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.

301 papers of 8,653 · showing 251–300Sort Recent · Most cited
  1. 2020
    Reparameterizing Convolutions for Incremental Multi-Task Learning without Task InterferenceMenelaos Kanakis, David Brüggemann, Suman Saha … Luc Van GoolECCV · ETH Zurich · KU Leuven
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  2. 2020PDF ↗
  3. 2020
    Online Continual Learning under Extreme Memory ConstraintsEnrico Fini, Stéphane Lathuilière, Enver Sangineto … Elisa RicciECCV · University of Trento · Télécom Paris · +2
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  4. 2020
    Class-Incremental Domain AdaptationJogendra Nath Kundu, Rahul Venkatesh, Naveen Venkat … R. Venkatesh BabuECCV · Indian Institute of Science Bangalore
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  5. 2020
    Disentangle-based Continual Graph Representation LearningXiaoyu Kou, Yankai Lin, Shaobo Liu … Yan ZhangEMNLP · Peking University · Tencent (China)
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  6. 2020
    Incremental Event Detection via Knowledge Consolidation NetworksPengfei Cao, Yubo Chen, Jun Zhao, Taifeng WangEMNLP
  7. 2020
    RODEO: Replay for Online Object DetectionManoj Acharya, Tyler L. Hayes, Christopher KananBMVC · Rochester Institute of Technology
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  8. 2020
    A Two-phase Prototypical Network Model for Incremental Few-shot Relation ClassificationHaopeng Ren, Yi Cai, Xiaofeng Chen … Qing LiCOLING · Ministry of Natural Resources · South China University of Technology · +1
  9. 2020
    Distill and Replay for Continual Language LearningJingyuan Sun, Shaonan Wang, Jiajun Zhang, Chengqing ZongCOLING · Institute of Automation · University of Chinese Academy of Sciences · +2
  10. 2020
    Continual Adaptation for Efficient Machine CommunicationRobert D. Hawkins, Minae Kwon, Dorsa Sadigh, Noah D. GoodmanCoNLL · Princeton University · Department of Physics, Mathematics and Informatics · +1
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  11. 2020
    Online Continual Learning on SequencesGerman I. Parisi, Vincenzo LomonacoStudies in computational intelligence · Universität Hamburg · University of Bologna
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  12. 2020
    Piggyback GAN: Efficient Lifelong Learning for Image Conditioned GenerationMengyao Zhai, Lei Chen, Jiawei He … Greg MoriECCV · Simon Fraser University · Collège Boréal
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  13. 2020PDF ↗
  14. 2020PDF ↗
  15. 2020
    On the Exploration of Incremental Learning for Fine-grained Image RetrievalWei Chen, Yu Liu, Weiping Wang … Michael S. LewBMVC · Leiden University · KU Leuven · +1
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  16. 2020
    Incremental Few-Shot Meta-learning via Indirect Discriminant AlignmentQing Liu, Orchid Majumder, Alessandro Achille … Stefano SoattoECCV · Johns Hopkins University · Amazon (United States)
  17. 2020
    Visually Grounded Continual Learning of Compositional PhrasesXisen Jin, Junyi Du, Arka Sadhu … Xiang RenEMNLP · University of Southern California · California Southern University · +1
  18. 2020
    An Empirical Investigation towards Efficient Multi-Domain Language Model Pre-trainingKristjan Arumae, Qing Sun, Parminder BhatiaEMNLP · Amazon (United States) · Seattle University · +1
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  19. 2020
    Human Action Recognition and Assessment via Deep Neural Network Self-OrganizationGerman I. ParisiModelling Human Motion · Universität Hamburg
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  20. 2020
    Using the Past Knowledge to Improve Sentiment ClassificationQi Qin, Wenpeng Hu, Bing LiuEMNLP · Peking University · King University
  21. 2020
    Continual Learning Long Short Term MemoryXin Guo, Yu Tian, Qinghan Xue … Xiaolong WangEMNLP · University of Delaware
  22. 2020
    Moving Towards Open Set Incremental Learning: Readily Discovering New AuthorsJustin Leo, Jugal KalitaAdvances in intelligent systems and computing · University of Colorado Colorado Springs
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  23. 2020
    Findings of the First Shared Task on Lifelong Learning Machine TranslationLoïc Barrault, Magdalena Biesialska, Marta R. Costa‐jussà … Olivier GalibertEMNLP · University of Sheffield · Universitat Politècnica de Catalunya · +2
  24. 2020
    M2KD: Incremental Learning via Multi-model and Multi-level Knowledge DistillationPeng Zhou, Long Mai, Jianming Zhang … Larry S. DavisBMVC · Beth Israel Deaconess Medical Center · Adobe Systems (United States) · +2
  25. 2020
