2 papers
cs.CV2026
Beyond Cross-Modal Alignment: Measuring and Leveraging Modality Gap in Vision-Language Models
Hanqi Yan, Xiangxiang Cui, Lu Yin +4
The success of vision-language models is primarily attributed to effective alignment across modalities such as vision and language. However, modality gaps persist in existing align…
cs.CL2026
SemPA: Improving Sentence Embeddings of Large Language Models through Semantic Preference Alignment
Ziyang Chen, Zhenxuan Huang, Yile Wang +3
Traditional sentence embedding methods employ token-level contrastive learning on non-generative pre-trained models. Recently, there have emerged embedding methods based on generat…