Related work

The foundational work on continual learning, 1959 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

4 papers of 11,817Sort Recent · Most cited
  1. 2022
    BeGin: Extensive Benchmark Scenarios and an Easy-to-use Framework for Graph Continual LearningJihoon Ko, Shinhwan Kang, Taehyung Kwon … Kijung ShinACM Transactions · Korea Advanced Institute of Science and Technology · International Graduate School of English
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  2. 2022
    Data Poisoning Attack Aiming the Vulnerability of Continual LearningGyojin Han, Jaehyun Choi, Hyeong Gwon Hong, Junmo KimICIP · Korea Advanced Institute of Science and Technology · International Graduate School of English
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  3. 2022
    Bridging Images and Videos: A Simple Learning Framework for Large Vocabulary Video Object DetectionSanghyun Woo, Kwanyong Park, Seoung Wug Oh … Joon‐Young LeeSpringer LNCS · Korea Advanced Institute of Science and Technology · Adobe Systems (United States)
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  4. 2022
    Boosting Adapter Transfer Learning via Weak Parameter SharingJune Suk Choi, Chae-Gyun Lim, Ho‐Jin ChoiIEEE International Conference on Big Data and Smart Compu… · Korea Advanced Institute of Science and Technology
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 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.