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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https://doi.org/10.1007/978-3-662-00073-1 to achieving effective retrieval, including multimodal retrieval and generative retrieval. Another important application of retrieval is its integration with language models, referred to as retrieval-augmented modeling. In this chapter, we will focus on this paradigm in detail and provide a taxonom

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https://doi.org/10.1007/978-3-658-11797-9lenges associated with the information that lives on the internet. While we develop technologies that make the process of information retrieval faster, easy to use, and equipped with many features and functionalities that improve user experience, we must be vary of potential misuse. The commitment t

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Book 2025gmented 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 an

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https://doi.org/10.1007/978-3-662-00073-1ion with language models, referred to as retrieval-augmented modeling. In this chapter, we will focus on this paradigm in detail and provide a taxonomy of retrieval-augmented modeling over multiple dimensions.

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