Related work

The foundational work on continual learning, 1980 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

4 papers of 8,653Sort Recent · Most cited
  1. 2026
    Robust Embodied Perception in Dynamic Environments via Disentangled Weight FusionJuncen Guo, Xiaoguang Zhu, Jingyi Wu … Liang SongarXiv
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  2. 2025
    Adaptive Weighted Parameter Fusion with CLIP for Class-Incremental LearningJuncen Guo, Xiaoguang Zhu, Liangyu Teng … Liang SongIEEE International Conference on Multimedia and Expo (ICME) · Fudan University · University of California, Davis · +1
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  3. 2025
    CalFuse: Multi-Modal Continual Learning via Feature Calibration and Parameter FusionJun-Cen Guo, Siao Liu, Xiaoguang Zhu … Liang SongarXiv
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  4. 2025
    Feature Calibration enhanced Parameter Synthesis for CLIP-based Class-incremental LearningJun-Cen Guo, Xiaoguang Zhu, Lianlong Sun … Liang SongarXiv
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.