Related work

The foundational work on continual learning, 1959 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

868 papers of 11,817 · showing 101–150Sort Recent · Most cited
  1. 2021
    Multi-Domain Incremental Learning for Semantic SegmentationPrachi Garg, Rohit Saluja, Vineeth N Balasubramanian … C. V. JawaharWACV · Indian Institute of Technology Hyderabad · Indian Institute of Technology Delhi
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  2. 2021
    Preventing Catastrophic Forgetting and Distribution Mismatch in Knowledge Distillation via Synthetic DataKuluhan Binici, Nam Trung Pham, Tulika Mitra, Karianto LemanWACV · Agency for Science, Technology and Research · National University of Singapore · +1
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  3. 2021
    Unsupervised Continual Learning Via Pseudo LabelsJiangpeng He, Fengqing ZhuSpringer LNCS · Purdue University West Lafayette
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  4. 2021
    Incremental Learning for Multi-organ Segmentation with Partially Labeled DatasetsPengbo Liu, Xia Wang, Mengsi Fan … Shuchang ZhouSpringer LNCS · University of Science and Technology of China · Chinese Academy of Sciences · +4
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  5. 2021
    Online Continual Learning Via Candidates VotingJiangpeng He, Fengqing ZhuWACV · Purdue University West Lafayette
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  6. 2021
    Transfer Learning Gaussian Anomaly Detection by Fine-Tuning RepresentationsOliver Rippel, Arnav Chavan, Chucai Lei, Dorit MerhofICIP · RWTH Aachen University · Indian Institute of Technology Dhanbad
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  7. 2021
    Unsupervised Continual Learning via Self-Adaptive Deep Clustering ApproachMahardhika Pratama, Andri Ashfahani, Edwin LughoferSpringer LNCS · University of South Australia · Nanyang Technological University
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  8. 2021
    SPeCiaL: Self-Supervised Pretraining for Continual LearningLucas Caccia, Joëlle PineauSpringer LNCS · McGill University
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  9. 2021
    Dataset Knowledge Transfer for Class-Incremental Learning without MemoryHabib Slim, Eden Belouadah, Adrian Popescu, Darian M. OnchişWACV · Commissariat à l'Énergie Atomique et aux Énergies Alternatives · Laboratoire d'Intégration des Systèmes et des Technologies · +5
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  10. 2021
    Enhancing Natural Language Representation with Large-Scale Out-of-Domain CommonsenseWanyun Cui, Xingran ChenACL · Shanghai University of Finance and Economics
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  11. 2021
    Modular Networks Prevent Catastrophic Interference in Model-Based Multi-Task Reinforcement LearningRobin Schiewer, Laurenz WiskottSpringer LNCS · Ruhr University Bochum
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  12. 2021
    Evaluating Continual Learning Algorithms by Generating 3D Virtual EnvironmentsEnrico Meloni, Alessandro Betti, Lapo Faggi … Stefano MelacciSpringer LNCS · University of Siena · University of Florence
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  13. 2021
    Continual Learning with Neuron Activation ImportanceSohee Kim, Seungkyu LeeSpringer LNCS · Kyung Hee University
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  14. 2021
    Transfer and Continual Supervised Learning for Robotic Grasping Through Grasping FeaturesLuca Monorchio, Marco Capotondi, Mario Corsanici … Francesco PujaSpringer LNCS · Sapienza University of Rome
  15. 2021
    Discriminative Distillation to Reduce Class Confusion in Continual LearningChanghong Zhong, Zhiying Cui, Wei‐Shi Zheng … Ruixuan WangSpringer LNCS · Sun Yat-sen University · Key Laboratory of Guangdong Province
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  16. 2021
    Metric Learning with Distillation for Overcoming Catastrophic ForgettingPiaoyao Yu, Juanjuan He, Qilang Min, Qi ZhuSpringer CCIS · Wuhan University of Science and Technology
  17. 2021
    Regular Decision Processes for Grid WorldsNicky Lenaers, Martijn van OtterloSpringer CCIS · Open University of the Netherlands · Radboud University Nijmegen
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  18. 2021
    Self-supervised Novelty Detection for Continual Learning: A Gradient-Based Approach Boosted by Binary ClassificationJingbo Sun, Li Yang, Jiaxin Zhang … Yu CaoSpringer LNCS · Arizona State University · Oak Ridge National Laboratory · +1
  19. 2021
    The Role of Bio-Inspired Modularity in General LearningRachel A. StClair, William Edward Hahn, Elan BarenholtzSpringer LNCS · Florida Atlantic University
