Rethinking visual prompting for multimodal large language models with external knowledge
In recent years, multimodal large language models (MLLMs) have made significant strides by training on vast high-quality image-text datasets, enabling them to generally understand images well. However, the inherent difficulty in explicitly conveying fine-grained or spatially dense information in tex...
Asıl Yazarlar: | Lin, Y, Li, Y, Chen, D, Xu, W, Clark, R, Torr, P, Yuan, L |
---|---|
Materyal Türü: | Internet publication |
Dil: | English |
Baskı/Yayın Bilgisi: |
2024
|
Benzer Materyaller
-
Prompting Large Language Models with Knowledge-Injection for Knowledge-Based Visual Question Answering
Yazar:: Zhongjian Hu, ve diğerleri
Baskı/Yayın Bilgisi: (2024-09-01) -
Knowledge graph construction for heart failure using large language models with prompt engineering
Yazar:: Tianhan Xu, ve diğerleri
Baskı/Yayın Bilgisi: (2024-07-01) -
Prompt Optimization in Large Language Models
Yazar:: Antonio Sabbatella, ve diğerleri
Baskı/Yayın Bilgisi: (2024-03-01) -
CAT: enhancing multimodal large language model to answer questions in dynamic audio-visual scenarios
Yazar:: Ye, Q, ve diğerleri
Baskı/Yayın Bilgisi: (2024) -
Review of large vision models and visual prompt engineering
Yazar:: Jiaqi Wang, ve diğerleri
Baskı/Yayın Bilgisi: (2023-11-01)