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Dec, 2023
大型视觉语言模型的少样本自适应研究
A Closer Look at the Few-Shot Adaptation of Large Vision-Language Models
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Julio Silva-Rodriguez, Sina Hajimiri, Ismail Ben Ayed, Jose Dolz
TL;DR
通过引入适应真实场景需求的新方法,我们综合评估了一个广泛的数据集和场景,发现其在实践中始终优于现有技术,同时作为更高效的替代方案。
Abstract
efficient transfer learning
(ETL) is receiving increasing attention to adapt large
pre-trained language-vision models
on downstream tasks with a few labeled samples. While significant progress has been made, we r
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