NS3 approximates joint ranking for EFO_k queries on KGs by merging free variables into hypernodes, pruning domains with dynamic budget B, and reducing to EFO_{k-1} queries, improving joint performance on three datasets while releasing a k=3 joint-ranking benchmark.
Top ten challenges towards agentic neural graph databases.arXiv preprint arXiv:2501.14224, 2025
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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.
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Neural Scalable Symbolic Search Framework for Complex Logical Queries with Multiple Free Variables
NS3 approximates joint ranking for EFO_k queries on KGs by merging free variables into hypernodes, pruning domains with dynamic budget B, and reducing to EFO_{k-1} queries, improving joint performance on three datasets while releasing a k=3 joint-ranking benchmark.
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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.