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.

256 papers of 11,817 · showing 101–150Sort Recent · Most cited
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  3. 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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  4. 2024
    Scalable Language Model with Generalized Continual LearningBohao Peng, Zhuotao Tian, Shu Liu … Jiaya JiaICLR
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  8. 2024
    A Unified and General Framework for Continual LearningZhenyi Wang, Yan Li, Li Shen, Heng HuangICLR
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  9. 2024
    Function-space Parameterization of Neural Networks for Sequential LearningAidan Scannell, Riccardo Mereu, Paul E. Chang … Arno SolinICLR
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  11. 2024
    Hebbian Learning based Orthogonal Projection for Continual Learning of Spiking Neural NetworksMingqing Xiao, Qingyan Meng, Zong-Peng Zhang … Zhouchen LinICLR
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  12. 2024
    Elastic Feature Consolidation for Cold Start Exemplar-free Incremental LearningSimone Magistri, Tomaso Trinci, Albin Soutif-Cormerais … Andrew D. BagdanovICLR
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  16. 2024
    Divide and not forget: Ensemble of selectively trained experts in Continual LearningGrzegorz Rype's'c, Sebastian Cygert, Valeriya Khan … Bartłomiej TwardowskiICLR
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  17. 2024
    Prompt Gradient Projection for Continual LearningJingyang Qiao, Zhizhong Zhang, Xin Tan … Yuan XieICLR
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  28. 2023
    TiC-CLIP: Continual Training of CLIP ModelsSaurabh Garg, Mehrdad Farajtabar, Hadi Pouransari … Fartash FaghriICLR
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  29. 2023
    How connectivity structure shapes rich and lazy learning in neural circuitsY. Liu, A. Baratin, Jonathan Cornford … Guillaume LajoieICLR
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  30. 2023
    TAIL: Task-specific Adapters for Imitation Learning with Large Pretrained ModelsZuxin Liu, Jesse Zhang, Kavosh Asadi … Rasool FakoorICLR
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  31. 2023
    TRAM: Bridging Trust Regions and Sharpness Aware MinimizationTom Sherborne, Naomi Saphra, Pradeep Dasigi, Hao PengICLR
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  32. 2023
    Class Incremental Learning via Likelihood Ratio Based Task PredictionHaowei Lin, Yijia Shao, W. Qian … Bing LiuICLR
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  34. 2023
    Understanding Catastrophic Forgetting in Language Models via Implicit InferenceSuhas Kotha, Jacob Mitchell Springer, Aditi RaghunathanICLR
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    Progressive Fourier Neural Representation for Sequential Video CompilationHaeyong Kang, Dahyun Kim, Jaehong Yoon … C. D. YooICLR
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  37. 2023
    Kalman Filter for Online Classification of Non-Stationary DataMichalis K. Titsias, Alexandre Galashov, Amal Rannen-Triki … J. BornscheinICLR
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  38. 2023
    A Probabilistic Framework for Modular Continual LearningL. Valkov, Akash Srivastava, Swarat Chaudhuri, Charles SuttonICLR
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  39. 2023
    ViDA: Homeostatic Visual Domain Adapter for Continual Test Time AdaptationJiaming Liu, Senqiao Yang, Peidong Jia … Shanghang ZhangICLR
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    Prediction Error-based Classification for Class-Incremental LearningMichal Zajkac, T. Tuytelaars, Gido M. van de VenICLR
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  43. 2023
    A Stable and Scalable Method for Solving Initial Value PDEs with Neural NetworksMarc Finzi, Andres Potapczynski, M. Choptuik, A. WilsonICLR
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  44. 2023
    Towards Open Temporal Graph Neural NetworksKaituo Feng, Changsheng Li, Xiaolu Zhang, Jun ZhouICLR
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  45. 2023
    Sparse Distributed Memory is a Continual LearnerTrenton Bricken, Xander Davies, Deepak Singh … G. KreimanICLR
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  46. 2023
    Is forgetting less a good inductive bias for forward transfer?Jiefeng Chen, Timothy Nguyen, Dilan Gorur, Arslan ChaudhryICLR
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  48. 2023
    Better Generative Replay for Continual Federated LearningDaiqing Qi, Handong Zhao, Sheng LiICLR
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  49. 2023
    New Insights for the Stability-Plasticity Dilemma in Online Continual LearningDahuin Jung, Dongjin Lee, Sunwon Hong … Sungroh YoonICLR
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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 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.