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LSA-PAST: Layer-Specific Adaptation and Prototype Transport for Compositional Incremental Learning
Class-Incremental Learning (CIL) enables models to recognize new classes over time while retaining prior knowledge, but many real-world problems are compositional, where visual concepts arise from combinations of primitives such as states (i.e., red, shiny) and objects (i.e., shoe, car). Standard CI
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