVC++: Robust and Flexible Adaptation to Incremental Views in Continual Multi-view Clustering.Jing Wang, Songhe Feng, Jiacheng Li … Michael C. KampffmeyerTPAMI
  6. 2026
  7. 2026
    LoRASculpt: Harmonious Low-Rank Adaptation for Multimodal Large Language ModelsJian Liang, Wenke Huang, Xian-Da Guo … Mang YeTPAMI
  8. 2026
    Crafting Your Evolving Dreams: Concept-Incremental Versatile CustomizationJia-Hua Dong, Wen-Qi Liang, Hong-Liu Li … F. KhanTPAMI
    PDF ↗
  9. 2026
  10. 2026
    Continual Test-Time Training on Graphs via Adaptive Prompts IntegrationQianyi Cai, Ziyue Qiao, Rui Cai … Hui XiongTPAMI
  11. 2026
    NExplore: Exploration with Neural Fields for Autonomous Scene Reconstruction.Zike Yan, Zijian Kuang, Yuetao Li … Hongbin ZhaTPAMI
  12. 2026
  13. 2026
    Locally Linear Continual Learning for Time Series Based on VC-Theoretical Generalization BoundsYan V. G. Ferreira, I. Lima, S. PedroH.G.Mapa … A. P. BragaTPAMI
    PDF ↗
  14. 2026
    Learning From Each Other: Generalized Federated Incremental Semantic SegmentationJiahua Dong, Wen-Qi Liang, Yang Cong … L. van GoolTPAMI
  15. 2026
    CAKGE: Context-Aware Adaptive Learning for Dynamic Knowledge Graph EmbeddingsZong-Sheng Cao, Qianqian Xu, Zhiyong Yang … Qing-Ming HuangTPAMI
  16. 2026
    Human Motion Prediction via Continual Prior CompensationJianwei Tang, Jian-Fang Hu, Tianming Liang … Jian-Huang LaiTPAMI
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.