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.

793 papers of 4,574 · showing 751–793Sort Recent · Most cited
  1. 2024
    Keep moving: identifying task-relevant subspaces to maximise plasticity for newly learned tasksDaniel Anthes, Sushrut Thorat, Peter König, Tim C. KietzmannCoLLAs
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  2. 2024
    TRAM: Bridging Trust Regions and Sharpness Aware MinimizationTom Sherborne, Naomi Saphra, Pradeep Dasigi, Hao PengICLR
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  3. 2024
    Hadamard Domain Training with Integers for Class Incremental Quantized LearningMartin Schiemer, Clemens J. S. Schaefer, Jayden Parker Vap … Siddharth JoshiCoLLAs
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  4. 2024PDF ↗
  5. 2024
    Adaptive Visual Scene Understanding: Incremental Scene Graph GenerationNaitik Khandelwal, Xiao Liu, Mengmi ZhangNeurIPS
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  6. 2024PDF ↗
  7. 2024
    Class Incremental Learning via Likelihood Ratio Based Task PredictionHaowei Lin, Yijia Shao, Weinan Qian … Bing LiuICLR
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  8. 2024
    Understanding Catastrophic Forgetting in Language Models via Implicit InferenceSuhas Kotha, Jacob M. Springer, Aditi RaghunathanICLR
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  9. 2024
    Rethinking Momentum Knowledge Distillation in Online Continual LearningNicolas Michel, Maorong Wang, Ling Xiao, Toshihiko YamasakiICML
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  10. 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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  11. 2024
    Fine-tuning can cripple your foundation model; preserving features may be the solutionJishnu Mukhoti, Yarin Gal, Philip H. S. Torr, Puneet K. DokaniaTMLR
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  12. 2024
    GRASP: A Rehearsal Policy for Efficient Online Continual LearningMd Yousuf Harun, Jhair Gallardo, Chen, Junyu, Kanan, ChristopherCoLLAs
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  13. 2024
    Maintaining Plasticity in Continual Learning via Regenerative RegularizationSaurabh Kumar, Henrik Marklund, Benjamin Van RoyCoLLAs
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  14. 2024
    Lookbehind-SAM: k steps back, 1 step forwardGonçalo Mordido, Pranshu Malviya, Aristide Baratin, Sarath ChandarICML
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  15. 2024
    Lifelong Generative Adversarial AutoencoderFei Ye, Adrian G. BorşTNNLS · University of York
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  16. 2024PDF ↗
  17. 2024
    Progressive Fourier Neural Representation for Sequential Video CompilationHaeyong Kang, Jaehong Yoon, DaHyun Kim … Chang D. YooICLR
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  18. 2024
    Continual Adaptation of Vision Transformers for Federated LearningShaunak Halbe, Smith, James Seale, Junjiao Tian, Zsolt KiraTMLR
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  19. 2024
    Kalman Filter for Online Classification of Non-Stationary DataMichalis K. Titsias, Alexandre Galashov, Amal Rannen-Triki … Jörg BornscheinICLR
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  20. 2024
    Efficient Bayesian Policy Reuse With a Scalable Observation Model in Deep Reinforcement LearningJinmei Liu, Zhi Wang, Chunlin Chen, Daoyi DongTNNLS · Nanjing University · University of Canberra · +1
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  21. 2024
    A Probabilistic Framework for Modular Continual LearningLazar Valkov, Akash Srivastava, Swarat Chaudhuri, Charles SuttonICLR
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  24. 2024
    ViDA: Homeostatic Visual Domain Adapter for Continual Test Time AdaptationJiaming Liu, Senqiao Yang, Peidong Jia … Shanghang ZhangICLR
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  25. 2024
    Dynamics-Adaptive Continual Reinforcement Learning via Progressive ContextualizationTiantian Zhang, Zichuan Lin, Yuxing Wang … Xiu LiTNNLS · Tencent (China) · Tsinghua University · +1
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  26. 2024
    Masked Autoencoders are Efficient Continual Federated LearnersSubarnaduti Paul, Lars-Joel Frey, Roshni Kamath … Martin MundtCoLLAs
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  27. 2024
    Overcoming the Stability Gap in Continual LearningMd Yousuf Harun, Christopher KananTMLR
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  28. 2024
    Uncertainty-Aware Distillation for Semi-Supervised Few-Shot Class-Incremental LearningYawen Cui, Wanxia Deng, Haoyu Chen, Li LiuTNNLS · University of Oulu · National University of Defense Technology
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  29. 2024
    Prediction Error-based Classification for Class-Incremental LearningMichał Zając, Tinne Tuytelaars, Gido M. van de VenICLR
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  30. 2024PDF ↗
  31. 2024
    Voyager: An Open-Ended Embodied Agent with Large Language ModelsGuanzhi Wang, Yuqi Xie, Yunfan Jiang … Anima AnandkumarTMLR
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  32. 2024
    Continual Multimodal Knowledge Graph ConstructionXiang Chen, Jintian Zhang, Xiaohan Wang … Huajun ChenIJCAI
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  33. 2024
    A Survey on Few-Shot Class-Incremental LearningSongsong Tian, Lusi Li, Weijun Li … Prayag TiwariNeural Networks
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  34. 2024
    Continual Diffusion: Continual Customization of Text-to-Image Diffusion with C-LoRASmith, James Seale, Yen-Chang Hsu, Lingyu Zhang … Hongxia JinTMLR
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  37. 2024
    CoDeC: Communication-Efficient Decentralized Continual LearningSakshi Choudhary, Sai Aparna Aketi, Gobinda Saha, Kaushik RoyTMLR
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  38. 2024
    PromptFusion: Decoupling Stability and Plasticity for Continual LearningHao Chen, Zuxuan Wu, Xintong Han … Yu–Gang JiangECCV
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  41. 2024
    Evolutionary Generalized Zero-Shot LearningDubing Chen, Jiang, Chenyi, Haofeng ZhangIJCAI
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  42. 2024
    Deep Class-Incremental Learning From Decentralized DataXiaohan Zhang, Songlin Dong, Jinjie Chen … Xiaopeng HongTNNLS · Xi'an Jiaotong University · Huawei Technologies (China) · +1
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  43. 2024
    Continual Pre-Training Mitigates Forgetting in Language and VisionAndrea Cossu, Tinne Tuytelaars, Antonio Carta … Davide BacciuNeural Networks
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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.