This book provides an extensive examination of state-of-the-art methods in multimodal retrieval, generation, and the pioneering field of retrieval-augmented generation.  The work is rooted in the domain of Transformer-based models, exploring the complexities of blending and interpreting the intricate connections between text and images.  The authors present cutting-edge theories, methodologies, and frameworks dedicated to multimodal retrieval and generation, aiming to furnish readers with a comprehensive understanding of the current state and future prospects of multimodal...