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.

11 papers of 8,653Sort Recent · Most cited
  1. 2026PDF ↗
  2. 2026
    Domain-Agnostic Incremental Learning for Sound Classification. A DCASE 2026 Challenge taskRiccardo Casciotti, Manjunath Mulimani, Manu Harju … Annamaria MesarosarXiv
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  3. 2026
    Incremental learning for audio classification with Hebbian Deep Neural NetworksRiccardo Casciotti, Francesco De Santis, Alberto Antonietti, Annamaria MesarosICASSP · Tampere University · Politecnico di Milano
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  4. 2025
    Online incremental learning for audio classification using a pretrained audio modelManjunath Mulimani, Annamaria MesarosIEEE Workshop on Applications of Signal Processing to Aud… · Tampere University
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  5. 2025
    Learning Order Matters in Class-Incremental Learning for Sound Localization and DetectionRuchi Pandey, Manjunath Mulimani, Archontis Politis, Annamaria MesarosEuropean Signal Processing Conference (EUSIPCO) · Tampere University of Applied Sciences · Tampere University
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  6. 2025
    Class-Incremental Learning for Sound Event Localization and DetectionRuchi Pandey, Manjunath Mulimani, Archontis Politis, Annamaria MesarosICASSP · Tampere University
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  7. 2025
    Domain-Incremental Learning for Audio ClassificationManjunath Mulimani, Annamaria MesarosICASSP · Tampere University
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  8. 2025
    A Closer Look at Class-Incremental Learning for Multi-Label Audio ClassificationManjunath Mulimani, Annamaria MesarosIEEE Transactions · Tampere University
  9. 2024
    Online Domain-Incremental Learning Approach to Classify Acoustic Scenes in All LocationsManjunath Mulimani, Annamaria MesarosEuropean Signal Processing Conference
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  10. 2024
    Class-Incremental Learning for Multi-Label Audio ClassificationManjunath Mulimani, Annamaria MesarosICASSP · Tampere University
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  11. 2023
    Incremental Learning of Acoustic Scenes and Sound EventsManjunath Mulimani, Annamaria MesarosarXiv
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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.