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.

422 papers of 8,653 · showing 1–50Sort Recent · Most cited
  1. 2020
    Simple Lifelong Learning MachinesJoshua T. Vogelstein, Jayanta Dey, Hayden S. Helm … Carey E. PriebeTPAMI · Johns Hopkins University · Baylor College of Medicine · +1
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  2. 2020
    Hidden Markov Neural NetworksLorenzo Rimella, Nick WhiteleyEntropy · Collegio Carlo Alberto · University of Turin · +1
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  3. 2020
    A Layered Learning Approach to Scaling in Learning Classifier Systems for Boolean ProblemsIsidro M. Alvarez, Trung B. Nguyen, Will N. Browne, Mengjie ZhangEvolutionary Computation · Victoria University of Wellington · Statistics New Zealand · +1
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  4. 2020
    A Wholistic View of Continual Learning with Deep Neural Networks: Forgotten Lessons and the Bridge to Active and Open World LearningMartin Mundt, Yongwon Hong, Iuliia Pliushch, Visvanathan RameshNeural Networks · Goethe University Frankfurt · Technische Universität Darmstadt · +1
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  5. 2020
    Overcoming Catastrophic Forgetting via Direction-Constrained OptimizationYunfei Teng, Anna Choromanska, Murray Campbell … Lior HoreshSpringer LNCS · New York University
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  6. 2020
    Class-Incremental Learning: Survey and Performance Evaluation on Image ClassificationMarc Masana, Xialei Liu, Bartłomiej Twardowski … Joost van de WeijerTPAMI · Computer Vision Center
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  7. 2020
    Instance Weighted Incremental Evolution Strategies for Reinforcement Learning in Dynamic EnvironmentsZhi Wang, Chunlin Chen, Daoyi DongTNNLS · University of Canberra · UNSW Sydney · +1
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  8. 2020
    Self-Training for Class-Incremental Semantic SegmentationLu Yu, Xialei Liu, Joost van de WeijerTNNLS · Tianjin University of Technology · Nankai University · +1
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  9. 2020
    Efficient Architecture Search for Continual LearningQiang Gao, Zhipeng Luo, Diego Klabjan, Fengli ZhangTNNLS · Southwestern University of Finance and Economics · Northwestern University · +1
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  10. 2020
    Drinking From a Firehose: Continual Learning With Web-Scale Natural LanguageHexiang Hu, Ozan Şener, Fei Sha, Vladlen KoltunTPAMI · University of Southern California · Intel (United States)
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  11. 2020PDF ↗
  12. 2020
    MgSvF: Multi-Grained Slow versus Fast Framework for Few-Shot Class-Incremental LearningHanbin Zhao, Yongjian Fu, Mintong Kang … Xi LiTPAMI · Zhejiang University of Science and Technology · Huawei Technologies (China)
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  13. 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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  14. 2020
    Learning Invariant Representation for Continual LearningGhada Sokar, Decebal Constantin Mocanu, Mykola PechenizkiyarXiv · Eindhoven University of Technology · University of Twente
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  15. 2020
    Refining Sample Embeddings with Relation Prototypes to Enhance Continual Relation ExtractionLi Cui, Deqing Yang, Jiaxin Yu … Yanghua XiaoACL · Fudan University
  16. 2020
    Continual Learning for Task-oriented Dialogue System with Iterative Network Pruning, Expanding and MaskingBinzong Geng, Fajie Yuan, Qiancheng Xu … Min YangACL · University of Science and Technology of China · Chinese Academy of Sciences · +7
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  17. 2020
    Learning to Solve NLP Tasks in an Incremental Number of LanguagesGiuseppe Castellucci, Simone Filice, Danilo Croce, Roberto BasiliACL · Amazon (United States) · Seattle University · +3
  18. 2020
    Rational LAMOL: A Rationale-based Lifelong Learning FrameworkKasidis Kanwatchara, Thanapapas Horsuwan, Piyawat Lertvittayakumjorn … Peerapon VateekulACL · Chulalongkorn University · Imperial College London
  19. 2020
    Learn to Bind and Grow Neural StructuresAzhar Shaikh, Nishant SinhaCOMAD/CODS · PES University
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  20. 2020
    Detecting Changes and Avoiding Catastrophic Forgetting in Dynamic Partially Observable EnvironmentsJeffery Dick, Paweł Ładosz, Eseoghene Ben-Iwhiwhu … Andrea SoltoggioFrontiers · Loughborough University · Teikyo University · +1
  21. 2020
    A New Artificial Immune System Based on Continuous Learning for Pattern RecognitionSimone F. Souza, Fernando Parra dos Anjos Lima, Fábio Roberto ChavaretteRevista de Informática Teórica e Aplicada · Universidade do Estado de Mato Grosso · Instituto Federal de Educação, Ciência e Tecnologia de Mato Grosso · +1
  22. 2020
    Selective Forgetting of Deep Networks at a Finer Level than SamplesTomohiro Hayase, Suguru Yasutomi, Takashi KatoharXiv
