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.

813 papers of 8,653 · showing 101–150Sort Recent · Most cited
  1. 2023
    Task Relation Distillation and Prototypical Pseudo Label for Incremental Named Entity RecognitionDuzhen Zhang, Hongliu Li, Wei Wei Cong … Xiuyi ChenCIKM · Baidu (China) · Hong Kong Polytechnic University · +3
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  2. 2023
    Incremental Graph Classification by Class Prototype Construction and AugmentationYixin Ren, Li Ke, Dong Li … Shuigeng ZhouCIKM · Fudan University · Alibaba Group (China)
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  3. 2023
    L2R: Lifelong Learning for First-stage Retrieval with Backward-Compatible RepresentationsYinqiong Cai, Keping Bi, Yixing Fan … Xueqi ChengCIKM · University of Chinese Academy of Sciences
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  4. 2023
    Look At Me, No Replay! SurpriseNet: Anomaly Detection Inspired Class Incremental LearningAnton Lee, Yaqian Zhang, Heitor Murilo Gomes … Bernhard PfahringerCIKM · Victoria University of Wellington · University of Waikato
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  5. 2023
    Towards a General Framework for Continual Learning with Pre-trainingLiyuan Wang, Jingyi Xie, Xingxing Zhang … Jun ZhuarXiv
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  6. 2023
    Continual Invariant Risk MinimizationFrancesco Alesiani, Shujian Yu, Mathias NiepertarXiv
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  7. 2023
    Learnware: small models do bigZhihua Zhou, Zhi-Hao TanInformation Sciences · Nanjing University
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  8. 2023PDF ↗
  9. 2023
    SCRL: Self-supervised Continual Reinforcement Learning for Domain AdaptationYuyang Fang, Bin Guo, Jiaqi Liu … Zhiwen YuInternational Conference on Artificial Intelligence of Th… · Northwestern Polytechnical University
  10. 2023PDF ↗
  11. 2023
    New Insights on Relieving Task-Recency Bias for Online Class Incremental LearningGuoqiang Liang, Zhaojie Chen, Zhaoqiang Chen … Yanning ZhangIEEE TCSVT · Northwestern Polytechnical University · Institute of Software
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  12. 2023
    Recasting Continual Learning as Sequence ModelingSoochan Lee, Jaehyeon Son, Gunhee KimNeurIPS
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  13. 2023
    Bayesian Flow Networks in Continual LearningMateusz Pyla, Kamil Rafał Deja, Bartłomiej Twardowski, T. P. TrzcinskiarXiv
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  14. 2023
    Enhancing Plasticity for First Session Adaptation Continual LearningImad Eddine Marouf, Subhankar Roy, Stéphane Lathuilière, Enzo TartaglionearXiv
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  15. 2023
    CLIN: A Continually Learning Language Agent for Rapid Task Adaptation and GeneralizationBodhisattwa Prasad Majumder, Bhavana Dalvi Mishra, Peter Jansen … Peter E. ClarkarXiv
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  16. 2023
    Prior-Free Continual Learning with Unlabeled Data in the WildTao Zhuo, Zhiyong Cheng, Hehe Fan, Mohan KankanhalliarXiv
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  17. 2023PDF ↗
  18. 2023
    Federated Class-Incremental Learning with PromptingXin Luo, Liang, Fang-Yi, Jiale Liu … Xin-Shun XuExpert Systems with Applications
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  19. 2023PDF ↗
  20. 2023
    Sub-network Discovery and Soft-masking for Continual Learning of Mixed TasksZixuan Ke, Bing Liu, Wenhan Xiong … Haoran LiEMNLP
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  21. 2023
    Incremental Object Detection with CLIPZiyue Huang, Yupeng He, Qingjie Liu, Yunhong WangarXiv
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  22. 2023PDF ↗
  23. 2023
    TriRE: A Multi-Mechanism Learning Paradigm for Continual Knowledge Retention and PromotionPreetha Vijayan, Prashant Bhat, Elahe Arani, Bahram ZonoozNeurIPS
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  24. 2023PDF ↗
  25. 2023
    TRACE: A Comprehensive Benchmark for Continual Learning in Large Language ModelsXiao Wang, Yuansen Zhang, Tianze Chen … Xuanjing HuangarXiv
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  26. 2023
    CoinSeg: Contrast Inter- and Intra- Class Representations for Incremental SegmentationZekang Zhang, Guangyu Gao, Jianbo Jiao … Yunchao WeiICCV
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  27. 2023
    Rationale-Enhanced Language Models are Better Continual Relation LearnersWeimin Xiong, Yifan Song, Peiyi Wang, Sujian LiEMNLP
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  28. 2023PDF ↗
