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.

6 papers of 8,653Sort Recent · Most cited
  1. 2024
    Adaptive LoRA Merging for Efficient Domain Incremental LearningLuigi Quarantiello, Eric Coleman, Julio Hurtado, Vincenzo LomonacoNeurIPS · University of Warwick
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  2. 2024
    I Know How: Combining Prior Policies to Solve New TasksMalio Li, Elia Piccoli, Vincenzo Lomonaco, Davide BacciuIEEE Conference on Games (CoG) · University of Pisa
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  3. 2024
    Calibration of Continual Learning ModelsLanpei Li, Elia Piccoli, Andrea Cossu … Vincenzo LomonacoCVPR · University of Pisa · Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo"
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  4. 2024
    Adaptive Hyperparameter Optimization for Continual Learning ScenariosRudy Semola, Julio Hurtado, Vincenzo Lomonaco, Davide BacciuCLAI Unconf
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  5. 2024
    Continual Learning: Applications and the Road ForwardEli Verwimp, Rahaf Aljundi, Shai Ben-David … Gido M. van de VenTMLR
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  6. 2024
    Continual Pre-Training Mitigates Forgetting in Language and VisionAndrea Cossu, Tinne Tuytelaars, Antonio Carta … Davide BacciuNeural Networks
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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. By default it shows the papers we have a reason to trust: published at a venue like NeurIPS, ICML, ICLR, CVPR or TPAMI, or written by someone who has published there, or cited a few hundred times. The rest are one click away under “All papers”. 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.