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.

352 papers of 4,574 · showing 1–50Sort Recent · Most cited
  1. 2021
    Recent Advances of Continual Learning in Computer Vision: An OverviewHaoxuan Qu, Hossein Rahmani, Li Xu … Jun LiuIET Computer Vision · Lancaster University · Singapore University of Technology and Design
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  2. 2021
    Continual Learning With Quasi-Newton MethodsSteven Vander Eeckt, Hugo Van hammeIEEE Access · KU Leuven
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  3. 2021
    Generative feature-driven image replay for continual learningKevin Thandiackal, Tiziano Portenier, Andrea Giovannini … Orçun GökselImage and Vision Computing · ETH Zurich · IBM Research - Zurich · +1
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  4. 2021
    Simultaneous Multi-View Object Recognition and Grasping in Open-Ended DomainsHamidreza Kasaei, Mohammadreza Kasaei, Georgios Tziafas … Remo SassoJournal of Intelligent & Robotic Systems · University of Groningen · University of Edinburgh
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  5. 2021
    Task-Specific Normalization for Continual Learning of Blind Image Quality ModelsWeixia Zhang, Kede Ma, Guangtao Zhai, Xiaokang YangTIP · Shanghai Jiao Tong University · City University of Hong Kong · +1
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  6. 2021
    Relational Experience Replay: Continual Learning by Adaptively Tuning Task-Wise RelationshipQuanziang Wang, Renzhen Wang, Yuexiang Li … Deyu MengIEEE Trans. Multimedia · Xi'an Jiaotong University · Tencent (China) · +1
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  7. 2021
    Tuned Compositional Feature Replays for Efficient Stream LearningMorgan B. Talbot, Rushikesh Zawar, Rohil Badkundri … Gabriel KreimanTNNLS · Boston Children's Hospital · Harvard–MIT Division of Health Sciences and Technology · +6
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  8. 2021
    Continual Learning: Fast and SlowQuang Pham, Chenghao Liu, Steven C. H. HoiTPAMI · Institute for Infocomm Research · Singapore Management University
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  9. 2021
    Continual Learning of Generative Models With Limited Data: From Wasserstein-1 Barycenter to Adaptive CoalescenceMehmet Dedeoğlu, Sen Lin, Zhaofeng Zhang, Junshan ZhangTNNLS · Arizona State University · The Ohio State University · +1
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  10. 2021
    Prototype-Guided Memory Replay for Continual LearningStella Ho, Ming Liu, Lan Du … Yong XiangTNNLS · Deakin University · Monash University · +1
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  11. 2021
    RMM: Reinforced Memory Management for Class-Incremental LearningYaoyao Liu, Bernt Schiele, Qianru SunNeurIPS
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  12. 2021PDF ↗
  13. 2021
    Embodied Learning for Lifelong Visual PerceptionDavid Nilsson, Aleksis Pirinen, Erik Gärtner, Cristian SminchisescuarXiv
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  14. 2021
    Generative Kernel Continual learningMohammad Mahdi Derakhshani, Xiantong Zhen, Ling Shao, Cees G. M. SnoekarXiv
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  15. 2021
    DILF-EN framework for Class-Incremental LearningMohammed Asad Karim, Indu Joshi, Pratik Mazumder, Pravendra SingharXiv
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  16. 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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  17. 2021PDF ↗
  18. 2021
    Imbal-OL: Online Machine Learning from Imbalanced Data Streams in Real-world IoTBharath Sudharsan, John G. Breslin, Muhammad Intizar AliIEEE International Conference on Big Data (Big Data) · Ollscoil na Gaillimhe – University of Galway · Dublin City University
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  19. 2021PDF ↗
  20. 2021
    Incremental Learning for End-to-End Automatic Speech RecognitionLi Fu, Xiaoxiao Li, Libo Zi … Bowen ZhouIEEE Automatic Speech Recognition and Understanding Works… · Jingdong (China)
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  21. 2021
    Improving Vision Transformers for Incremental LearningPei Yu, Yinpeng Chen, Ying Jin, Zicheng LiuarXiv
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  22. 2021
    Gradient-matching coresets for continual learningLukas Balles, Giovanni Zappella, Cédric ArchambeauarXiv
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  23. 2021PDF ↗
  24. 2021
    Overcome Anterograde Forgetting with Cycled Memory NetworksJian Peng, Dingqi Ye, Bo Tang … Haifeng LiarXiv
