4 papers · 1 filter
Information-Theoretic Decoupled Prompt Tuning for Continual Learning
Yunfei Zhang, Wen Wen, Tieliang Gong +1
Continual learning (CL) aims to incrementally acquire knowledge from sequential data while avoiding catastrophic forgetting. Recently, prompt tuning has attracted increasing attent…
Drift and Dependence: Layer-wise Information-Theoretic Bounds for Replay-Based Continual Learning
Tieliang Gong, Zhongbo Zhang, Wen Wen +1
Continual learning must absorb new tasks without erasing old ones, and replay---mixing a small buffer of past examples into current training---is among the most effective remedies…
Beyond Sharpness: A Flatness Decomposition Framework for Efficient Continual Learning
Yanan Chen, Tieliang Gong, Yunjiao Zhang +1
Continual Learning (CL) aims to enable models to sequentially learn multiple tasks without forgetting previous knowledge. Recent studies have shown that optimizing towards flatter…
Information-Theoretic Generalization Bounds of Replay-based Continual Learning
Wen Wen, Tieliang Gong, Zeyu Gao +3
Continual learning (CL) has emerged as a dominant paradigm for acquiring knowledge from sequential tasks while avoiding catastrophic forgetting. Although many CL methods have been…