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  20. 2021
    Latent-Insensitive Autoencoders for Anomaly Detection and Class-Incremental LearningMuhammad S. Battikh, Artem LenskiyMathematics · Al-Azhar University · Australian National University
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  21. 2021PDF ↗
  22. 2021
    Continual Deep Learning through Unforgettable Past Practical ConvolutionMuhammad Rehan Naeem, M. Iqbal, Rashid AminJournal of information communication technologies and rob…
  23. 2021
    A Data-Adaptive Loss Function for Incomplete Data and Incremental Learning in Semantic Image SegmentationMinh H. Vu, Gabriella Norman, Tufve Nyholm, Tommy LofstedtIEEE TMI · Umeå University
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  24. 2021
    Reinforcement Learning-Based Dialogue Guided Event Extraction to Exploit Argument RelationsQian Li, Hao Peng, Jianxin Li … Zheng WangIEEE/ACM Transactions on Audio Speech and Language Proces… · Beijing Advanced Sciences and Innovation Center · Beihang University · +4
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  25. 2021PDF ↗
  26. 2021
    Embodied Learning for Lifelong Visual PerceptionDavid Nilsson, Aleksis Pirinen, Erik Gärtner, Cristian SminchisescuarXiv
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  27. 2021
    Generative Kernel Continual learningMohammad Mahdi Derakhshani, Xiantong Zhen, Ling Shao, Cees G. M. SnoekarXiv
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  28. 2021
    Root CT Segmentation Using Incremental Learning Methodology on Improved Multiple Resolution ImagesK. GeethaJournal of Innovative Image Processing · PSG INSTITUTE OF TECHNOLOGY AND APPLIED RESEARCH
  29. 2021
    DILF-EN framework for Class-Incremental LearningMohammed Asad Karim, Indu Joshi, Pratik Mazumder, Pravendra SingharXiv
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  30. 2021
  31. 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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  32. 2021
    Strategizing three forms of growthAuthors pendingStrategic Direction
  33. 2021
    Proving Theorems using Incremental Learning and Hindsight Experience ReplayEser Aygün, Laurent Orseau, Ankit Anand … Shibl MouradICML
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  34. 2021PDF ↗
  35. 2021
    Modular Dynamic Neural Network: A Continual Learning ArchitectureDaniel Z. Turner, Pedro J. S. Cardoso, João M. F. RodriguesApplied Sciences · University of Algarve
  36. 2021
    Toward durable representations for continual learningAlaa El Khatib, Fakhri KarrayAdvances in Computational Intelligence · University of Waterloo
  37. 2021
    An Empirical Investigation of the Role of Pre-training in Lifelong LearningSanket Vaibhav Mehta, Darshan Patil, Sarath Chandar, Emma StrubellJMLR
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  38. 2021PDF ↗
  39. 2021
    Continual Neural Network Model RetrainingXiaofeng Zhu, Diego KlabjanIEEE International Conference on Big Data (Big Data) · Microsoft (United States) · Northwestern University
  40. 2021PDF ↗
  41. 2021
    Modeling nuisance classifier towards class-incremental learning of crowd-sourced dataRamesh Ashok Tabib, T. Santoshkumar, Dikshit Hegde … Uma MudenagudiTwelfth Indian Conference on Computer Vision, Graphics an… · KLE Technological University
  42. 2021
    Continual Learning In Environments With Polynomial Mixing TimesM. Riemer, S. Raparthy, Ignacio Cases … I. RishNeurIPS
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  43. 2021
    Improving Vision Transformers for Incremental LearningPei Yu, Yinpeng Chen, Ying Jin, Zicheng LiuarXiv
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  44. 2021
    Lifelong Learning with Monolithic 3D Ferroelectric Ternary Content-Addressable MemorySoumya Dutta, Abhishek Khanna, Huacheng Ye … Suman DattaIEEE International Electron Devices Meeting (IEDM) · University of Notre Dame
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  47. 2021PDF ↗
  48. 2021
    Modeling the Background for Incremental and Weakly-Supervised Semantic SegmentationFabio Cermelli, Massimiliano Mancini, Samuel Rota Bulo … Barbara CaputoTPAMI · Politecnico di Torino · TH Bingen University of Applied Sciences · +3
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  49. 2021
    Gradient-matching coresets for continual learningLukas Balles, Giovanni Zappella, Cédric ArchambeauarXiv
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  50. 2021
    Tracking cell lineages in 3D by incremental deep learningKo Sugawara, Çağrı Çevrim, Michalis AverofeLife · École Normale Supérieure de Lyon · Centre National de la Recherche Scientifique · +1
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 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.