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 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
    PDF ↗
  2. 2020
    Hidden Markov Neural NetworksLorenzo Rimella, Nick WhiteleyEntropy · Collegio Carlo Alberto · University of Turin · +1
    PDF ↗
  3. 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
    PDF ↗
  4. 2020
    Overcoming Catastrophic Forgetting via Direction-Constrained OptimizationYunfei Teng, Anna Choromanska, Murray Campbell … Lior HoreshSpringer LNCS · New York University
    PDF ↗
  5. 2020
    Class-Incremental Learning: Survey and Performance Evaluation on Image ClassificationMarc Masana, Xialei Liu, Bartłomiej Twardowski … Joost van de WeijerTPAMI · Computer Vision Center
    PDF ↗
  6. 2020
    Instance Weighted Incremental Evolution Strategies for Reinforcement Learning in Dynamic EnvironmentsZhi Wang, Chunlin Chen, Daoyi DongTNNLS · University of Canberra · UNSW Sydney · +1
    PDF ↗
  7. 2020
    Self-Training for Class-Incremental Semantic SegmentationLu Yu, Xialei Liu, Joost van de WeijerTNNLS · Tianjin University of Technology · Nankai University · +1
    PDF ↗
  8. 2020
    Efficient Architecture Search for Continual LearningQiang Gao, Zhipeng Luo, Diego Klabjan, Fengli ZhangTNNLS · Southwestern University of Finance and Economics · Northwestern University · +1
    PDF ↗
  9. 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)
    PDF ↗
  10. 2020PDF ↗
  11. 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)
    PDF ↗
  12. 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
    PDF ↗
  13. 2020
    Learning Invariant Representation for Continual LearningGhada Sokar, Decebal Constantin Mocanu, Mykola PechenizkiyarXiv · Eindhoven University of Technology · University of Twente
    PDF ↗
  14. 2020
    Refining Sample Embeddings with Relation Prototypes to Enhance Continual Relation ExtractionLi Cui, Deqing Yang, Jiaxin Yu … Yanghua XiaoACL · Fudan University
  15. 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
    PDF ↗
  16. 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
  17. 2020
    Rational LAMOL: A Rationale-based Lifelong Learning FrameworkKasidis Kanwatchara, Thanapapas Horsuwan, Piyawat Lertvittayakumjorn … Peerapon VateekulACL · Chulalongkorn University · Imperial College London
  18. 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
  19. 2020
    Selective Forgetting of Deep Networks at a Finer Level than SamplesTomohiro Hayase, Suguru Yasutomi, Takashi KatoharXiv
    PDF ↗
  20. 2020
  21. 2020
    Entropy-based Sample Selection for Online Continual LearningFelix Wiewel, Bin YangEuropean Signal Processing Conference (EUSIPCO) · University of Stuttgart
  22. 2020
    Consequences of Slow Neural Dynamics for Incremental LearningShima Rahimi Moghaddam, Fanjun Bu, Christopher J. HoneyarXiv
    PDF ↗
  23. 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
  24. 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)
  25. 2020
    Pseudo-Rehearsal: Achieving Deep Reinforcement Learning without Catastrophic ForgettingCraig Atkinson, Brendan McCane, Lech Szymanski, Anthony RobinsNeurocomputing · University of Otago
    PDF ↗
  26. 2020
    Association: Remind Your GAN not to ForgetYi Gu, Jie Li, Yuting Gao … Zhang, ZiruiarXiv
    PDF ↗
  27. 2020
    Enhancing network modularity to mitigate catastrophic forgettingLu Chen, Masayuki MurataApplied Network Science · Kyoto Institute of Technology · Osaka Health Science University · +1
  28. 2020
    Consolidation via Policy Information Regularization in Deep RL for Multi-Agent GamesTyler Malloy, Tim Klinger, Miao Liu … Chris R. SimsarXiv
