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GeoKGM: A Multimodal Large Language Model for Zero-Shot Knowledge Graph Completion in Geospatial Databases

Summary: GeoKGM: multimodal LLM framework for zero-shot geospatial KG completion—self-supervised geospatial encoder plus spatial-feature injection into LLMs and multi-task fine-tuning to enable direct inference on unlabeled geospatial DBs. Uses adversarial implicit alignment for cross-domain robustness and outperforms prior SOTA on four real-world datasets. (summarized by gpt-5-mini on Feb 11 2026)

Paper ID
7392
Venue
SIGMOD
Year
2026
Pagerank
4.1945683e-05
Overall Rank
10,083 | 29.86%
DOI
10.1145/3769796

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