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.

18 papers of 6,984Sort Recent · Most cited
  1. 2025
    Federated Continual Learning for Monocular Depth Estimation in Dynamic Indoor EnvironmentsAllen-Jasmin Farcas, Hyun Joon Song, Radu MărculescuInternational Conference on Distributed Computing in Smar… · The University of Texas at Austin
  2. 2025
    Attack on Prompt: Backdoor Attack in Prompt-Based Continual LearningTrang M Nguyen, Anh Tran, Nhat HoAAAI · The University of Texas at Austin
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  3. 2025
    Online-LoRA: Task-Free Online Continual Learning via Low Rank AdaptationXiwen Wei, Guihong Li, Radu MarculescuWACV · The University of Texas at Austin
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  4. 2024
    Rapid context inference in a thalamocortical model using recurrent neural networksWei‐Long Zheng, Zhongxuan Wu, Ali Hummos … Michael M. HalassaNature Communications · Shanghai Jiao Tong University · Massachusetts Institute of Technology · +3
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  5. 2024
    LOTUS: Continual Imitation Learning for Robot Manipulation Through Unsupervised Skill DiscoveryWeikang Wan, Yifeng Zhu, Rutav Shah, Yuke ZhuICRA · The University of Texas at Austin
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  6. 2024
    A collective AI via lifelong learning and sharing at the edgeAndrea Soltoggio, Eseoghene Ben-Iwhiwhu, Vladimir Braverman … Soheil KolouriNature Machine Intelligence · Loughborough University · Rice University · +21
  7. 2023
    Data Augmented Flatness-aware Gradient Projection for Continual LearningEnneng Yang, Li Shen, Zhenyi Wang … Xingwei WangICCV · Northeastern University · Jingdong (China) · +2
  8. 2023
    Continual Learning for On-Device Speech Recognition Using Disentangled ConformersAnuj Diwan, Ching-Feng Yeh, Wei-Ning Hsu … Abdelrahman MohamedICASSP · The University of Texas at Austin
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  9. 2023
    A Domain-Agnostic Approach for Characterization of Lifelong Learning SystemsMegan M. Baker, Alexander New, Mario Aguilar-Simon … Gautam K. VallabhaNeural Networks · Johns Hopkins University Applied Physics Laboratory · Teledyne Technologies (United States) · +13
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  10. 2022
    Lifelong Adaptive Machine Learning for Sensor-Based Human Activity Recognition Using Prototypical NetworksRebecca Adaimi, Edison ThomazSensors · The University of Texas at Austin
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  11. 2022
    Multiband VAE: Latent Space Alignment for Knowledge Consolidation in Continual LearningKamil Rafał Deja, Paweł Wawrzyński, Wojciech Masarczyk … T. P. TrzcinskiIJCAI · Warsaw University of Technology · The University of Texas at Austin · +2
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  12. 2022
    Towards Lifelong Learning of Multilingual Text-to-Speech SynthesisMu Yang, Shaojin Ding, Tianlong Chen … Zhangyang WangICASSP · The University of Texas at Dallas · Texas A&M University · +2
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  13. 2019
    Unified Probabilistic Deep Continual Learning through Generative Replay and Open Set RecognitionMartin Mundt, Iuliia Pliushch, Sagnik Majumder … Visvanathan RameshJournal of Imaging · Goethe University Frankfurt · The University of Texas at Austin · +1
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  14. 2022
    Biological underpinnings for lifelong learning machinesDhireesha Kudithipudi, Mario Aguilar-Simon, Jonathan Babb … Hava T. SiegelmannNature Machine Intelligence · The University of Texas at San Antonio · Intelligent Systems Research (United States) · +24
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  15. 2021
    Wanderlust: Online Continual Object Detection in the Real WorldJianren Wang, Xin Wang, Yue Shang-Guan, Abhinav GuptaICCV · Carnegie Mellon University · Microsoft Research (United Kingdom) · +1
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  16. 2020
    Firefly Neural Architecture Descent: a General Approach for Growing Neural NetworksLemeng Wu, Bo Liu, Peter Stone, Qiang LiuNeurIPS · The University of Texas at Austin
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  17. 2021
    A Lifelong Learning Approach to Mobile Robot NavigationBo Liu, Xuesu Xiao, Peter StoneRA-L · The University of Texas at Austin · Sony Corporation (United States)
  18. 2020
    Lifelong NavigationBo Liu, Xuesu Xiao, Peter StonearXiv · The University of Texas at Austin
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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. 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.