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.

4,574 papers · showing 4401–4450Sort Recent · Most cited
  1. 2019
    Incremental Reading for Question AnsweringSamira Abnar, Tania Bedrax-Weiss, Tom Kwiatkowski, William W. CohenarXiv · University of Amsterdam · Google (United States)
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  2. 2019
    Sentence Embedding Alignment for Lifelong Relation ExtractionHongfei Wang, Wenhan Xiong, Mo Yu … William Yang WangNAACL · University of California, Santa Barbara
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  3. 2019
    An Embarrassingly Simple Approach for Transfer Learning from Pretrained Language ModelsAlexandra Chronopoulou, Christos Baziotis, Alexandros PotamianosNAACL · National Technical University of Athens
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  4. 2019
    DeeSIL: Deep-Shallow Incremental LearningEden Belouadah, Adrian PopescuSpringer LNCS · Commissariat à l'Énergie Atomique et aux Énergies Alternatives · Laboratoire d'Intégration des Systèmes et des Technologies
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  5. 2019
    Revisiting Distillation and Incremental Classifier LearningKhurram Javed, Faisal ShafaitSpringer LNCS · National University of Sciences and Technology
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  6. 2019
    An Incremental Construction of Deep Neuro Fuzzy System for Continual Learning of Nonstationary Data StreamsMahardhika Pratama, Witold Pedrycz, Geoffrey I. WebbIEEE Transactions · Nanyang Technological University · University of Alberta · +1
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  7. 2019
    Psycholinguistics Meets Continual Learning: Measuring Catastrophic Forgetting in Visual Question AnsweringClaudio Greco, Barbara Plank, Raquel Fernández, Raffaella BernardiACL · University of Trento · IT University of Copenhagen · +1
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  8. 2019
    Adding New Tasks to a Single Network with Weight Trasformations using Binary MasksMassimiliano Mancini, Elisa Ricci, Barbara Caputo, Samuel Rota BulòSpringer LNCS · Fondazione Bruno Kessler · Sapienza University of Rome · +2
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  9. 2019
    Continual and Multi-Task Architecture SearchRamakanth Pasunuru, Mohit BansalACL · University of North Carolina at Chapel Hill · University of North Carolina Health Care
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  10. 2019
    Continual Learning for Sentence Representations Using ConceptorsTianlin Liu, Lyle Ungar, João SedocNAACL · Constructor University · University of Pennsylvania
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  11. 2019
    Marginal Replay vs Conditional Replay for Continual LearningTimothée Lesort, Alexander Gepperth, Andrei Stoian, David FilliatSpringer LNCS · École Nationale Supérieure de Techniques Avancées · Thales (France) · +1
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  12. 2019
    A Progressive Model to Enable Continual Learning for Semantic Slot FillingYilin Shen, Xiangyu Zeng, Hongxia JinEMNLP · Samsung (South Korea) · Samsung (United States) · +1
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  13. 2019
    Meta-Learning Improves Lifelong Relation ExtractionAbiola Obamuyide, Andreas VlachosWorkshop on Representation Learning for NLP (RepL4NLP-2019) · University of Cambridge · PRG S&Tech (South Korea) · +1
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  14. 2019
    Continual Learning with Deep ArchitecturesVincenzo LomonacoAMS Dottorato Institutional Doctoral Theses Repository (U…
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  15. 2019
    Incremental Learning from Scratch for Task-Oriented Dialogue SystemsWeikang Wang, Jiajun Zhang, Qian Li … Zhifei LiACL · Shandong Institute of Automation · Institute of Automation · +3
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  16. 2019
    Continuous Learning for Large-scale Personalized Domain ClassificationHan Li, Jihwan Lee, Sidharth Mudgal … Young‐Bum KimNAACL · University of Wisconsin–Madison · Amazon (Germany)
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  17. 2019
    Lifelong Learning Starting From ZeroClaes Strannegård, Herman Carlström, Niklas Engsner … Morteza Haghir ChehreghaniSpringer LNCS · Chalmers University of Technology
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  18. 2019
    Transfer Learning with Sparse Associative MemoriesQuentin Jodelet, Vincent Gripon, Masafumi HagiwaraSpringer LNCS · Keio University · IMT Atlantique
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  19. 2018
    Self-organizing maps for storage and transfer of knowledge in reinforcement learningThommen George Karimpanal, Roland BouffanaisAdaptive Behavior · Singapore University of Technology and Design
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  20. 2019
    Deep Online Learning via Meta-Learning: Continual Adaptation for Model-Based RLAnusha Nagabandi, Chelsea Finn, Sergey LevineICLR · University of California, Berkeley
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  21. 2018
    Continual Match Based Training in Pommerman: Technical ReportPeng Peng, Liang Pang, Yufeng Yuan, Chao GaoarXiv
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  22. 2019
    An Empirical Study of Example Forgetting during Deep Neural Network LearningMariya Toneva, Alessandro Sordoni, Rémi Tachet des Combes … Geoffrey J. GordonICLR · Carnegie Mellon University · Microsoft (United States) · +1
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  23. 2018PDF ↗
  24. 2018
