Dynamically Anchored Prompting for Task-Imbalanced Continual Learning

Existing continual learning literature relies heavily on a strong assumption that tasks arrive with a balanced data stream, which is often unrealistic in real-world applications. In this work, we explore task-imbalanced continual learning (TICL) scenarios where the distribution of task data is non-u...

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Bibliographic Details
Main Authors Hong, Chenxing, Jin, Yan, Kang, Zhiqi, Chen, Yizhou, Li, Mengke, Lu, Yang, Wang, Hanzi
Format Journal Article
LanguageEnglish
Published 22.04.2024
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