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.

6 papers of 11,817Sort Recent · Most cited
  1. 2024
    On Mitigating Stability-Plasticity Dilemma in CLIP-guided Image Morphing via Geodesic Distillation LossYeongtak Oh, Saehyung Lee, Uiwon Hwang, Sungroh YoonInternational Journal of Computer Vision
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  2. 2023
    New Insights for the Stability-Plasticity Dilemma in Online Continual LearningDahuin Jung, Dongjin Lee, Sunwon Hong … Sungroh YoonICLR
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  3. 2023
    Large-scale Lifelong Learning of In-context Instructions and How to Tackle ItJ. Mok, Jaeyoung Do, Sungjin Lee … Sungroh YoonACL
  4. 2023
    CLeAR: Continual Learning on Algorithmic Reasoning for Human-like IntelligenceBong Gyun Kang, HyunGi Kim, Dahuin Jung, Sungroh YoonNeurIPS
  5. 2022
    Brain-inspired Predictive Coding Improves the Performance of Machine Challenging TasksJangho Lee, Jeonghee Jo, Byoung-Hwa Lee … Sungroh YoonFrontiers · Seoul National University · Electronics and Telecommunications Research Institute · +1
  6. 2022
    Dataset Condensation with Contrastive SignalsSaehyung Lee, Sanghyuk Chun, Sangwon Jung … Sungroh YoonICML
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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 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.