Related work

The foundational work on continual learning, 1988 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

958 papers of 6,984 · showing 801–850Sort Recent · Most cited
  1. 2023
    Pretrained back propagation based adaptive resonance theory network for adaptive learningCaixia Zhang, Cong Jiang, Qingyang XuJournal of Algorithms & Computational Technology · Weihai Chest Hospital · Shandong University
  2. 2023
    Recent Advances in Class-Incremental LearningDejie Yang, Minghang Zheng, Weishuai Wang … Yang LiuSpringer LNCS · Peking University
  3. 2023
    Toward a More Neurally Plausible Neural Network Model of Latent Cause InferenceQihong Lu, Tan Tien Nguyen, Uri Hasson … Kenneth A. NormanConference on Cognitive Computational Neuroscience · Princeton University · Washington University in St. Louis · +1
  4. 2023
    Class Incremental Learning with Important and Diverse MemoryLi Mei, Zeyu Yan, Changsheng LiSpringer LNCS · Beijing Institute of Technology
  5. 2023
    Class-Incremental Learning Based on Anomaly DetectionLijuan Zhang, Xiaokang Yang, Kai Zhang … Dongming LiIEEE Access · Changchun University of Technology · Jilin University of Finance and Economics · +1
    PDF ↗
  6. 2023
    ConnectomeNet: A Unified Deep Neural Network Modeling Framework for Multi-Task LearningHeechul Lim, Kang-Wook Chon, Min‐Soo KimIEEE Access · Daegu Gyeongbuk Institute of Science and Technology · Korea University of Technology and Education · +1
    PDF ↗
  7. 2023
    Employing Convolutional Neural Networks for Continual LearningMarcin Jasiński, Michał WoźniakSpringer LNCS · Wrocław University of Science and Technology · AGH University of Krakow
  8. 2023
    FETCH: A Memory-Efficient Replay Approach for Continual Learning in Image ClassificationMarkus Weißflog, Peter Protzel, Peer NeubertSpringer LNCS · Chemnitz University of Technology · Koblenz University of Applied Sciences · +1
    PDF ↗
  9. 2023
    Filter Bank Networks for Few-Shot Class-Incremental LearningYanzhao Zhou, Binghao Liu, Yiran Liu, Jianbin JiaoComputer Modeling in Engineering & Sciences · University of Chinese Academy of Sciences
    PDF ↗
  10. 2023
    Human Inspired Progressive Alignment and Comparative Learning for Grounded Word AcquisitionYuwei Bao, Barrett Lattimer, Joyce ChaiACL · University of Michigan
    PDF ↗
  11. 2023
    Machine Learning and Knowledge Discovery in Databases: Research Track: European Conference, ECML PKDD 2023, Turin, Italy, September 18–22, 2023, Proceedings, Part VDanai Koutra, Claudia Plant, Manuel Gomez-Rodriguez … Francesco BonchiSpringer LNCS · University of Michigan · University of Vienna · +2
    PDF ↗
  12. 2023
    Overcoming Catastrophic Forgetting for Fine-Tuning Pre-trained GANsZeren Zhang, Xingjian Li, Hong Tao … Chengzhong XuSpringer LNCS · Peking University · Baidu (China) · +2
  13. 2023
    POSTER: Advancing Federated Edge Computing with Continual Learning for Secure and Efficient PerformanceChunlu Chen, Kevin I‐Kai Wang, Peng Li, Kouichi SakuraiSpringer LNCS · Kyushu University · University of Auckland · +1
  14. 2023
    Prototypical quadruplet for few-shot class incremental learningSanchar Palit, Biplab Banerjee, Subhasis ChaudhuriProcedia Computer Science · Indian Institute of Technology Bombay
    PDF ↗
  15. 2023
    Task-aware network: Mitigation of task-aware and task-free performance gap in online continual learningYong Woo Hong, Hyeran Byun, Sungho ParkNeurocomputing · Yonsei University
  16. 2023
    Using Flexible Memories to Reduce Catastrophic ForgettingWernsen Wong, Yun Sing Koh, Gillian DobbieSpringer LNCS · University of Auckland
  17. 2023
    CLeAR: Continual Learning on Algorithmic Reasoning for Human-like IntelligenceBong Gyun Kang, Hyungi Kim, Dahuin Jung, Sungroh YoonNeurIPS
  18. 2023
