Related work

The foundational work on continual learning, 1980 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

37 papers of 8,653Sort Recent · Most cited
  1. 2023
    TiC-CLIP: Continual Training of CLIP ModelsSaurabh Garg, Mehrdad Farajtabar, Hadi Pouransari … Fartash FaghriICLR
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  2. 2023
    TAIL: Task-specific Adapters for Imitation Learning with Large Pretrained ModelsZuxin Liu, Jesse Zhang, Kavosh Asadi … Rasool FakoorICLR
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  3. 2023
    TRAM: Bridging Trust Regions and Sharpness Aware MinimizationTom Sherborne, Naomi Saphra, Pradeep Dasigi, Hao PengICLR
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  4. 2023
    Class Incremental Learning via Likelihood Ratio Based Task PredictionHaowei Lin, Yijia Shao, Weinan Qian … Bing LiuICLR
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  5. 2023
    Understanding Catastrophic Forgetting in Language Models via Implicit InferenceSuhas Kotha, Jacob M. Springer, Aditi RaghunathanICLR
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  6. 2023
    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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  7. 2023
    Progressive Fourier Neural Representation for Sequential Video CompilationHaeyong Kang, Jaehong Yoon, DaHyun Kim … Chang D. YooICLR
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  8. 2023
    Kalman Filter for Online Classification of Non-Stationary DataMichalis K. Titsias, Alexandre Galashov, Amal Rannen-Triki … Jörg BornscheinICLR
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  9. 2023
    A Probabilistic Framework for Modular Continual LearningLazar Valkov, Akash Srivastava, Swarat Chaudhuri, Charles SuttonICLR
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  10. 2023
    ViDA: Homeostatic Visual Domain Adapter for Continual Test Time AdaptationJiaming Liu, Senqiao Yang, Peidong Jia … Shanghang ZhangICLR
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  13. 2023
    Prediction Error-based Classification for Class-Incremental LearningMichał Zając, Tinne Tuytelaars, Gido M. van de VenICLR
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  14. 2023
    Towards Open Temporal Graph Neural NetworksKaituo Feng, Changsheng Li, Xiaolu Zhang, Jun ZhouICLR
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  15. 2023
    Sparse Distributed Memory is a Continual LearnerTrenton Bricken, Xander Davies, Deepak Singh … Gabriel KreimanICLR
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  16. 2023
    Is forgetting less a good inductive bias for forward transfer?Jiefeng Chen, Timothy Nguyen, Dilan Görür, Arslan ChaudhryICLR
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  17. 2023PDF ↗
  18. 2023
    Better Generative Replay for Continual Federated LearningDaiqing Qi, Handong Zhao, Sheng LiICLR
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  19. 2023
    New Insights for the Stability-Plasticity Dilemma in Online Continual LearningDahuin Jung, Dongjin Lee, Sunwon Hong … Sungroh YoonICLR
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  22. 2023
    Continual Pre-training of Language ModelsZixuan Ke, Yijia Shao, Haowei Lin … Bing LiuICLR
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  23. 2023PDF ↗
  24. 2023
    Online Reinforcement Learning in Non-Stationary Context-Driven EnvironmentsPouya Hamadanian, Arash Nasr-Esfahany, Malte Schwarzkopf … Mohammad AlizadehICLR
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  25. 2023
    Progressive Prompts: Continual Learning for Language ModelsAnastasia Razdaibiedina, Yuning Mao, Rui Hou … Amjad AlmahairiICLR
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  26. 2023
    DEJA VU: Continual Model Generalization For Unseen DomainsChenxi Liu, Lixu Wang, Lingjuan Lyu … Qi ZhuICLR
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  27. 2023
    Artificial Neuronal Ensembles with Learned Context Dependent GatingM. J. Tilley, Michelle Miller, David A. FreedmanICLR
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  28. 2023
  29. 2023
  30. 2023
    Online Bias Correction for Task-Free Continual LearningA. Chrysakis, Marie-Francine MoensICLR
  31. 2023
    Online Boundary-Free Continual Learning by Scheduled Data PriorHyun-woo Koh, M. Seo, Jihwan Bang … Jonghyun ChoiICLR
  32. 2023
  33. 2023
    Continual Learning of Language ModelsZixuan Ke, Yijia Shao, Haowei Lin … Bin LiuICLR
  34. 2023
  35. 2023
    Optimizing Spca-based Continual Learning: A Theoretical ApproachChunchun Yang, Malik Tiomoko, Zengfu WangICLR
  36. 2023
    Self-Supervised Continual LearningK. Thakral, S. Mittal, Utkarsh Uppal … Richa SinghICLR
  37. 2023
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.