# An Introduction to Vision-Language Modeling

**Authors:** Florian Bordes, Richard Yuanzhe Pang, Anurag Ajay, Alexander C. Li, Adrien Bardes, Suzanne Petryk, Oscar Mañas, Zhiqiu Lin, Anas Mahmoud, Bargav Jayaraman, Mark Ibrahim, Melissa Hall, Yunyang Xiong, Jonathan Lebensold, Candace Ross, Srihari Jayakumar, Chuan Guo, Diane Bouchacourt, Haider Al-Tahan, Karthik Padthe  
**arXiv:** [2405.17247](https://arxiv.org/abs/2405.17247)  
**Date:** 2024-05-27  
**Summary page:** https://www.summarizepaper.com/en/paper/2405.17247v1/

## Key points

- Large Language Models (LLMs) have led to the emergence of Vision-Language Models (VLMs)
- VLMs have the potential to revolutionize technology by providing visual assistance and generating images based on textual descriptions
- Challenges in development and deployment need to be addressed for reliable performance
- Disparity between language and vision is a key challenge that requires effective language-vision mapping
- This work provides a comprehensive introduction to VLMs, covering fundamentals, functioning, training methods, evaluation approaches, and potential extensions
- Authored by experts including Florian Bordes, Richard Yuanzhe Pang, Anurag Ajay, Alexander C. Li
- Serves as a valuable resource for gaining insights into Vision-Language Modeling landscape

## Summary

In recent years, Large Language Models (LLMs) have gained significant popularity and led to the emergence of Vision-Language Models (VLMs). These models have the potential to revolutionize our interaction with technology by providing visual assistance in unfamiliar environments and generating images based on textual descriptions. However, their development and deployment come with numerous challenges that need to be addressed for reliable performance. One key challenge is the disparity between language and vision, where concepts may not always be easily discretized. Effective language-vision mapping is crucial for improving VLM performance. This work aims to provide a comprehensive introduction to VLMs and aid those interested in entering this field by delving into their fundamentals, functioning, training methods, evaluation approaches, and potential extensions from image-to-language mapping to video understanding. Authored by a diverse group of experts including Florian Bordes, Richard Yuanzhe Pang, Anurag Ajay, Alexander C. Li, and others listed above, this introduction serves as a valuable resource for gaining insights into the evolving landscape of Vision-Language Modeling. With contributions from researchers across various disciplines, this work sheds light on the complexities and possibilities inherent in bridging the gap between vision and language through advanced computational models like VLMs.