ConES: Concept Embedding Search for Parameter Efficient Tuning Large Vision Language Models

no code implementations • 30 May 2023 • Huahui Yi, Ziyuan Qin, Wei Xu, Miaotian Guo, Kun Wang, Shaoting Zhang, Kang Li, Qicheng Lao

To achieve this, we propose a Concept Embedding Search (ConES) approach by optimizing prompt embeddings -- without the need of the text encoder -- to capture the 'concept' of the image modality through a variety of task objectives.

Instance Segmentation Prompt Engineering +2