Related work

The foundational work on continual learning, 1959 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

24 papers of 11,817Sort Recent · Most cited
  1. 2026PDF ↗
  2. 2026PDF ↗
  3. 2026
    SPREAD: Subspace Representation Distillation for Lifelong Imitation LearningKaushik Roy, Giovanni D'Urso, Nicholas Lawrance … Peyman MoghadamarXiv
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  4. 2026
    ELLA: Efficient Lifelong Learning for Adapters in Large Language ModelsShristi Das Biswas, Yue Zhang, Anwesan Pal … Kaushik RoyEACL
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  5. 2025PDF ↗
  6. 2025
  7. 2024
    CODE-CL: Conceptor-Based Gradient Projection for Deep Continual LearningM. Apolinario, Sakshi Choudhary, Kaushik RoyICCV
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  8. 2024
    M2Distill: Multi-Modal Distillation for Lifelong Imitation LearningKaushik Roy, Akila Dissanayakc, Brendan Tidd, P. MoghadamICRA
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  9. 2024
    Continual Learning: A Review of Techniques, Challenges, and Future DirectionsB. Wickramasinghe, Gobinda Saha, Kaushik RoyIEEE TAI
  10. 2023
    CL3: Generalization of Contrastive Loss for Lifelong LearningKaushik Roy, Christian Simon, Peyman Moghadam, Mehrtash HarandiJournal of Imaging
  11. 2023
    L3 Ensembles: Lifelong Learning Approach for Ensemble of Foundational Language Models✱Aidin Shiri, Kaushik Roy, Amit P. Sheth, Manas GaurCOMAD/CODS
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  12. 2023
    Subspace Distillation for Continual LearningKaushik Roy, Christian Simon, Peyman Moghadam, Mehrtash HarandiNeural Networks
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  13. 2023
    L3DMC: Lifelong Learning using Distillation via Mixed-Curvature SpaceKaushik Roy, Peyman Moghadam, Mehrtash HarandiMICCAI
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  14. 2023
  15. 2023
    CoDeC: Communication-Efficient Decentralized Continual LearningSakshi Choudhary, Sai Aparna Aketi, Gobinda Saha, Kaushik RoyTrans. Mach. Learn. Res.
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  16. 2023PDF ↗
  17. 2021
    Saliency Guided Experience Packing for Replay in Continual LearningGobinda Saha, Kaushik RoyWACV · Purdue University West Lafayette
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  18. 2023
  19. 2020
    SPACE: Structured Compression and Sharing of Representational Space for Continual LearningGobinda Saha, Isha Garg, Aayush Ankit, Kaushik RoyIEEE Access · Purdue University West Lafayette
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  20. 2019PDF ↗
  21. 2017
    Incremental Learning in Deep Convolutional Neural Networks Using Partial Network SharingSyed Shakib Sarwar, Aayush Ankit, Kaushik RoyIEEE Access · Purdue University West Lafayette
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  22. 2018
    Tree-CNN: A hierarchical Deep Convolutional Neural Network for incremental learningDeboleena Roy, Priyadarshini Panda, Kaushik RoyNeural Networks · Purdue University West Lafayette
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  23. 2017
    ASP: Learning to Forget With Adaptive Synaptic Plasticity in Spiking Neural NetworksPriyadarshini Panda, Jason M. Allred, Shriram Ramanathan, Kaushik RoyIEEE Journal on Emerging and Selected Topics in Circuits… · Purdue University West Lafayette
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  24. 2017
    Habituation based synaptic plasticity and organismic learning in a quantum perovskiteFan Zuo, Priyadarshini Panda, Michele Kotiuga … Shriram RamanathanNature Communications · Purdue University West Lafayette · Rutgers, The State University of New Jersey · +3
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 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.