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Multimodal Knowledge Graph Completion via Relation-Aware Negative Sampling with Diffusion-Based Interpolation

Summary: RelDINS performs relation-cardinality-aware multimodal embedding learning and diffusion-space interpolation to generate hardness-tunable negative samples. It improves semantic consistency and achieves state-of-the-art MMKG completion accuracy. (summarized by gpt-5.6-luna on Aug 17 2026)

Paper ID
hd2ab4fb67e95bb7b
Venue
VLDB
Year
2026
Pagerank
4.9793485e-05
Overall Rank
10,761 | 27.65%
DOI
10.14778/3819518.3819526

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BibTeX Citation

@article{ma_vldb26,
        title = {{Multimodal Knowledge Graph Completion via Relation-Aware Negative Sampling with Diffusion-Based Interpolation}},
        author = {Ma, Qian and Dai, Linfei and Yao, Zhongming and Gu, Yu and Li, Tianyi and Jensen, Christian S. and Yu, Ge},
        journal = {PVLDB},
        series = {{VLDB} '26},
        volume = {19},
        number = {9},
        pages = {1949--1962},
        doi = {10.14778/3819518.3819526},
        url = {https://doi.org/10.14778/3819518.3819526},
        year = {2026}
}

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