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.
TRIX: A more ex- pressive model for zero-shot domain transfer in knowledge graphs.CoRR, abs/2502.19512
2 Pith papers cite this work. Polarity classification is still indexing.
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A parallel encoding strategy with anchor-conditioned message passing and a merged relation graph allows entity alignment foundation models to generalize to unseen knowledge graphs by shortening the reasoning horizon.
citing papers explorer
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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.
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Breaking the Reasoning Horizon in Entity Alignment Foundation Models
A parallel encoding strategy with anchor-conditioned message passing and a merged relation graph allows entity alignment foundation models to generalize to unseen knowledge graphs by shortening the reasoning horizon.