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. 2025
    Genesis: A Spiking Neuromorphic Accelerator With On-chip Continual LearningVedant Karia, Abdullah M. Zyarah, Dhireesha KudithipudiarXiv
    PDF ↗
  2. 2024
    Probabilistic metaplasticity for continual learning with memristors in spiking networksFatima Tuz Zohora, Vedant Karia, Nicholas Soures, Dhireesha KudithipudiScientific Reports · The University of Texas at San Antonio
    PDF ↗
  3. 2024
    PositCL: Compact Continual Learning with Posit Aware QuantizationVedant Karia, Abdullah M. Zyarah, Dhireesha KudithipudiGreat Lakes Symposium on VLSI 2024 · The University of Texas at San Antonio
    PDF ↗
  4. 2024
    Advancing Neuro-Inspired Lifelong Learning for Edge with Co-DesignNicholas Soures, Vedant Karia, Dhireesha KudithipudiAAAI · The University of Texas at San Antonio
    PDF ↗
  5. 2022
    SCOLAR: A Spiking Digital Accelerator with Dual Fixed Point for Continual LearningVedant Karia, Fatima Tuz Zohora, Nicholas Soures, Dhireesha KudithipudiIEEE International Symposium on Circuits and Systems (ISCAS) · The University of Texas at San Antonio
  6. 2021
    MetaplasticNet: Architecture with Probabilistic Metaplastic Synapses for Continual LearningFatima Tuz Zohora, Vedant Karia, Anurag Daram … Dhireesha KudithipudiIEEE International Symposium on Circuits and Systems (ISCAS) · The University of Texas at San Antonio
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.