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cs.CV2024
LPT: Less-overfitting Prompt Tuning for Vision-Language Model
Chenhao Ding, Xinyuan Gao, Songlin Dong +5
Vision-language models (VLMs) have demonstrated exceptional generalization capabilities for downstream tasks. Due to its efficiency, prompt learning has gradually become a more eff…
cs.CV2024
Beyond Prompt Learning: Continual Adapter for Efficient Rehearsal-Free Continual Learning
Xinyuan Gao, Songlin Dong, Yuhang He +2
The problem of Rehearsal-Free Continual Learning (RFCL) aims to continually learn new knowledge while preventing forgetting of the old knowledge, without storing any old samples an…
cs.CV2024
CEAT: Continual Expansion and Absorption Transformer for Non-Exemplar Class-Incremental Learning
Xinyuan Gao, Songlin Dong, Yuhang He +2
In real-world applications, dynamic scenarios require the models to possess the capability to learn new tasks continuously without forgetting the old knowledge. Experience-Replay m…