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.

227 papers of 4,574 · showing 151–200Sort Recent · Most cited
  1. 2022
    ACIL: Analytic Class-Incremental Learning with Absolute Memorization and Privacy ProtectionHuiping Zhuang, Zhenyu Weng, Wei, Hongxin … Zhiping LinNeurIPS
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  2. 2022PDF ↗
  3. 2022
    The CLEAR Benchmark: Continual LEArning on Real-World ImageryZhiqiu Lin, Jia Shi, Deepak Pathak, Deva RamananNeurIPS
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  4. 2022
    Preservation of the Global Knowledge by Not-True Distillation in Federated LearningGihun Lee, Minchan Jeong, Yongjin Shin … Se-Young YunNeurIPS
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  5. 2022
    Memory Efficient Continual Learning with TransformersBeyza Ermis, Giovanni Zappella, Martin Wistuba … Cédric ArchambeauNeurIPS
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  6. 2022
    Repeated Augmented Rehearsal: A Simple but Strong Baseline for Online Continual LearningYaqian Zhang, Bernhard Pfahringer, Eibe Frank … Yunzhe JiaNeurIPS
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  7. 2019
    Lifelong Neural Predictive Coding: Learning Cumulatively Online without ForgettingAlex Ororbia, Ankur Mali, C Lee Giles, Daniel KiferNeurIPS
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  8. 2022
    Continual Learning In Environments With Polynomial Mixing TimesMatthew Riemer, Sharath Chandra Raparthy, Ignacio Cases … Irina RishNeurIPS
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  9. 2022
    Continual Learning with Evolving Class OntologiesZhiqiu Lin, Deepak Pathak, Yu-Xiong Wang … Shu KongNeurIPS
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  10. 2022
    A simple but strong baseline for online continual learning: Repeated Augmented RehearsalYaqian Zhang, Bernhard Pfahringer, Eibe Frank … Yunzhe JiaNeurIPS
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  11. 2021
    How Should Pre-Trained Language Models Be Fine-Tuned Towards Adversarial Robustness?Dong, Xinhsuai, Tuan, Luu Anh, Min Lin … Hanwang ZhangNeurIPS
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  12. 2020PDF ↗
  13. 2021PDF ↗
  14. 2021
    Continual Learning via Local Module CompositionOleksiy Ostapenko, Pau Rodríguez, M. Caccia, Laurent CharlinNeurIPS · Taras Shevchenko National University of Kyiv · University of Insubria · +1
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  15. 2021
    Overcoming Catastrophic Forgetting in Incremental Few-Shot Learning by Finding Flat MinimaGuangyuan Shi, Jiaxin Chen, Wenlong Zhang … Xiao-Ming WuNeurIPS · Hong Kong Polytechnic University
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  16. 2021
    Bridging Non Co-occurrence with Unlabeled In-the-wild Data for Incremental Object DetectionNa Dong, Yongqiang Zhang, Mingli Ding, Gim Hee LeeNeurIPS · Harbin Institute of Technology · National University of Singapore
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  17. 2021
    Learning where to learn: Gradient sparsity in meta and continual learningJohannes von Oswald, Dominic Zhao, Seijin Kobayashi … João SacramentoNeurIPS
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  18. 2021
    AFEC: Active Forgetting of Negative Transfer in Continual LearningLiyuan Wang, Ming‐Tian Zhang, Zhongfan Jia … Yi ZhongNeurIPS · Tsinghua University · University College London
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  19. 2021
    Flattening Sharpness for Dynamic Gradient Projection Memory Benefits Continual LearningDanruo Deng, Guangyong Chen, Jianye Hao … Pheng‐Ann HengNeurIPS · Chinese University of Hong Kong · Shenzhen Institutes of Advanced Technology · +1
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  20. 2021
    Powerpropagation: A sparsity inducing weight reparameterisationJonathan Schwarz, Siddhant M. Jayakumar, Razvan Pascanu … Yee Whye TehNeurIPS · Google (United States)
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  21. 2021
    Formalizing the Generalization-Forgetting Trade-off in Continual LearningKrishnan Raghavan, Prasanna BalaprakashNeurIPS · Argonne National Laboratory
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  22. 2021
    SSUL: Semantic Segmentation with Unknown Label for Exemplar-based Class-Incremental LearningSungmin Cha, Beomyoung Kim, Youngjoon Yoo, Taesup MoonNeurIPS · Sungkyunkwan University · Naver (South Korea) · +1
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  23. 2021
    Natural continual learning: success is a journey, not (just) a destinationTa-Chu Kao, Kristopher T. Jensen, Gido M. van de Ven … Guillaume HennequinNeurIPS
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  24. 2021
    Optimizing Reusable Knowledge for Continual Learning via MetalearningJulio Hurtado, Alain Raymond-Sáez, Álvaro SotoNeurIPS · Pontificia Universidad Católica de Chile
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  25. 2021
    A Procedural World Generation Framework for Systematic Evaluation of Continual LearningTimm Hess, Martin Mundt, Iuliia Pliushch, Visvanathan RameshNeurIPS · Goethe University Frankfurt
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  26. 2021