  29. 2023
    Evaluating Differential Privacy in Federated Continual LearningJunyan Ouyang, Rui Han, Chi Harold LiuIEEE 98th Vehicular Technology Conference (VTC2023-Fall) · Beijing Institute of Technology
  30. 2023
    Prompt-augmented Temporal Point Process for Streaming Event SequenceSiqiao Xue, Yan Wang, Zhixuan Chu … Jun ZhouNeurIPS
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  31. 2023PDF ↗
  32. 2023PDF ↗
  33. 2023
    Continual Contrastive Spoken Language UnderstandingUmberto Cappellazzo, Enrico Fini, Muqiao Yang … Bhiksha RajACL
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  34. 2023
    ProtoNER: Few shot Incremental Learning for Named Entity Recognition using Prototypical NetworksRitesh Kumar, Saurabh Goyal, Ashish Verma, Vatche IsahagianBusiness Process Management Workshops
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  35. 2023
    Exploring Continual Learning and Self-learning for Historical Digit RecognitionAsma Kharrat, Fadoua Drira, Franck Lebourgeois, Christophe GarcíaInternational Conference on Cyberworlds (CW) · University of Sfax · Lyon 1 Université · +2
  36. 2023
    Class-Incremental Learning using Diffusion Model for Distillation and ReplayQuentin Jodelet, Xin Liu, Yin Jun Phua, Tsuyoshi MurataICCV · Tokyo Institute of Technology · National Institute of Advanced Industrial Science and Technology
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  37. 2023
    A Comprehensive Empirical Evaluation on Online Continual LearningAlbin Soutif--Cormerais, Antonio Carta, Andrea Cossu … Hamed HematiICCV · Computer Vision Center · University of Pisa · +2
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  38. 2023
    Multimodal Parameter-Efficient Few-Shot Class Incremental LearningMarco D’Alessandro, Alberto Valdés Alonso, Enrique Calabrés, Mikel GalarICCV · Universidad Pública de Navarra (UPNA) · Universidad de Navarra
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  39. 2023
    Adapt Your Teacher: Improving Knowledge Distillation for Exemplar-free Continual LearningFilip Szatkowski, Mateusz Pyla, Marcin Przewięźlikowski … T. P. TrzcinskiICCV · Warsaw University of Technology · Integrated Detector Electronics AS (Norway) · +5
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  40. 2023
    Continual Evidential Deep Learning for Out-of-Distribution DetectionEduardo Aguilar, Bogdan Raducanu, Petia Radeva, Joost van de WeijerICCV · Universidad Católica del Norte · Computer Vision Center
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  41. 2023
    Clustering-based Domain-Incremental LearningChristiaan Lamers, René Vidal, Nabil Belbachir … Paris V. GiampourasICCV · NORCE Research AS · University of Pennsylvania · +1
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  42. 2023
    Improving Replay Sample Selection and Storage for Less Forgetting in Continual LearningDaniel Brignac, Niels da Vitoria Lobo, Abhijit MahalanobisICCV · University of Arizona · University of Central Florida
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  43. 2023
    On the Effectiveness of LayerNorm Tuning for Continual Learning in Vision TransformersThomas De Min, Massimiliano Mancini, Karteek Alahari … Elisa RicciICCV · University of Trento · Institut polytechnique de Grenoble · +5
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  44. 2023
    TKIL: Tangent Kernel Optimization for Class Balanced Incremental LearningJinlin Xiang, Eli ShlizermanICCV · University of Washington · Seattle University
  45. 2023
    FedRCIL: Federated Knowledge Distillation for Representation based Contrastive Incremental LearningAthanasios Psaltis, Christos Chatzikonstantinou, Charalampos Z. Patrikakis, Petros DarasICCV · University of West Attica · Centre for Research and Technology Hellas
  46. 2023
    Selective Freezing for Efficient Continual LearningAmelia Sorrenti, Giovanni Bellitto, Federica Proietto Salanitri … Simone PalazzoICCV · University of Catania
  47. 2023
    Instant Continual Learning of Neural Radiance FieldsRyan Po, Zhengyang Dong, Alexander W. Bergman, Gordon WetzsteinICCV · Stanford University
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  48. 2023
  49. 2023PDF ↗
  50. 2023
    Looking through the past: better knowledge retention for generative replay in continual learningValeriya Khan, Sebastian Cygert, Bartłomiej Twardowski, T. P. TrzcinskiICCV · Integrated Detector Electronics AS (Norway) · Corporación Universitaria de Colombia Ideas · +4
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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. 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.