Related work

The foundational work on continual learning, 1988 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

129 papers of 6,984 · showing 1–50Sort Recent · Most cited
  1. 2026
  2. 2025
  3. 2024
  4. 2024
  5. 2024
  6. 2023
    Enhancing Continual Learning with Global Prototypes: Counteracting Negative Representation DriftXueying Bai, Jinghuan Shang, Yifan Sun, Niranjan BalasubramanianPreprint
  7. 2023
  8. 2023
  9. 2023
  10. 2023
  11. 2023
    Supplementary Material for Dense Network Expansion for Class Incremental LearningZhiyuan Hu, Yunsheng Li, J. Lyu … N. VasconcelosPreprint
  12. 2023
  13. 2023
  14. 2023
  15. 2022
    Federated Continual Learning with Differentially Private Data SharingGiulio Zizzo, Ambrish Rawat, N. Holohan, Seshu TirupathiPreprint
  16. 2022
    Speeding-up Continual Learning through Information Gains in Novel ExperiencesPierrick Lorang, Shivam Goel, Patrik Zips … matthias. scheutzPreprint
  17. 2022
    Deep Learning for Class-Incremental Learning: A surveyDa-Wei Zhou, Fu Lee Wang, Han-Jia Ye, De-chuan ZhanPreprint
  18. 2022
  19. 2022
    Continual Learning for Time-to-Event ModelingManisha Dubey, P. K. Srijith, M. DesarkarPreprint
  20. 2022
  21. 2022
    Can Sequential Bayesian Inference Solve Continual Learning?Samuel Kessler, Adam D. Cobb, S. Zohren, Stephen J. RobertsPreprint
  22. 2022
  23. 2022
    Populating Memory in Continual Learning with Consistency Aware SamplingJ. Hurtado, Alain Raymond-Sáez, Vladimir Araujo … D. BacciuPreprint
  24. 2022
    Supplementary Material: Continual Learning with Lifelong Vision TransformerZhen Wang, Liu Liu, Yiqun Duan … Dacheng TaoPreprint
  25. 2022
  26. 2022
    CL-LSG: Continual Learning via Learnable Sparse GrowthLi Yang, Sen Lin, Junshan Zhang, Deliang FanPreprint
  27. 2022
    Class-Incremental Learning with Strong Pre-trained Models Supplemental MaterialTz-Ying Wu, Gurumurthy Swaminathan, Zhizhong Li … S. SoattoPreprint
  28. 2022
  29. 2022
    Continual Learning for Scene Analysis in Open WorldRomaric Audigier, Hejer AmmarPreprint
  30. 2022
  31. 2022
  32. 2022
    Elastic Weight Consolidation for Reduction of Catastrophic Forgetting in GPT-2Rishi Bommasani, Drew A. Hudson, Ehsan Adeli … D. LuanPreprint
  33. 2022
  34. 2022
    Supplementary material for ”FeTrIL: Feature Translation for Exemplar-Free Class-Incremental Learning”Grégoire Petit, Adrian-Ştefan Popescu, Hugo Schindler … Bertrand DelezoidePreprint
  35. 2022
  36. 2022
    Supplementary: CAM-GAN: Continual Adaptation Modules for Generative Adversarial NetworksSakshi Varshney, V. Verma, P. K. Srijith … Piyush RaiPreprint
  37. 2021
    Online Continual Learning Under Domain ShiftQ. Pham, Chenghao Liu, S. HoiPreprint
  38. 2021
  39. 2021
  40. 2021
  41. 2021
    Continual Learning with Memory CascadesD. Kappel, F. Negri, Christian TetzlaffPreprint
  42. 2021
  43. 2021
  44. 2021
  45. 2021
  46. 2021
    Lifelong Robot LearningE. Oztop, Emre UgurPreprint
  47. 2021
    MAML-CL: Edited Model-Agnostic Meta-Learning for Continual LearningMarcin Andrychowicz, Misha Denil, Sergio Gómez … Longxiang GaoPreprint
  48. 2021
  49. 2021
  50. 2021
    Supplementary Material: Rectification-based Knowledge Retention for Continual LearningPravendra Singh, Pratik Mazumder, Piyush Rai, Vinay P. NamboodiriPreprint
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 lists only papers we have a reason to trust: published at a venue like NeurIPS, ICML, ICLR, CVPR or TPAMI, or led by someone who has published there, or cited a few hundred times. Preprints that later get accepted, and authors who later publish at those venues, are picked up by the weekly run. 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.