KGFMs can predict links using observed half-links, with performance varying across four scenarios of half-link visibility in inference graphs.
An open challenge for inductive link prediction on knowledge graphs.arXiv preprint arXiv:2203.01520, 2022
2 Pith papers cite this work, alongside 11 external citations. Polarity classification is still indexing.
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UNVERDICTED 2representative citing papers
KGPFN pretrains on multiple KGs to learn relation patterns, then performs query-specific reasoning by encoding local context with NBFNet and global context via retrieved instances aggregated in a PFN with feature- and sample-level attention.
citing papers explorer
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Half a Link can Be Enough to Predict a Whole Link: Understanding Generalization in Knowledge Graph Foundation Models
KGFMs can predict links using observed half-links, with performance varying across four scenarios of half-link visibility in inference graphs.
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KGPFN: Unlocking the Potential of Knowledge Graph Foundation Model via In-Context Learning
KGPFN pretrains on multiple KGs to learn relation patterns, then performs query-specific reasoning by encoding local context with NBFNet and global context via retrieved instances aggregated in a PFN with feature- and sample-level attention.