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.

8 papers of 8,653Sort Recent · Most cited
  1. 2025
    TinyCL: An Efficient Hardware Architecture for Continual Learning on Autonomous SystemsEugenio Ressa, Alberto Marchisio, Maurizio Martina … Muhammad ShafiqueIJCNN · Politecnico di Torino · New York University Abu Dhabi
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  2. 2025
    Replay4NCL: An Efficient Memory Replay-based Methodology for Neuromorphic Continual Learning in Embedded AI SystemsMishal Fatima Minhas, Rachmad Vidya Wicaksana Putra, Falah Awwad … Muhammad ShafiqueDesign Automation Conference · United Arab Emirates University · New York University Abu Dhabi · +1
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  3. 2024
    Continual Learning With Neuromorphic Computing: Foundations, Methods, and Emerging ApplicationsMishal Fatima Minhas, Rachmad Vidya Wicaksana Putra, Falah R. Awwad … Muhammad ShafiqueIEEE Access
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  4. 2024
    Examining Changes in Internal Representations of Continual Learning Models Through Tensor DecompositionNishant Suresh Aswani, Amira Guesmi, Muhammad Abdullah Hanif, Muhammad ShafiqueCLAI Unconf
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  5. 2023
    A Framework for Open World Object DetectionKhadija Shaheen, Muhammad Abdullah Hanif, Osman Hasan, Muhammad ShafiqueArtificial Intelligence Evolution · National University of Sciences and Technology · New York University Abu Dhabi
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  6. 2022
    lpSpikeCon: Enabling Low-Precision Spiking Neural Network Processing for Efficient Unsupervised Continual Learning on Autonomous AgentsRachmad Vidya Wicaksana Putra, Muhammad ShafiqueIJCNN · TU Wien · New York University Abu Dhabi
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  7. 2022
    Continual Learning for Real-World Autonomous Systems: Algorithms, Challenges and FrameworksKhadija Shaheen, Muhammad Abdullah Hanif, Osman Hasan, Muhammad ShafiqueJournal of Intelligent & Robotic Systems · National University of Sciences and Technology · New York University Abu Dhabi
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  8. 2021
    SpikeDyn: A Framework for Energy-Efficient Spiking Neural Networks with Continual and Unsupervised Learning Capabilities in Dynamic EnvironmentsRachmad Vidya Wicaksana Putra, Muhammad ShafiqueDesign Automation Conference · TU Wien · New York University Abu Dhabi
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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.