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.

793 papers of 4,574 · showing 551–600Sort Recent · Most cited
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  3. 2024
    ECIL-MU: Embedding Based Class Incremental Learning and Machine UnlearningZhiwei Zuo, Zhuo Tang, Bin Wang … Anwitaman DattaICASSP · Hunan University · Nanyang Technological University
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  4. 2024
    Class-Wise Buffer Management for Incremental Object Detection: An Effective Buffer Training StrategyJunsu Kim, Sumin Hong, Chanwoo Kim … Seungryul BaekICASSP · Ulsan National Institute of Science and Technology · Seoul National University of Science and Technology · +3
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  5. 2024
    INCPrompt: Task-Aware Incremental Prompting for Rehearsal-Free Class-Incremental LearningZhiyuan Wang, Xiaoyang Qu, Jing Xiao … Jianzong WangICASSP · Tsinghua–Berkeley Shenzhen Institute · Shenzhen Technology University · +3
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  7. 2024
    P2DT: Mitigating Forgetting in Task-Incremental Learning with Progressive Prompt Decision TransformerZhiyuan Wang, Xiaoyang Qu, Jing Xiao … Jianzong WangICASSP · Tsinghua–Berkeley Shenzhen Institute · Shenzhen Technology University · +3
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  8. 2024
    Generalizable Two-Branch Framework for Image Class-Incremental LearningChao Wu, Xiaobin Chang, Ruixuan WangICASSP · Sun Yat-sen University
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  9. 2024
    Learning a Low-Rank Feature Representation: Achieving Better Trade-Off Between Stability and Plasticity in Continual LearningZhenrong Liu, Yang Li, Yi Gong, Yik‐Chung WuICASSP · Southern University of Science and Technology · University of Hong Kong · +1
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  10. 2024
    FusDom: Combining in-Domain and Out-of-Domain Knowledge for Continuous Self-Supervised LearningAshish Seth, Sreyan Ghosh, S. Umesh, Dinesh ManochaICASSP · Indian Institute of Technology Madras · University of Maryland, College Park
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    Function-space Parameterization of Neural Networks for Sequential LearningAidan Scannell, Riccardo Mereu, Paul E. Chang … Arno SolinICLR
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  14. 2024
    Towards Robustness and Diversity: Continual Learning in Dialog Generation with Text-Mixup and Batch Nuclear-Norm MaximizationZihan Wang, Jiayu Xiao, Mengxian Li … Shuang-Yong SongIEEE International Joint Conference on Neural Network
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  15. 2024
    Few-Shot Class Incremental Learning with Attention-Aware Self-Adaptive PromptChenxi Liu, Zhenyi Wang, Tianyi Xiong … Heng HuangECCV
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    Simple and Scalable Strategies to Continually Pre-train Large Language ModelsAdam Ibrahim, Benjamin Therien, Kshitij Gupta … Irina RishTMLR
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  21. 2024
    Self-Regulated Neurogenesis for Online Data-Incremental LearningMurat Onur Yildirim, Elif Ceren Gok Yildirim, Decebal Constantin Mocanu, Joaquin VanschorenarXiv
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  22. 2024
    Continual All-in-One Adverse Weather Removal With Knowledge Replay on a Unified Network StructureDe Cheng, Yanling Ji, Dong Gong … Dingwen ZhangIEEE Trans. Multimedia
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  24. 2024
    12 mJ Per Class On-Device Online Few-Shot Class-Incremental LearningYoga Esa Wibowo, Cristian Cioflan, Thorir Mar Ingolfsson … Luca BeniniDesign, Automation and Test in Europe
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  25. 2024
    Premonition: Using Generative Models to Preempt Future Data Changes in Continual LearningMark D. McDonnell, Dong Gong, Ehsan Abbasnejad, Anton van den HengelarXiv
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  27. 2024
    Continual Learning by Three-Phase ConsolidationDavide Maltoni, Lorenzo PellegriniarXiv
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  28. 2024
    Semantic Residual Prompts for Continual LearningMartin Menabue, Emanuele Frascaroli, Matteo Boschini … Simone CalderaraECCV
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  32. 2024
    Adaptive Hyperparameter Optimization for Continual Learning ScenariosRudy Semola, Julio Hurtado, Vincenzo Lomonaco, Davide BacciuCLAI Unconf
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  33. 2024
    DiffClass: Diffusion-Based Class Incremental LearningZichong Meng, Zhang Jie, Changdi Yang … Yanzhi WAngECCV
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  35. 2024
    Mixture-of-LoRAs: An Efficient Multitask Tuning Method for Large Language ModelsWenfeng Feng, Chuzhan Hao, Yuewei Zhang … Hao WangInternational Conference on Language Resources and Evalua…
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  36. 2024
    GUIDE: Guidance-based Incremental Learning with Diffusion ModelsBartosz Cywiński, Kamil Rafał Deja, T. P. Trzcinski … Łukasz KucińskiEuropean Conference on Artificial Intelligence
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  38. 2024
    DP-CRE: Continual Relation Extraction via Decoupled Contrastive Learning and Memory Structure PreservationHuang, Mengyi, Meng Xiao, Ludi Wang, Yi DuInternational Conference on Language Resources and Evalua…
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  39. 2024PDF ↗
  40. 2024
    Open-world Machine Learning: A Review and New OutlooksFei Zhu, Shijie Ma, Zhen Cheng … Liu, Cheng-LinarXiv
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  41. 2024
    Zero-shot Generalizable Incremental Learning for Vision-Language Object DetectionJieren Deng, Haojian Zhang, Kun Ding … Yunkuan WangNeurIPS
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  42. 2024
    Transformers for Supervised Online Continual LearningJörg Bornschein, Yazhe Li, Amal Rannen-TrikiarXiv
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  45. 2024
    Disentangling the Causes of Plasticity Loss in Neural NetworksClare Lyle, Zeyu Zheng, Khimya Khetarpal … Will DabneyCoLLAs
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  48. 2024
    A Comprehensive Survey of Continual Learning: Theory, Method and ApplicationLiyuan Wang, Xingxing Zhang, Hang Su, Jun ZhuTPAMI · Tsinghua University
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  50. 2024
    Photonic neuromorphic architecture for tens-of-task lifelong learningYuan Cheng, Jianing Zhang, Tiankuang Zhou … Lu FangLight: Science & Applications
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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.