Co2In: a Bi-level Memory Incremental Learning Framework with Knowledge Encoding, Consolidation, and Integration

Co2In is a bi‑level memory incremental learning framework that mimics human memory mechanisms. It uses a working memory to encode new knowledge and a long‑term memory to retain it, with a consolidation step that extracts patterns and compresses them into a compact representation. Experiments on CIFAR‑10, CIFAR‑100, and Tiny‑ImageNet demonstrate state‑of‑the‑art performance while keeping memory usage efficient.

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