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Titlebook: Advances in Multimodal Information Retrieval and Generation; Man Luo,Tejas Gokhale,Chitta Baral Book 2025 The Editor(s) (if applicable) an

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发表于 2025-3-21 17:47:57 | 显示全部楼层 |阅读模式
期刊全称Advances in Multimodal Information Retrieval and Generation
影响因子2023Man Luo,Tejas Gokhale,Chitta Baral
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发行地址Provides a comprehensive overview of the state-of-the-art in multi-modal architectures and representation learning.Presents state-of-the-art techniques including neural models based on transformers an
学科分类Synthesis Lectures on Computer Vision
图书封面Titlebook: Advances in Multimodal Information Retrieval and Generation;  Man Luo,Tejas Gokhale,Chitta Baral Book 2025 The Editor(s) (if applicable) an
影响因子.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 AI.  As such, the book is a crucial resource for anyone interested in delving into the intricacies of multimodal retrieval and generation.  Serving as a bridge to mastering and leveraging advanced AI technologies in this field, the book is designed for students, researchers, practitioners, and AI aficionados alike, offering the tools needed to expand the horizons of what can be achieved in multimodal artificial intelligence..
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发表于 2025-3-21 21:23:11 | 显示全部楼层
978-3-031-57818-2The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
发表于 2025-3-22 02:26:02 | 显示全部楼层
Man Luo,Tejas Gokhale,Chitta BaralProvides a comprehensive overview of the state-of-the-art in multi-modal architectures and representation learning.Presents state-of-the-art techniques including neural models based on transformers an
发表于 2025-3-22 04:35:51 | 显示全部楼层
Synthesis Lectures on Computer Visionhttp://image.papertrans.cn/b/image/167290.jpg
发表于 2025-3-22 09:17:58 | 显示全部楼层
https://doi.org/10.1007/978-3-8351-9208-9In this chapter, we will learn about the modeling and learning techniques that drive multimodal applications. We will focus specifically on the recent advances in transformer-based modeling for natural language understanding, and image understanding, and how these approaches connect for jointly understanding combinations of language and image.
发表于 2025-3-22 13:25:50 | 显示全部楼层
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发表于 2025-3-23 00:32:58 | 显示全部楼层
https://doi.org/10.1007/978-3-8351-9208-9, limited to a single type of data, often fall short of capturing the complexity and richness of human communication and experience. In contrast, multimodal retrieval systems leverage the complementary nature of different data types to provide more accurate, context-aware, and user-centric search re
发表于 2025-3-23 03:08:03 | 显示全部楼层
https://doi.org/10.1007/978-3-8351-9208-9t. With the proliferation of multimedia platforms and data sources, we are constantly bombarded with a rich variety of images, videos, audio, and text. This vast array of heterogeneous data poses new challenges and opportunities for the field of Information Retrieval (IR). To address these challenge
发表于 2025-3-23 07:14:36 | 显示全部楼层
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