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  25. 2021
    Continual Learning for Multivariate Time Series Tasks with Variable Input DimensionsVibhor Gupta, Jyoti Narwariya, Pankaj Malhotra … Gautam ShroffICDM
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  26. 2021PDF ↗
  27. 2021
    CVPR 2020 Continual Learning in Computer Vision Competition: Approaches, Results, Current Challenges and Future DirectionsVincenzo Lomonaco, Lorenzo Pellegrini, Pau Rodríguez … Davide MaltoniArtificial Intelligence · University of Bologna · Mila - Quebec Artificial Intelligence Institute · +7
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  28. 2021
    Reviewing continual learning from the perspective of human-level intelligenceYifan Chang, Wenbo Li, Jian Peng … Haifeng LiarXiv
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  29. 2021
    Learning by Active Forgetting for Neural NetworksJian Peng, Xian Sun, Min Deng … Haifeng LiarXiv · Central South University
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  30. 2021
    Defeating Catastrophic Forgetting via Enhanced Orthogonal Weights ModificationYanni Li, Bing Liu, Kaicheng Yao … Jiangtao CuiarXiv
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  31. 2021
    Lifelong Reinforcement Learning with Temporal Logic Formulas and Reward MachinesXuejing Zheng, Chao Yu, Chen Chen … Hankz Hankui ZhuoarXiv
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  32. 2021
    Self-Supervised Class Incremental LearningZixuan Ni, Siliang Tang, Yueting ZhuangarXiv
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  33. 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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  34. 2021
    Target Layer Regularization for Continual Learning Using Cramer-Wold GeneratorMarcin Mazur, Łukasz Pustelnik, Szymon Knop … Przemysław SpurekarXiv
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  35. 2021
    Kronecker Factorization for Preventing Catastrophic Forgetting in Large-scale Medical Entity LinkingDenis Jered McInerney, Luyang Kong, Kristjan Arumae … Parminder BhatiaarXiv · Universidad del Noreste · Amazon (Germany)
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  36. 2021PDF ↗
  37. 2021
    One Pass ImageNetHuiyi Hu, Ang Li, Daniele Calandriello, Dilan GörürarXiv
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  38. 2021
    A Meta-Learned Neuron model for Continual LearningRodrigue SiryarXiv · Normandie Université · Université de Caen Normandie
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  39. 2021
    Variance Guided Continual Learning in a Convolutional Neural Network Gaussian Process Single Classifier Approach for Multiple Tasks in Noisy ImagesMahed Javed, Lyudmila Mihaylova, Nidhal BouaynayaInformation Fusion · University of Sheffield · Rowan University
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  40. 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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  41. 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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  42. 2021
    Learning where to learn: Gradient sparsity in meta and continual learningJohannes von Oswald, Dominic Zhao, Seijin Kobayashi … João SacramentoNeurIPS
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  43. 2021PDF ↗
  44. 2021PDF ↗
  45. 2021
    Exploring System Performance of Continual Learning for Mobile and Embedded Sensing ApplicationsYoung D. Kwon, Jagmohan Chauhan, Abhishek Kumar … Cecilia MascoloTyöväentutkimus Vuosikirja · University of Cambridge · University of Southampton
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  46. 2021
    Mixture-of-Variational-Experts for Continual LearningHeinke Hihn, Daniel BraunarXiv · Universität Ulm
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  47. 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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  48. 2021
    Center Loss Regularization for Continual LearningKaustubh Olpadkar, Ekta GavasarXiv
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  49. 2021
    A TinyML Platform for On-Device Continual Learning With Quantized Latent ReplaysLeonardo Ravaglia, Manuele Rusci, Davide Nadalini … Luca BeniniIEEE Journal on Emerging and Selected Topics in Circuits… · University of Bologna · University of Modena and Reggio Emilia · +1
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  50. 2021
    Continual Learning in Multilingual NMT via Language-Specific EmbeddingsAlexandre BérardConference on Machine Translation
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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.