Visual Language Models: Foundations and Applications

Visual Language Models (VLMs) have swiftly accelerated the blending of the visual modality with textual information, enabling more natural and contextually aware human–AI interaction. This survey offers an in-depth overview of foundations, capabilities and constraints of existing VLMs.We first introduce a taxonomy of architecture, objectives of training and benchmark data, commenting on how design decisions impact performance. Then, we discuss evaluation processes, balancing capability measures with reliability measures like robustness, fairness and efficiency. Applications across fields like healthcare, education, scientific discovery and creative arts are discussed to illuminate both potential and practical challenges. Finally, we summarize open issues in scalability, explainability and trustworthy operation. Aiming to marry technical expertise with applied direction, the present survey hopes to illuminate researchers, practitioners and educators with an appreciation of the present state of VLMs and their future responsible use.