2 papers
cs.CV2025
Efficient and Effective In-context Demonstration Selection with Coreset
Zihua Wang, Jiarui Wang, Haiyang Xu +6
In-context learning (ICL) has emerged as a powerful paradigm for Large Visual Language Models (LVLMs), enabling them to leverage a few examples directly from input contexts. Howeve…
cs.CV2025
L-CLIPScore: a Lightweight Embedding-based Captioning Metric for Evaluating and Training
Li Li, Yingzhe Peng, Xu Yang +4
We propose a novel embedding-based captioning metric termed as L-CLIPScore that can be used for efficiently evaluating caption quality and training captioning model. L-CLIPScore is…