RiverEcho-2.0: A Real-Time Interactive System for Yellow River Culture via Enhanced MultiModal Document RAG

The Yellow River culture is a cornerstone of Chinese civilization, embodying rich historical, social, and ecological significance. To conserve and promote this invaluable cultural heritage, we propose RiverEcho-2.0, a real-time interactive digital system designed to facilitate user engagement with Yellow River culture. As the foundation of our system, we curated and digitized a comprehensive collection of books and documents related to Yellow River heritage, constructing a dedicated multimodal corpus. To effectively leverage this corpus, we introduce a novel multi-modal Document Retrieval-Augmented Generation (RAG) framework that enhances document retrieval through context-aware image-text alignment and joint embedding. Experimental results demonstrate that our method achieves a large improvement over existing state-of-the-art multi-modal RAG baselines, leading to significant gains in downstream tasks.

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Publication Details

Journal
Transactions on Artificial Intelligence
Published
2025-09-22
DOI
https://doi.org/10.53941/tai.2025.100014
Citations
1
Primary Topic
Advanced Computational Techniques and Applications
Type
article
Field-Weighted Citation Impact
2.48

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article

RiverEcho-2.0: A Real-Time Interactive System for Yellow River Culture via Enhanced MultiModal Document RAG

Rongqun Lin, Siwei Ma, Y.B. Wang, Yue Tong et al.
1 citations
Transactions on Artificial Intelligence
Advanced Computational Techniques and Applications
2.48
article

RiverEcho-2.0: A Real-Time Interactive System for Yellow River Culture via Enhanced MultiModal Document RAG

Rongqun Lin, Siwei Ma, Y.B. Wang, Yue Tong, Tao Zhang, Feng Gao, Zehao Li, Haofeng Wang, Yilin Guo, Shiqi Wang
article en
1 citations

Abstract

The Yellow River culture is a cornerstone of Chinese civilization, embodying rich historical, social, and ecological significance. To conserve and promote this invaluable cultural heritage, we propose RiverEcho-2.0, a real-time interactive digital system designed to facilitate user engagement with Yellow River culture. As the foundation of our system, we curated and digitized a comprehensive collection of books and documents related to Yellow River heritage, constructing a dedicated multimodal corpus. To effectively leverage this corpus, we introduce a novel multi-modal Document Retrieval-Augmented Generation (RAG) framework that enhances document retrieval through context-aware image-text alignment and joint embedding. Experimental results demonstrate that our method achieves a large improvement over existing state-of-the-art multi-modal RAG baselines, leading to significant gains in downstream tasks.

Transactions on Artificial IntelligenceVol. 1(1)
City University of Hong Kong (HK), Peking University (CN), Peking University Shenzhen Hospital (CN), Peng Cheng Laboratory (CN), Institute for Advanced Study (DE), Renmin University of China (CN)
National Natural Science Foundation of China, Bulgarian National Science Fund
Openalex Percentile: Top 8%
Advanced Computational Techniques and Applications
2.48
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