Research on Military Multimodal Knowledge Fusion Representation Based on Retrieval-Augmented Generation

There are various forms of military knowledge and intelligence, including text, audio, images, videos and other modalities. Traditional knowledge representation methods cannot effectively associate and fuse these knowledge and intelligence, but with the rapid development of large language models based on retrieval augmentation generation technology, they have been able to identify and process multimodal information, so on this basis, this paper aims to realize the association representation of knowledge through the retrieval and multimodal processing capabilities provided by retrieval augmentation generation technology, build a vector database for multimodal battlefield intelligence knowledge, provide efficient storage and retrieval capabilities, and effectively associate and fuse battlefield knowledge to achieve effective battlefield multimodal Knowledge fusion representation.

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Publication Details

Published
2024-11-01
DOI
https://doi.org/10.1109/iccbd-ai65562.2024.00044
Primary Topic
Advanced Computational Techniques and Applications
Type
article
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article

Research on Military Multimodal Knowledge Fusion Representation Based on Retrieval-Augmented Generation

Jing Yao, Junlin Li, Bowen Zhao
Advanced Computational Techniques and Applications
article

Research on Military Multimodal Knowledge Fusion Representation Based on Retrieval-Augmented Generation

Jing Yao, Junlin Li, Bowen Zhao
article en

Abstract

There are various forms of military knowledge and intelligence, including text, audio, images, videos and other modalities. Traditional knowledge representation methods cannot effectively associate and fuse these knowledge and intelligence, but with the rapid development of large language models based on retrieval augmentation generation technology, they have been able to identify and process multimodal information, so on this basis, this paper aims to realize the association representation of knowledge through the retrieval and multimodal processing capabilities provided by retrieval augmentation generation technology, build a vector database for multimodal battlefield intelligence knowledge, provide efficient storage and retrieval capabilities, and effectively associate and fuse battlefield knowledge to achieve effective battlefield multimodal Knowledge fusion representation.

Openalex Percentile: Top 74%
Advanced Computational Techniques and Applications
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Research on Military Multimodal Knowledge Fusion Representation Based on Retrieval-Augmented Generation — Jing Yao, Junlin Li, et al. · (2024) | TGRS Research Map | TGRS