    Transfer Incremental Learning using Data AugmentationGhouthi Boukli Hacene, Vincent Gripon, Nicolas Farrugia … Michel JézéquelApplied Sciences · Université de Bretagne Occidentale · Laboratoire des Sciences et Techniques de l’Information de la Communication et de la Connaissance · +2
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  25. 2018
    Overcoming Catastrophic Forgetting by Soft Parameter PruningJian Peng, Hao, Jiang, Zhuo Li … Haifeng LiarXiv
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  26. 2018
    Few-Shot Self Reminder to Overcome Catastrophic ForgettingJunfeng Wen, Yanshuai Cao, Ruitong HuangarXiv
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  27. 2019
    Efficient Lifelong Learning with A-GEMArslan Chaudhry, Marc’Aurelio Ranzato, Marcus Rohrbach, Mohamed ElhoseinyICLR
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  28. 2017
    Incremental Learning Through Deep AdaptationAmir Rosenfeld, John K. TsotsosTPAMI · York University
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  29. 2018PDF ↗
  30. 2019
    Experience Replay for Continual LearningDavid Rolnick, Arun Ahuja, Jonathan Schwarz … Greg WayneNeurIPS · California University of Pennsylvania · University of Pennsylvania · +1
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  31. 2018
    Lifelong Learning of Spatiotemporal Representations With Dual-Memory Recurrent Self-OrganizationGerman I. Parisi, Jun Tani, Cornelius Weber, Stefan WermterFrontiers · Universität Hamburg · Okinawa Institute of Science and Technology Graduate University
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  32. 2018
    Partitioned Variational Inference: A unified framework encompassing federated and continual learningThang D. Bui, Cuong V. Nguyen, Siddharth Swaroop, Richard E. TurnerarXiv
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  33. 2018
    Generative Adversarial Network Training is a Continual Learning ProblemKevin J Liang, Chunyuan Li, Guoyin Wang, Lawrence CarinarXiv
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  34. 2018
    On Training Recurrent Neural Networks for Lifelong LearningShagun Sodhani, Sarath Chandar, Yoshua BengioNeural Computation
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  35. 2018
    The Barbados 2018 List of Open Issues in Continual LearningTom Schaul, Hado van Hasselt, Joseph Modayil … Doina PrecuparXiv
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  36. 2018
    On the role of neurogenesis in overcoming catastrophic forgettingGerman I. Parisi, Xu Ji, Stefan WermterarXiv
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  37. 2018
    Closed-Loop GAN for continual LearningAmanda Rios, Laurent IttiarXiv · University of Southern California · California Southern University
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  38. 2018
    Don't forget, there is more than forgetting: new metrics for Continual LearningNatalia Díaz-Rodríguez, Vincenzo Lomonaco, David Filliat, Davide MaltoniarXiv · Laboratoire d’Informatique et Systèmes · University of Bologna
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  39. 2018
    Re-evaluating Continual Learning Scenarios: A Categorization and Case for Strong BaselinesYen-Chang Hsu, Yen‐Cheng Liu, Ramasamy, Anita, Kira, ZsoltarXiv · Georgia Institute of Technology
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  40. 2019
    Learning to Learn without Forgetting By Maximizing Transfer and Minimizing InterferenceMatthew Riemer, Ignacio Cases, Robert Ajemian … Gerald TesauroICLR · IBM (United States) · Stanford University · +2
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  41. 2018
    Self-Supervised GAN to Counter ForgettingTing Chen, Xiaohua Zhai, Neil HoulsbyarXiv
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  42. 2018
    Continual Classification Learning Using Generative ModelsFrantzeska Lavda, Jason Ramapuram, Magda Gregorová, Alexandros KalousisNeurIPS
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  43. 2018
    Alleviating catastrophic forgetting using context-dependent gating and synaptic stabilizationNicolas Y. Masse, Gregory D. Grant, David J. FreedmanPNAS · University of Chicago
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  44. 2018
    Continual State Representation Learning for Reinforcement Learning using Generative ReplayHugo Caselles-Dupré, M. Ortíz, David FilliatarXiv · Laboratoire d’Informatique et Systèmes · SoftBank Robotics (France)
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  45. 2018
    A Neural Model of Schemas and Memory ConsolidationTiffany Hwu, Jeffrey L. KrichmarbioRxiv · University of California, Irvine
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  46. 2018
    An Ensemble with Shared Representations Based on Convolutional Networks for Continually Learning Facial ExpressionsHenrique Siqueira, Pablo Barros, Sven Magg, Stefan WermterIROS · Universität Hamburg · Hamburg University of Technology
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  47. 2018
    Accelerating Learning in Constructive Predictive Frameworks with the Successor RepresentationCraig Sherstan, Marlos C. Machado, Patrick M. PilarskiIROS · University of Alberta
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  48. 2018
    Generative replay with feedback connections as a general strategy for continual learningGido M. van de Ven, Andreas S. ToliasarXiv · Baylor College of Medicine
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  49. 2018
    Autonomous Deep Learning: Incremental Learning of Denoising Autoencoder for Evolving Data StreamsMahardhika Pratama, Andri Ashfahani, Yew-Soon Ong … Edwin LughoferarXiv
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  50. 2018PDF ↗
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.