Related work

The foundational work on continual learning, 1988 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

6 papers of 6,984Sort Recent · Most cited
  1. 2024
    Streaming Continual Learning for Unified Adaptive Intelligence in Dynamic EnvironmentsFederico Giannini, Giacomo Ziffer, Andrea Cossu, Vincenzo LomonacoIEEE Intelligent Systems · Politecnico di Milano · University of Pisa
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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
    Drifting explanations in continual learningAndrea Cossu, Francesco Spinnato, Riccardo Guidotti, Davide BacciuNeurocomputing · University of Pisa · Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" · +1
  5. 2024
    Updating knowledge in Large Language Models: an Empirical EvaluationAlberto Roberto Marinelli, Antonio Carta, Lucia PassaroIEEE International Conference on Evolving and Adaptive In… · University of Pisa
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  6. 2024
    Continual Learning with Graph Reservoirs: Preliminary experiments in graph classificationDomenico Tortorella, Alessio MicheliESANN 2024 proceesdings · University of Pisa · Istituto Nazionale di Fisica Nucleare, Sezione di Pisa
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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 lists only papers we have a reason to trust: published at a venue like NeurIPS, ICML, ICLR, CVPR or TPAMI, or led by someone who has published there, or cited a few hundred times. Preprints that later get accepted, and authors who later publish at those venues, are picked up by the weekly run. 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.