Auxiliary Descriptive Knowledge for Few-Shot Adaptation of Vision-Language Model

This article likely discusses a research paper on improving the performance of Vision-Language Models (VLMs) in few-shot learning scenarios. The core idea seems to be leveraging additional descriptive knowledge to help the model adapt with limited training data. The focus is on how to incorporate and utilize this auxiliary knowledge effectively.