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.

9 papers of 11,817Sort Recent · Most cited
  1. 2026
    Random Dense Knowledge Distillation for Continual LearningJie Chu, Pei Liu, Tongzhenzhi Su … Zenglin ShiACM Trans. Multim. Comput. Commun. Appl.
  2. 2026
    Text-Prompted Prompt Generator with Uncertainty Regularization for Rehearsal-Free Class-Incremental LearningShaofan Wang, Fuhao Wei, Hong Ma … Baocai YinACM Trans. Multim. Comput. Commun. Appl.
  3. 2025
    THMM-CLIP: Task-Guided Hierarchical Multi-Modal Alignment for Rehearsal-Free Class Incremental LearningYuankang Pan, Zhaoquan Yuan, Xiao Wu … Changsheng XuACM Trans. Multim. Comput. Commun. Appl.
  4. 2025
    Gleaning Wisdom from the Past: Towards Label Incremental Learning for Online Hashing with a Plug-and-Play FrameworkChong-Yu Zhang, Xin Luo, Yu-Wei Zhan … Xin-Shun XuACM Trans. Multim. Comput. Commun. Appl.
  5. 2025
    Visuo-Tactile Class-Incremental LearningHao Fu, Fengyu Yang, Boyang Wang … Hui QianACM Trans. Multim. Comput. Commun. Appl.
  6. 2024
    Multi-scale Consistency Deep Lifelong Cross-modal HashingLiming Xu, Hanqi Li, Jie Shao … Weisheng LiACM Trans. Multim. Comput. Commun. Appl.
  7. 2024
    Progressive Adapting and Pruning: Domain-Incremental Learning for Saliency PredictionKaihui Yang, Junwei Han, Guangyu Guo … Dingwen ZhangACM Trans. Multim. Comput. Commun. Appl.
  8. 2024
    Backdoor Two-Stream Video Models on Federated LearningJing Zhao, Hongwei Yang, Hui He … Aniello CastiglioneACM Trans. Multim. Comput. Commun. Appl.
  9. 2023
    Distilled Meta-learning for Multi-Class Incremental LearningHao Liu, Zhaoyu Yan, Bing Liu … Abdulmotaleb El SaddikACM Trans. Multim. Comput. Commun. Appl.
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.