4 papers
Joint Semantic Token Selection and Prompt Optimization for Interpretable Prompt Learning
Yating Wang, Yaqi Zhao, Yongshun Gong +2
Vision-language models such as CLIP achieve strong visual-textual alignment, but often suffer from overfitting and limited interpretability when adapted through continuous prompt l…
Holistic Optimal Label Selection for Robust Prompt Learning under Partial Labels
Yaqi Zhao, Haoliang Sun, Yating Wang +2
Prompt learning has gained significant attention as a parameter-efficient approach for adapting large pre-trained vision-language models to downstream tasks. However, when only par…
A Conditional Probability Framework for Compositional Zero-shot Learning
Peng Wu, Qiuxia Lai, Hao Fang +4
Compositional Zero-Shot Learning (CZSL) aims to recognize unseen combinations of known objects and attributes by leveraging knowledge from previously seen compositions. Traditional…
Off-OAB: Off-Policy Policy Gradient Method with Optimal Action-Dependent Baseline
Wenjia Meng, Qian Zheng, Long Yang +2
Policy-based methods have achieved remarkable success in solving challenging reinforcement learning problems. Among these methods, off-policy policy gradient methods are particular…