    Dynamic Memory-Based Continual Learning with Generating and ScreeningSiying Tao, Jinyang Huang, Xiang Zhang … Yu GuSpringer LNCS · Hefei University of Technology · University of Science and Technology of China · +1
  19. 2023
    Incrementally Learned Angular Representations for Few-Shot Class-Incremental LearningIn-Ug Yoon, Jong-Hwan KimIEEE Access · Korea Advanced Institute of Science and Technology
    PDF ↗
  20. 2023
    NeCa: Network Calibration for Class Incremental LearningZhenyao Zhang, Lijun ZhangSpringer LNCS · Nanjing University
  21. 2023
    On Representation-Level Forgetting in Class Incremental Learning: What's the Bottleneck?Zixuan Ni, Haizhou Shi, Longhui Wei … Siliang TangSocial Science Research Network · First Affiliated Hospital Zhejiang University · Zhejiang University
  22. 2023
    Towards Continual Reinforcement Learning for Quadruped RobotsGiovanni Minelli, Vassilis VassiliadesIMET
    PDF ↗
  23. 2023
    Class-Incremental Learning with Multiscale Distillation for Weakly Supervised Temporal Action LocalizationTianquan Chen, Bairong Li, Yusheng Tao … Yuesheng ZhuSpringer LNCS · Peking University
  24. 2023
    Continual Vocabularies to Tackle the Catastrophic Forgetting Problem in Machine TranslationSalvador Carrión, Francisco CasacubertaSpringer LNCS · Universitat Politècnica de València
  25. 2023
    Efficient Continual Learning in Reservoir NetworksPaul Okeahalam, Liang Zhou, Jorge Aurelio Menendez, Peter E. LathamConference on Cognitive Computational Neuroscience · University College London
  26. 2023
    Humans and Neural Networks Show Similar Patterns of Transfer and Interference in a Continual Learning TaskEleanor Holton, Lukas Braun, Jessica A. F. Thompson, Christopher SummerfieldConference on Cognitive Computational Neuroscience · University of Oxford
  27. 2023
  28. 2023
    Online class incremental learning for multi-pose point cloud targetsRun-jiang ZHANG, Jie-long GUO, Hui Yu … Xian WeiChinese Journal of Liquid Crystals and Displays
  29. 2023
    Rapid Learning Without Catastrophic Forgetting in Multiple Morris Water MazesRaymond Wang, Jaedong Hwang, Akhilan Boopathy, Ila FieteConference on Cognitive Computational Neuroscience · Massachusetts Institute of Technology
  30. 2023PDF ↗
  31. 2023
    Deep Class-Incremental Learning: A SurveyDa-Wei Zhou, Qiwen Wang, Zhi-Hong Qi … Ziwei LiuarXiv
  32. 2023
  33. 2023
  34. 2023
  35. 2023
    Online Bias Correction for Task-Free Continual LearningA. Chrysakis, Marie-Francine MoensICLR
  36. 2023
    Online Boundary-Free Continual Learning by Scheduled Data PriorHyun-woo Koh, M. Seo, Jihwan Bang … Jonghyun ChoiICLR
  37. 2023
  38. 2023
  39. 2023
    Real-Time Evaluation in Online Continual Learning: A New ParadigmYasir Ghunaim, Adel Bibi, K. Alhamoud … Bernard GhanemarXiv
  40. 2023
    Addressing Catastrophic Forgetting in Federated Class-Continual LearningJie Zhang, Chen Chen, Weiming Zhuang, Ling-Juan LvarXiv
  41. 2023
    COPF: Continual Learning Human Preference through Optimal Policy FittingHan Zhang, Lin Gui, Yuan-Zhao Zhai … Ruifeng XuarXiv
  42. 2023
  43. 2023
    Optimizing Mode Connectivity for Class Incremental LearningHaitao Wen, Haoyang Cheng, Heqian Qiu … Hongliang LiICML
  44. 2023
    Continual Learning of Language ModelsZixuan Ke, Yijia Shao, Haowei Lin … Bin LiuICLR
  45. 2023
  46. 2023
    Towards Causal Replay for Knowledge Rehearsal in Continual LearningNikhil Churamani, Jiaee Cheong, Sinan Kalkan, Hatice GunesAAAI
  47. 2023
  48. 2023
  49. 2023
    Continually learning representations at scaleAlexandre Galashov, Jovana Mitrovic, Dhruva Tirumala … Razvan PascanuCoLLAs
  50. 2023
    Improving Continual Learning by Accurate Gradient Reconstructions of the PastErik Daxberger, S. Swaroop, Kazuki Osawa … Mohammad Emtiyaz KhanTMLR
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. 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.