    Morphology dictates learnability in neural controllersJoshua Powers, Ryan Grindle, Sam Kriegman … Josh BongardThe 2020 Conference on Artificial Life · University of Vermont
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  26. 2020
    Continual Learning of Image Translation Networks Using Task-Dependent Weight Selection MasksMatsumoto Asato, ‪Keiji Yanai‬Springer LNCS · University of Electro-Communications
  27. 2020
    Confidence Calibration for Incremental LearningDongmin Kang, Yeonsik Jo, Yeongwoo Nam, Jonghyun ChoiIEEE Access · Gwangju Institute of Science and Technology
  28. 2020
    Memory Protection Generative Adversarial Network (MPGAN): A Framework to Overcome the Forgetting of GANs Using Parameter Regularization MethodsYifan Chang, Wenbo Li, Jian Peng … Yingliang HuangIEEE Access · University of Science and Technology of China · Hefei Institute of Technology Innovation · +3
  29. 2020
    A Perpetual Learning Algorithm That Incrementally Improves Performance With DeliberationHaiou Qin, Du ZhangIEEE Access · Macau University of Science and Technology
  30. 2020
    An Incremental Learning Network Model Based on Random Sample Distribution FittingWencong Wang, Lan Huang, Hao Liu … Kangping WangSpringer LNCS · Jilin University · Jilin Province Science and Technology Department
  31. 2020
    Mitigate Catastrophic Forgetting by Varying GoalsLu Chen, Masayuki MurataInternational Conference on Agents and Artificial Intelli… · Kyoto Institute of Technology · The University of Osaka
  32. 2020
    Organizing recurrent network dynamics by task-computation to enable continual learningLea Duncker, Laura N. Driscoll, K. Shenoy … David SussilloNeurIPS
  33. 2020
    Calibrating CNNs for Lifelong LearningPravendra Singh, V. Verma, Pratik Mazumder … Piyush RaiNeurIPS
  34. 2020
    Mitigating Forgetting in Online Continual Learning via Instance-Aware ParameterizationHung-Jen Chen, An-Chieh Cheng, Da-Cheng Juan … Min SunNeurIPS
  35. 2020
  36. 2020
    Progressive Memory Banks for Incremental Domain AdaptationNabiha Asghar, Lili Mou, Kira A. Selby … Xin JiangICLR
  37. 2020
  38. 2020
  39. 2020
    Continuous Meta-Learning without TasksJ. Michael Harrison, Apoorva Sharma, Chelsea Finn, Marco PavoneNeurIPS · Stanford University · University of California, Berkeley
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  40. 2020
    Continual Learning with Adaptive Weights (CLAW)Tameem Adel, Han Zhao, Richard E. TurnerICLR
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  41. 2020
    Online Topology Learning by a Gaussian Membership-Based Self-Organizing Incremental Neural NetworkHang Yu, Jie Lü, Guangquan ZhangTNNLS · University of Technology Sydney
  42. 2020
    Toward Training Recurrent Neural Networks for Lifelong LearningShagun Sodhani, Sarath Chandar, Yoshua BengioNeural Computation · Université de Montréal
  43. 2020
    Orthogonal Gradient Descent for Continual LearningMehrdad Farajtabar, Navid Azizan, A. Mott, Ang LiAISTATS · Google (United States)
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  44. 2020
    Compositional Language Continual LearningYuanpeng Li, Liang Zhao, Kenneth Ward Church, Mohamed ElhoseinyICLR
  45. 2020
    Tree-CNN: A hierarchical Deep Convolutional Neural Network for incremental learningDeboleena Roy, Priyadarshini Panda, Kaushik RoyNeural Networks · Purdue University West Lafayette
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  46. 2020
    LAMOL: LAnguage MOdeling for Lifelong Language LearningFan-Keng Sun, Cheng-Hao Ho, Hung-yi LeeICLR · Massachusetts Institute of Technology · National Taiwan University
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  47. 2020
    Generative Memory for Lifelong LearningXin Su, Shangqi Guo, Tian Tan, Feng ChenTNNLS · Beijing Advanced Sciences and Innovation Center · Tsinghua University · +1
  48. 2020PDF ↗
  49. 2020
    Uncertainty-guided Continual Learning with Bayesian Neural NetworksSayna Ebrahimi, Mohamed Elhoseiny, Trevor Darrell, Marcus RohrbachICLR · University of California, Berkeley · King Abdullah University of Science and Technology · +1
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  50. 2020
    Continual learning with hypernetworksJohannes von Oswald, Christian Henning, J. Sacramento, B. GreweICLR
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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. By default it shows the papers we have a reason to trust: published at a venue like NeurIPS, ICML, ICLR, CVPR or TPAMI, or written by someone who has published there, or cited a few hundred times. The rest are one click away under “All papers”. 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.