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. 2024
    Dynamic Prompt Selection for Resource-Efficient Continual Learning in Panoptic SegmentationQuynh-Trang Pham Thi, Minh-Anh Dang, Tri-Thanh Nguyen … Thanh-Hai DangRIVF International Conference on Computing and Communicat… · FPT University
  2. 2024
    FT-IBCL: Enhancing Imprecise Bayesian for Continual Learning Under Trade-Offs with Fine-TuningQuynh-Trang Pham Thi, Tu-Tai Hoang, Van-Toan Phan … Thanh Hai DangInternational Conference on Knowledge and System Engineer… · VNU University of Science · Hội Gastroenterology Việt Nam
  3. 2024
    Contrastive Learning for Boosting Knowledge Transfer in Task-Incremental Continual Learning of Aspect Sentiment Classification TasksThanh Hai Dang, Quynh-Trang Pham Thi, Duc-Trong Le, Tri-Thanh NguyenVNU Journal of Science Computer Science and Communication… · VNU University of Science · Universal Environmental Technologies (United States)
  4. 2024
    Towards Robust Continual Learning: A Multi-Head Approach with Online Prototype Equilibrium and Adaptive Prototypical FeedbackQuynh-Trang Pham Thi, Duc‐Hung Nguyen, Thanh Hai Dang … Quang-Thuy HaSpringer LNCS · VNU University of Science
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.