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.

248 papers of 11,817 · showing 101–150Sort Recent · Most cited
  1. 2025
  2. 2025
  3. 2025
  4. 2025PDF ↗
  5. 2025PDF ↗
  6. 2025PDF ↗
  7. 2025PDF ↗
  8. 2025PDF ↗
  9. 2025PDF ↗
  10. 2026
    Expert Routing with Synthetic Data for Continual LearningYewon Byun, Sanket Vaibhav Mehta, Saurabh Garg … Z. LiptonICML
    PDF ↗
  11. 2024
  12. 2024PDF ↗
  13. 2024
  14. 2024
  15. 2024
  16. 2024
    Adjusting Model Size in Continual Gaussian Processes: How Big is Big Enough?Guiomar Pescador-Barrios, Sarah Filippi, Mark van der WilkICML
    PDF ↗
  17. 2024
    An Effective Dynamic Gradient Calibration Method for Continual LearningWeichen Lin, Jiaxiang Chen, Ru Huang, Huihua DingICML
    PDF ↗
  18. 2024
    COALA: A Practical and Vision-Centric Federated Learning PlatformWeiming Zhuang, Jian Xu, Chen Chen … Lingjuan LyuICML
    PDF ↗
  19. 2024
    An Attention-based Representation Distillation Baseline for Multi-Label Continual LearningMartin Menabue, Emanuele Frascaroli, Matteo Boschini … Simone CalderaraICML
    PDF ↗
  20. 2024PDF ↗
  21. 2024PDF ↗
  22. 2024
    A Statistical Theory of Regularization-Based Continual LearningXu-Yang Zhao, Huiyuan Wang, Weiran Huang, Wei LinICML
    PDF ↗
  23. 2024
    Harnessing Neural Unit Dynamics for Effective and Scalable Class-Incremental LearningDe-Peng Li, Tianqi Wang, Junwei Chen … Zhigang ZengICML
    PDF ↗
  24. 2024
    Conditional Language Learning with ContextXiao Zhang, Miao Li, Ji WuICML
    PDF ↗
  25. 2024
    Provable Contrastive Continual LearningYi-Fei Wen, Zhiquan Tan, Kaipeng Zheng … Weiran HuangICML
    PDF ↗
  26. 2024
    Learning to Continually Learn with the Bayesian PrincipleSoochan Lee, Hyeonseong Jeon, Jaehyeon Son, Gunhee KimICML
    PDF ↗
  27. 2024
    Compositional Few-Shot Class-Incremental LearningYixiong Zou, Shang-Hang Zhang, Haichen Zhou … Ruixuan LiICML
    PDF ↗
  28. 2024PDF ↗
  29. 2024
    FreeBind: Free Lunch in Unified Multimodal Space via Knowledge FusionZehan Wang, Ziang Zhang, Xize Cheng … Zhou ZhaoICML
    PDF ↗
  30. 2024
    Kullback-Leibler Reservoir Sampling for Fairness in Continual LearningSotirios Nikoloutsopoulos, I. Koutsopoulos, Michalis K. TitsiasICML
  31. 2024
    Position: Lifetime tuning is incompatible with continual reinforcement learningGolnaz Mesbahi, P. Panahi, Olya Mastikhina … Adam WhiteICML
    PDF ↗
  32. 2024
    Improving Continual Learning Performance and Efficiency with Auxiliary ClassifiersFilip Szatkowski, Yaoyue Zheng, Fei Yang … Joost van de WeijerICML
    PDF ↗
  33. 2024PDF ↗
  34. 2024
    Towards Robust Graph Incremental Learning on Evolving GraphsJunwei Su, Difan Zou, Zijun Zhang, Chuan WuICML
    PDF ↗
  35. 2024PDF ↗
  36. 2024PDF ↗
  37. 2024
    Where is the Truth? The Risk of Getting Confounded in a Continual WorldFlorian Peter Busch, Roshni Kamath, Rupert Mitchell … Martin MundtICML
    PDF ↗
  38. 2024PDF ↗
  39. 2024PDF ↗
  40. 2024
    Continual Few-Shot Relation Learning Via Dynamic Margin Loss and Space RecallYongbing Li, Peng-Fei Duan, Yi Rong … Aoxing WangICML
  41. 2024
    Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AITheodore Papamarkou, Maria Skoularidou, Konstantina Palla … Ruqi ZhangICML
    PDF ↗
  42. 2024
    Neighboring Perturbations of Knowledge Editing on Large Language ModelsJun-Yu Ma, Jia-Chen Gu, Ningyu Zhang, Zhen-Hua LingICML
    PDF ↗
  43. 2024
    Multi-layer Rehearsal Feature Augmentation for Class-Incremental LearningBowen Zheng, Da-Wei Zhou, Han-Jia Ye, De-Chuan ZhanICML
  44. 2024
    Federated Continual Learning via Prompt-based Dual Knowledge TransferHongming Piao, Yichen Wu, Dapeng Wu, Ying WeiICML
  45. 2024
  46. 2024
  47. 2024
  48. 2024
    Rapid Learning without Catastrophic Forgetting in the Morris Water MazeRaymond Wang, Jaedong Hwang, Akhilan Boopathy, I. FieteICML
  49. 2024
  50. 2024PDF ↗
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.