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Research questionHow can pretrained models learn new concepts from evolving streams without task identities or replay while retaining prior knowledge?In general continual learning, data arrive as a nonstationary stream without reliable task labels or known boundaries, and earlier examples cannot be revisited. The model must update its representations for new concepts without destabilizing knowledge acquired earlier.
AI
Machine Learning
Latest papersRecent research connected to this question, newest first.MePo++: Unifying Representation Refinement and Reconciliation for General Continual LearningThe source concerns pretrained models receiving evolving data streams without task identities, explicit boundaries, or repeated access to previous data. Evidence comes from experiments across diverse pretrained models, datasets, and continual-learning baselines; the abstract does not specify modalities, stream construction, or deployment constraints.research paper · Sep 4, 2026
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