Understanding and Improving In-Context Learning on Vision-language
Models

Understanding and Improving In-Context Learning on Vision-language Models

29 November 2023

Zhen Han

Philip H. S. Torr

Jindong Gu

Papers citing "Understanding and Improving In-Context Learning on Vision-language Models"

4 / 4 papers shown

Title
CBVLM: Training-free Explainable Concept-based Large Vision Language Models for Medical Image Classification Cristiano Patrício Isabel Rio-Torto J. S. Cardoso Luís F. Teixeira João C. Neves VLM 109 0 0 21 Jan 2025
BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation Junnan Li Dongxu Li Caiming Xiong S. Hoi MLLM BDL VLM CLIP 380 4,010 0 28 Jan 2022
An Empirical Study of GPT-3 for Few-Shot Knowledge-Based VQA Zhengyuan Yang Zhe Gan Jianfeng Wang Xiaowei Hu Yumao Lu Zicheng Liu Lijuan Wang 161 401 0 10 Sep 2021
Fantastically Ordered Prompts and Where to Find Them: Overcoming Few-Shot Prompt Order Sensitivity Yao Lu Max Bartolo Alastair Moore Sebastian Riedel Pontus Stenetorp AILaw LRM 274 882 0 18 Apr 2021