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  23. 2020
  24. 2020
  25. 2020
    Entropy-based Sample Selection for Online Continual LearningFelix Wiewel, Bin YangEuropean Signal Processing Conference (EUSIPCO) · University of Stuttgart
  26. 2020
    Learning without Forgetting for Decentralized Neural Nets with Low Communication OverheadXinyue Liang, Alireza M. Javid, Mikael Skoglund, Saikat ChatterjeeEuropean Signal Processing Conference (EUSIPCO) · KTH Royal Institute of Technology
  27. 2020
    Lifelong Machine Learning for Regional-Based Image Classification in Open DatasetsHashem Alyami, Abdullah Alharbi, M. Irfan UddinSymmetry · Taif University · Kohat University of Science and Technology
  28. 2020
    Consequences of Slow Neural Dynamics for Incremental LearningShima Rahimi Moghaddam, Fanjun Bu, Christopher J. HoneyarXiv
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  29. 2020
    Continual learning classification method with constant-sized memory cells based on the artificial immune systemDong Li, Shulin Liu, Furong Gao, Xin SunKnowledge-Based Systems · Hong Kong University of Science and Technology · Changzhou University · +1
  30. 2020
    Incremental Learning for Autonomous Navigation of Mobile Robots based on Deep Reinforcement LearningManh Luong, Cuong PhamJournal of Intelligent & Robotic Systems · VinUniversity · Posts and Telecommunications Institute of Technology
  31. 2020
    Extending Conditional Convolution Structures For Enhancing Multitasking Continual LearningCheng-Hao Tu, Cheng-En Wu, Chu-Song ChenAsia-Pacific Signal and Information Processing Associatio…
  32. 2020
    Cuepervision: self-supervised learning for continuous domain adaptation without catastrophic forgettingMark Schutera, Frank M. Hafner, Jochen Abhau … Markus ReischlImage and Vision Computing · Karlsruhe Institute of Technology · ZF Friedrichshafen (Germany)
  33. 2020
    Pseudo-Rehearsal: Achieving Deep Reinforcement Learning without Catastrophic ForgettingCraig Atkinson, Brendan McCane, Lech Szymanski, Anthony RobinsNeurocomputing · University of Otago
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  34. 2020
    Association: Remind Your GAN not to ForgetYi Gu, Jie Li, Yuting Gao … Zhang, ZiruiarXiv
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  35. 2020
    Enhancing network modularity to mitigate catastrophic forgettingLu Chen, Masayuki MurataApplied Network Science · Kyoto Institute of Technology · Osaka Health Science University · +1
  36. 2020
    Continual learning with direction-constrained optimizationYunfei Teng, A. Choromańska, Murray CampbellarXiv
  37. 2020
    Lethean Attack: An Online Data Poisoning TechniqueEyal PerryarXiv · Massachusetts Institute of Technology
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  38. 2020
    Consolidation via Policy Information Regularization in Deep RL for Multi-Agent GamesTyler Malloy, Tim Klinger, Miao Liu … Chris R. SimsarXiv
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  39. 2020
    Motivational engine and long-term memory coupling within a cognitive architecture for lifelong open-ended learningJ. A. Becerra, Alejandro Romero, Francisco Bellas, Richard J. DuroNeurocomputing · Universidade da Coruña
  40. 2020
    Generalized Continual Zero-Shot LearningChandan Gautam, Sethupathy Parameswaran, Ashish Mishra, Suresh SundaramarXiv · Indian Institute of Science Bangalore · Indian Institute of Technology Madras
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  41. 2020
    Brick Assembly Networks: An Effective Network for Incremental Learning ProblemsJiacang Ho, Dae-Ki KangElectronics · Dongseo University
  42. 2020PDF ↗
  43. 2020
    Comparative Analysis of Catastrophic Forgetting in Metric LearningJiahao Huo, Terence L. van ZylInternational Conference on Soft Computing & Machine… · University of the Witwatersrand · University of Johannesburg
  44. 2020
    Continual Learning with Deep Artificial NeuronsBlake Camp, Jaya Krishna Mandivarapu, Rolando EstradaarXiv · Georgia State University
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  45. 2020
    Incremental Learning Using a Grow-and-Prune Paradigm With Efficient Neural NetworksXiaoliang Dai, Hongxu Yin, Niraj K. JhaIEEE Transactions · Princeton University
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  46. 2020
    Lifelong learning of interpretable image representationsFei Ye, Adrian G. BorşICIP · University of York
  47. 2020
    State Primitive Learning to Overcome Catastrophic Forgetting in RoboticsFangzhou Xiong, Zhiyong Liu, Kaizhu Huang … Hong QiaoCognitive Computation · Shandong Institute of Automation · University of Chinese Academy of Sciences · +2
  48. 2020
    A Novel Layer Sharing-based Incremental Learning via Bayesian OptimizationYoonsik Choe, Bomi Kim, Taehyeon KimApplied Sciences · Yonsei University
  49. 2020
    Class incremental learning via Multi-hinge distillationQianhe Lin, Yuanlong Yu, Zhiyong HuangChinese Automation Congress (CAC) · Fuzhou University · Zhejiang Lab
  50. 2020PDF ↗
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.