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.

3 papers of 8,653Sort Recent · Most cited
  1. 2026
    SAILS: Segment Anything with Incrementally Learned Semantics for Task-Invariant and Training-Free Continual LearningShishir Muralidhara, Didier Stricker, René SchusterIEEE Conference on Artificial Intelligence (CAI) · German Research Centre for Artificial Intelligence
    PDF ↗
  2. 2024
    PoseAdapt: Sustainable Human Pose Estimation via Continual Learning Benchmarks and ToolkitMuhammad Saif Ullah Khan, Didier StrickerWACV · German Research Centre for Artificial Intelligence
    PDF ↗
  3. 2022
    Attribution-aware Weight Transfer: A Warm-Start Initialization for Class-Incremental Semantic SegmentationDipam Goswami, René Schuster, Joost van de Weijer, Didier StrickerWACV · German Research Centre for Artificial Intelligence · Birla Institute of Technology and Science, Pilani · +2
    PDF ↗
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.