AI RESEARCH
Dynamic Distillation and Gradient Consistency for Robust Long-Tailed Incremental Learning
arXiv CS.CV
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ArXi:2605.03364v1 Announce Type: new The task of Long-tailed Class Incremental Learning (LT-CIL) addresses the sequential learning of new classes from datasets with imbalanced class distributions. This scenario intensifies the fundamental problem of catastrophic forgetting, inherent to continual learning, with the dual challenges of under-learning minority classes and overfitting majority classes. To tackle these combined issues, this paper proposes two main techniques. First, we