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cs.LG2025
Pushing the Limits of Distillation-Based Continual Learning via Classifier-Proximal Lightweight Plugins
Zhiming Xu, Baile Xu, Jian Zhao +2
Continual learning requires models to learn continuously while preserving prior knowledge under evolving data streams. Distillation-based methods are appealing for retaining past k…
cs.LG2025
Multimodal-Guided Dynamic Dataset Pruning for Robust and Efficient Data-Centric Learning
Suorong Yang, Peijia Li, Yujie Liu +5
Modern deep models are trained on large real-world datasets, where data quality varies and redundancy is common. Data-centric approaches such as dataset pruning have shown promise…