    PDF ↗
  29. 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
  30. 2020PDF ↗
  31. 2020
    Continual Learning with Deep Artificial NeuronsBlake Camp, Jaya Krishna Mandivarapu, Rolando EstradaarXiv · Georgia State University
    PDF ↗
  32. 2020
    Incremental Learning Using a Grow-and-Prune Paradigm With Efficient Neural NetworksXiaoliang Dai, Hongxu Yin, Niraj K. JhaIEEE Transactions · Princeton University
    PDF ↗
  33. 2020
    Lifelong learning of interpretable image representationsFei Ye, Adrian G. BorşICIP · University of York
  34. 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
  35. 2020
    A Novel Layer Sharing-based Incremental Learning via Bayesian OptimizationYoonsik Choe, Bomi Kim, Taehyeon KimApplied Sciences · Yonsei University
  36. 2020
    Class incremental learning via Multi-hinge distillationQianhe Lin, Yuanlong Yu, Zhiyong HuangChinese Automation Congress (CAC) · Fuzhou University · Zhejiang Lab
  37. 2020
    Fast Adapting Without Forgetting for Face RecognitionHao Liu, Xiangyu Zhu, Zhen Lei … Stan Z. LiIEEE TCSVT · Chinese Academy of Sciences · Beijing Academy of Artificial Intelligence · +3
  38. 2020
    Embracing Change: Continual Learning in Deep Neural Networks.Raia Hadsell, Dushyant Rao, Andrei A. Rusu, Razvan PascanuTrends in Cognitive Sciences · Google DeepMind (United Kingdom) · Google (United Kingdom)
  39. 2020
    Meta-Learning for Natural Language Understanding under Continual Learning FrameworkJiacheng Wang, Yong Fan, Duo Jiang, Shiqing LiarXiv · Supélec · University of Applied Sciences and Arts of Southern Switzerland · +1
    PDF ↗
  40. 2020
    Learn-Prune-Share for Lifelong LearningZifeng Wang, Tong Jian, Kaushik Chowdhury … Stratis IoannidisICDM · Northeastern University
    PDF ↗
  41. 2020
    CLIFER: Continual Learning with Imagination for Facial Expression RecognitionNikhil Churamani, Hatice GüneşIEEE International Conference on Automatic Face and Gestu… · University of Cambridge
  42. 2020
    Lifelong Learning Without a Task OracleAmanda Rios, Laurent IttiIEEE 32nd International Conference on Tools with Artifici… · University of Southern California
    PDF ↗
  43. 2020
    An Error-Correcting Output Code Framework for Lifelong Learning without a TeacherShen-Shyang Ho, Mathew Marchiano, Scott Zockoll, Hiêú D. NguyêñIEEE 32nd International Conference on Tools with Artifici… · Rowan University
  44. 2020
    SEM: Adaptive Staged Experience Access Mechanism for Reinforcement LearningJianshu Wang, Xinzhi Wang, Xiangfeng Luo … Yang LiIEEE 32nd International Conference on Tools with Artifici… · Shanghai University of Engineering Science
  45. 2020
    Neural inhibition for continual learning and memoryHelen C. BarronCurrent Opinion in Neurobiology · John Radcliffe Hospital · University of Oxford · +3
  46. 2020
    A Study on Efficiency in Continual Learning Inspired by Human LearningPhilip Ball, Yingzhen Li, Angus Lamb, Cheng ZhangarXiv
    PDF ↗
  47. 2020
    Continual Learning in Automatic Speech RecognitionSamik Sadhu, Hynek HeřmanskýInterspeech
  48. 2020
    SERIL: Noise Adaptive Speech Enhancement using Regularization-based Incremental LearningChi-Chang Lee, Yu-Chen Lin, Hsuan-Tien Lin … Yu TsaoInterspeech
    PDF ↗
  49. 2020
    Latent Replay for Real-Time Continual LearningLorenzo Pellegrini, Gabriele Graffieti, Vincenzo Lomonaco, Davide MaltoniIROS · University of Bologna
    PDF ↗
  50. 2020
    A Combinatorial Perspective on Transfer LearningJianan Wang, Eren Sezener, David Budden … Joel VenessNeurIPS · Google (United States)
    PDF ↗
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.