Large Vision-Language Models by Kaiyang Zhou, Ziwei Liu & Peng Gao

Large Vision-Language Models by Kaiyang Zhou, Ziwei Liu & Peng Gao

Vision-Language Models are rewriting what AI can perceive and understand — and this field is moving faster than almost any other in deep learning. Large Vision-Language Models: Pre-training, Prompting, and Applications, edited by Kaiyang Zhou, Ziwei Liu, and Peng Gao (Springer), is the authoritative academic and practitioner reference for this rapidly evolving discipline. Published in the prestigious Advances in Computer Vision and Pattern Recognition series, this book brings together the cutting edge of VLM research in one comprehensive volume.

From foundational pre-training strategies to advanced prompting techniques and real-world applications, this book covers the full technical landscape of large vision-language models with the rigor and depth that Springer is known for. Whether you're a researcher pushing the boundaries of multimodal AI, a graduate student entering the field, or an engineer building systems that understand both images and language — this is the reference work your shelf needs. The multimodal AI revolution is here. This book explains how it works.

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