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class-incremental learning

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Jul 13, 2026 · Artificial Intelligence

Breaking the Forgetting Barrier: CaRE Scales Continual Learning to 300+ Tasks

The paper introduces CaRE, a scalable continual‑learning framework that leverages a bi‑level routing mixture‑of‑experts to successfully train Vision Transformers on over 300 non‑overlapping tasks, outperforming existing baselines and accompanied by a new 1,000‑class benchmark, OmniBenchmark‑1K.

Bi-Level RoutingCaREMixture of Experts

0 likes · 11 min read

Breaking the Forgetting Barrier: CaRE Scales Continual Learning to 300+ Tasks

Alibaba Cloud Big Data AI Platform

Mar 19, 2024 · Artificial Intelligence

M2SD: Multiple Mixing Self-Distillation for Few-Shot Class-Incremental Learning

This paper introduces M2SD, a dual‑branch multiple‑mixing self‑distillation framework that expands feature space, mitigates overfitting and catastrophic forgetting, and achieves state‑of‑the‑art results on CIFAR‑100, CUB‑200 and miniImageNet for few‑shot class‑incremental learning.

M2SDclass-incremental learningfeature augmentation

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M2SD: Multiple Mixing Self-Distillation for Few-Shot Class-Incremental Learning