Related work

The foundational work on continual learning, 1989 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

7 papers of 5,456Sort Recent · Most cited
  1. 2025
    Continual Neural Topic ModelCharu Karakkaparambil James, Waleed Mustafa, Marius Kloft, Sophie FellenzEACL
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  2. 2023PDF ↗
  3. 2023
    Generative Replay Inspired by Hippocampal Memory Indexing for Continual Language LearningAru Maekawa, Hidetaka Kamigaito, Kotaro Funakoshi, Manabu OkumuraEACL · Tokyo Institute of Technology · Nara Institute of Science and Technology
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  4. 2021
    AdapterFusion: Non-Destructive Task Composition for Transfer LearningJonas Pfeiffer, Aishwarya Kamath, Andreas Rücklé … Iryna GurevychEACL · Technische Universität Darmstadt · Supélec · +5
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  5. 2021
    Multilingual Machine Translation: Closing the Gap between Shared and Language-specific Encoder-DecodersCarlos Escolano, Marta R. Costa‐jussà, José A. R. Fonollosa, Mikel ArtetxeEACL · Universitat Politècnica de Catalunya · University of the Basque Country · +1
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  6. 2021
    Elastic weight consolidation for better bias inoculationJames Thorne, Andreas VlachosEACL · University of Cambridge
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  7. 2021
    Lifelong Knowledge-Enriched Social Event Representation LearningPrashanth Vijayaraghavan, Deb RoyEACL · IIT@MIT · Human Media
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 written 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.