Related work

The foundational work on continual learning, 1991 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

168 papers of 4,574 · showing 51–100Sort Recent · Most cited
  1. 2025
    LoRanPAC: Low-rank Random Features and Pre-trained Models for Bridging Theory and Practice in Continual LearningLiangzu Peng, Juan Elenter, Joshua Agterberg … René Víctor Valqui VidalICLR
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  2. 2025PDF ↗
  3. 2025PDF ↗
  4. 2025
    Theory on Mixture-of-Experts in Continual LearningHongbo Li, Sen Lin, Lingjie Duan … Ness B. ShroffICLR
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  5. 2025
    MOS: Model Synergy for Test-Time Adaptation on LiDAR-Based 3D Object DetectionZhuoxiao Chen, Junjie Meng, Mahsa Baktashmotlagh … Yadan LuoICLR
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  6. 2025
    Towards Continuous Reuse of Graph Models via Holistic Memory DiversificationZiyue Qiao, Junren Xiao, Qingqiang Sun … Xiong, HuiICLR
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  7. 2025
    Learning Continually by Spectral RegularizationAlex Lewandowski, Bortkiewicz, Michał, Saurabh Kumar … Marlos C. MachadoICLR
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  8. 2025PDF ↗
  9. 2025
    Perturbation-Restrained Sequential Model EditingJun-Yu Ma, Hong Wang, Hao-Xiang Xu … Jia-Chen GuICLR
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  10. 2025
    A Second-Order Perspective on Model Compositionality and Incremental LearningAngelo Porrello, Lorenzo Bonicelli, Pietro Buzzega … Rita CucchiaraICLR
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  11. 2025
    Adaptive Retention&Correction: Test-Time Training for Continual LearningHao Chen, Micah Goldblum, Zuxuan Wu, Yu–Gang JiangICLR
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  12. 2025PDF ↗
  13. 2024PDF ↗
  14. 2024
    Continual Learning on a Diet: Learning from Sparsely Labeled Streams Under Constrained ComputationWenxuan Zhang, Youssef Mohamed, Bernard Ghanem … Mohamed ElhoseinyICLR
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  15. 2024
    Scalable Language Model with Generalized Continual LearningBohao Peng, Zhuotao Tian, Shu Liu … Jiaya JiaICLR
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  16. 2024PDF ↗
  17. 2024PDF ↗
  18. 2024
    A Unified and General Framework for Continual LearningZhenyi Wang, Yan Li, Li Shen, Heng HuangICLR
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  19. 2024
    Function-space Parameterization of Neural Networks for Sequential LearningAidan Scannell, Riccardo Mereu, Paul E. Chang … Arno SolinICLR
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  20. 2024PDF ↗
  21. 2024
    Hebbian Learning based Orthogonal Projection for Continual Learning of Spiking Neural NetworksMingqing Xiao, Qingyan Meng, Zongpeng Zhang … Zhouchen LinICLR
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  22. 2024
    Elastic Feature Consolidation for Cold Start Exemplar-free Incremental LearningSimone Magistri, Tomaso Trinci, Albin Soutif--Cormerais … Andrew D. BagdanovICLR
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  23. 2024PDF ↗
  24. 2024PDF ↗
  25. 2024
    Locality Sensitive Sparse Encoding for Learning World Models OnlineZichen Liu, Chao Du, Wee Sun Lee, Min LinICLR
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  26. 2024
    Divide and not forget: Ensemble of selectively trained experts in Continual LearningGrzegorz Rypeść, Sebastian Cygert, Valeriya Khan … Bartłomiej TwardowskiICLR · Warsaw University of Technology · Integrated Detector Electronics AS (Norway) · +6
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  27. 2024
    TiC-CLIP: Continual Training of CLIP ModelsSaurabh Garg, Mehrdad Farajtabar, Hadi Pouransari … Fartash FaghriICLR
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  28. 2024
    TAIL: Task-specific Adapters for Imitation Learning with Large Pretrained ModelsZuxin Liu, Jesse Zhang, Kavosh Asadi … Rasool FakoorICLR
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  29. 2024
    TRAM: Bridging Trust Regions and Sharpness Aware MinimizationTom Sherborne, Naomi Saphra, Pradeep Dasigi, Hao PengICLR
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  30. 2024
    Class Incremental Learning via Likelihood Ratio Based Task PredictionHaowei Lin, Yijia Shao, Weinan Qian … Bing LiuICLR
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  31. 2024
    Understanding Catastrophic Forgetting in Language Models via Implicit InferenceSuhas Kotha, Jacob M. Springer, Aditi RaghunathanICLR
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  32. 2024
    Federated Orthogonal Training: Mitigating Global Catastrophic Forgetting in Continual Federated LearningYavuz Faruk Bakman, Duygu Nur Yaldiz, Yahya H. Ezzeldin, Salman AvestimehrICLR
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  33. 2024
    Progressive Fourier Neural Representation for Sequential Video CompilationHaeyong Kang, Jaehong Yoon, DaHyun Kim … Chang D. YooICLR
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  34. 2024
    Kalman Filter for Online Classification of Non-Stationary DataMichalis K. Titsias, Alexandre Galashov, Amal Rannen-Triki … Jörg BornscheinICLR
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  35. 2024
    A Probabilistic Framework for Modular Continual LearningLazar Valkov, Akash Srivastava, Swarat Chaudhuri, Charles SuttonICLR
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  36. 2024
    ViDA: Homeostatic Visual Domain Adapter for Continual Test Time AdaptationJiaming Liu, Senqiao Yang, Peidong Jia … Shanghang ZhangICLR
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  37. 2023PDF ↗
  38. 2023PDF ↗
  39. 2024
    Prediction Error-based Classification for Class-Incremental LearningMichał Zając, Tinne Tuytelaars, Gido M. van de VenICLR
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  40. 2023
    Towards Open Temporal Graph Neural NetworksKaituo Feng, Changsheng Li, Xiaolu Zhang, Jun ZhouICLR
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  41. 2023
    Sparse Distributed Memory is a Continual LearnerTrenton Bricken, Xander Davies, Deepak Singh … Gabriel KreimanICLR
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  42. 2023
    Is forgetting less a good inductive bias for forward transfer?Jiefeng Chen, Timothy Nguyen, Dilan Görür, Arslan ChaudhryICLR
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  43. 2023PDF ↗
  44. 2023
    Better Generative Replay for Continual Federated LearningDaiqing Qi, Handong Zhao, Sheng LiICLR
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  45. 2023
    New Insights for the Stability-Plasticity Dilemma in Online Continual LearningDahuin Jung, Dongjin Lee, Sunwon Hong … Sungroh YoonICLR
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  46. 2023PDF ↗
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  48. 2023
    Continual Pre-training of Language ModelsZixuan Ke, Yijia Shao, Haowei Lin … Bing LiuICLR
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  49. 2023PDF ↗
  50. 2025
    Online Reinforcement Learning in Non-Stationary Context-Driven EnvironmentsPouya Hamadanian, Arash Nasr-Esfahany, Malte Schwarzkopf … Mohammad AlizadehICLR
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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, and only papers with a PDF we can point you at, so every title opens the paper itself. 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.