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.
Authors
- Rongqun Lin (ORCID: https://orcid.org/0000-0003-0711-8012)
- Siwei Ma (ORCID: https://orcid.org/0000-0002-2731-5403)
- Y.B. Wang (ORCID: https://orcid.org/0000-0002-3184-4201)
- Yue Tong (ORCID: https://orcid.org/0009-0003-6881-2080)
- Tao Zhang (ORCID: https://orcid.org/0000-0002-2980-6281)
- Feng Gao (ORCID: https://orcid.org/0009-0004-5859-9586)
- Zehao Li (ORCID: https://orcid.org/0000-0003-4535-7698)
- Haofeng Wang (ORCID: https://orcid.org/0000-0002-5865-263X)
- Yilin Guo (ORCID: https://orcid.org/0009-0007-8410-2328)
- Shiqi Wang
Institutions
- 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)
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
Funders
- National Natural Science Foundation of China
- Bulgarian National Science Fund