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.

6 papers of 6,984Sort Recent · Most cited
  1. 2023
    Perpetual Humanoid Control for Real-time Simulated AvatarsZhengyi Luo, Jinkun Cao, Alexander Winkler … Weipeng XuICCV · META Health · Carnegie Mellon University
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  2. 2023
    Audio-Visual Class-Incremental LearningWeiguo Pian, Shentong Mo, Yunhui Guo, Yapeng TianICCV · The University of Texas at Dallas · Carnegie Mellon University
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  3. 2023
    Class-Incremental Grouping Network for Continual Audio-Visual LearningShentong Mo, Weiguo Pian, Yapeng TianICCV · Carnegie Mellon University
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  4. 2023
    BioSLAM: A Bioinspired Lifelong Memory System for General Place RecognitionPeng Yin, Abulikemu Abuduweili, Shiqi Zhao … Sebastian SchererIEEE Transactions · City University of Hong Kong · Carnegie Mellon University
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  5. 2023
    Federated Continual Learning for Socially Aware RoboticsLuke Guerdan, Hatice GüneşIEEE International Conference on Robot and Human Interact… · Carnegie Mellon University · University of Cambridge
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  6. 2023
    Leveraging joint incremental learning objective with data ensemble for class incremental learningPratik Mazumder, Mohammed Asad Karim, Indu Joshi, Pravendra SinghNeural Networks · Indian Institute of Technology Jodhpur · Carnegie Mellon University · +2
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.