    Continual World: A Robotic Benchmark For Continual Reinforcement LearningMaciej Wołczyk, Michał Zając, Razvan Pascanu … Piotr MiłośNeurIPS · Jagiellonian University · Google (United States)
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  27. 2021
    CAM-GAN: Continual Adaptation Modules for Generative Adversarial NetworksSakshi Varshney, Vinay Kumar Verma, P K Srijith … Piyush RaiNeurIPS
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  28. 2020
    Firefly Neural Architecture Descent: a General Approach for Growing Neural NetworksLemeng Wu, Bo Liu, Peter Stone, Qiang LiuNeurIPS · The University of Texas at Austin
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  29. 2021
    Posterior Meta-Replay for Continual LearningChristian Henning, Maria R. Cervera, Francesco D'Angelo … João SacramentoNeurIPS
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  30. 2020
    A Combinatorial Perspective on Transfer LearningJianan Wang, Eren Sezener, David Budden … Joel VenessNeurIPS · Google (United States)
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  31. 2020
    Continual Learning in Low-rank Orthogonal SubspacesArslan Chaudhry, Naeemullah Khan, Puneet K. Dokania, Philip H. S. TorrNeurIPS · University of Oxford
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  32. 2020
    Meta-Consolidation for Continual LearningK J Joseph, Vineeth N BalasubramanianNeurIPS · Indian Institute of Technology Hyderabad
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  33. 2020
    La-MAML: Look-ahead Meta Learning for Continual LearningGunshi Gupta, Karmesh Yadav, Liam PaullNeurIPS · Carnegie Mellon University · Université de Montréal
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  34. 2020
    Lifelong Policy Gradient Learning of Factored Policies for Faster Training Without ForgettingJorge A. Mendez, Boyu Wang, Eric EatonNeurIPS · California University of Pennsylvania · University of Pennsylvania · +1
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  35. 2020
    RATT: Recurrent Attention to Transient Tasks for Continual Image CaptioningRiccardo Del Chiaro, Bartłomiej Twardowski, Andrew D. Bagdanov, Joost van de WeijerNeurIPS
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  36. 2020
    Meta-Learning through Hebbian Plasticity in Random NetworksElias Najarro, Sebastian RisiNeurIPS · IT University of Copenhagen
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  37. 2021PDF ↗
  38. 2020
    Supermasks in SuperpositionMitchell Wortsman, Vivek Ramanujan, Rosanne Liu … Ali FarhadiNeurIPS
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  39. 2020
    Task-Agnostic Online Reinforcement Learning with an Infinite Mixture of Gaussian ProcessesMengdi Xu, Wenhao Ding, Jiacheng Zhu … Ding ZhaoNeurIPS · Carnegie Mellon University · Tsinghua University · +1
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  40. 2020
    Learning to Learn with Feedback and Local PlasticityJack Lindsey, Ashok Litwin-KumarNeurIPS · Columbia University
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  41. 2020
    GAN Memory with No ForgettingYulai Cong, Miaoyun Zhao, Jianqiao Li … Lawrence CarinNeurIPS · Duke University
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  42. 2020
    Understanding the Role of Training Regimes in Continual LearningSeyed Iman Mirzadeh, Mehrdad Farajtabar, Razvan Pascanu, Hassan GhasemzadehNeurIPS
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  43. 2020
    Gaussian Gated Linear NetworksDavid Budden, Adam Marblestone, Eren Sezener … Joel VenessNeurIPS · Google (United States)
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  44. 2020
    Coresets via Bilevel Optimization for Continual Learning and StreamingZalán Borsos, Mojmír Mutný, Andreas KrauseNeurIPS · ETH Zurich
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  45. 2020
    Continual Deep Learning by Functional Regularisation of Memorable PastPingbo Pan, Siddharth Swaroop, Alexander Immer … Mohammad Emtiyaz KhanNeurIPS
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  46. 2020
    Dark Experience for General Continual Learning: a Strong, Simple BaselinePietro Buzzega, Matteo Boschini, Angelo Porrello … Simone CalderaraNeurIPS · University of Modena and Reggio Emilia
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  47. 2020
    Continual Learning with Node-Importance based Adaptive Group Sparse RegularizationSangwon Jung, Hongjoon Ahn, Sungmin Cha, Taesup MoonNeurIPS · Sungkyunkwan University
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  48. 2020
    Online Fast Adaptation and Knowledge Accumulation: a New Approach to Continual LearningM. Caccia, Pau Rodríguez, Оleksiy Ostapenko … Laurent CharlinNeurIPS
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  49. 2020
    Continuous Meta-Learning without TasksJ. Michael Harrison, Apoorva Sharma, Chelsea Finn, Marco PavoneNeurIPS · Stanford University · University of California, Berkeley
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  50. 2019
    Continual Unsupervised Representation LearningDushyant Rao, Francesco Visin, Andrei Rusu … Raia HadsellNeurIPS · Carnegie Mellon University · Google (United States) · +2
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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.