JindongGu/Awesome-Prompting-on-Vision-Language-Model
This repo lists relevant papers summarized in our survey paper: A Systematic Survey of Prompt Engineering on Vision-Language Foundation Models.
This resource helps AI researchers and practitioners understand and apply 'prompt engineering' to Vision-Language Models (VLMs). It provides a curated collection of research papers that detail how to fine-tune existing multimodal-to-text, image-text matching, and text-to-image generation models for new tasks. Researchers can use this to quickly find relevant studies and techniques to improve their VLM applications.
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Use this if you are a researcher or AI practitioner exploring the cutting-edge of prompt engineering for Vision-Language Models and need a curated list of influential papers and their classifications.
Not ideal if you are looking for an introductory guide to large language models or a hands-on coding tutorial for VLM prompting, as this is a research-focused survey.
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