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MGRAG: Semantic Subgraph Matching and Graph-Aware Caching for Multimodal Retrieval-Augmented Generation

Summary: MGRAG builds query-specific multimodal KGs lazily and retrieves evidence via semantics-aware path/subgraph matching rather than rigid topology. Its event-aware KV cache preserves graph-level structure while avoiding unnecessary token recomputation, improving RAG effectiveness and efficiency. (summarized by gpt-5.6-luna on Aug 17 2026)

Paper ID
h90d6a1db7d5bba1e
Venue
VLDB
Year
2026
Pagerank
4.9793485e-05
Overall Rank
10,800 | 27.39%
DOI
10.14778/3819518.3819565

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BibTeX Citation

@article{wang_vldb26,
        title = {{MGRAG: Semantic Subgraph Matching and Graph-Aware Caching for Multimodal Retrieval-Augmented Generation}},
        author = {Wang, Yubo and Li, Haoyang and Chen, Lei},
        journal = {PVLDB},
        series = {{VLDB} '26},
        volume = {19},
        number = {9},
        pages = {2480--2493},
        doi = {10.14778/3819518.3819565},
        url = {https://doi.org/10.14778/3819518.3819565},
        year = {2026}
}

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