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Half a Link can Be Enough to Predict a Whole Link: Understanding Generalization in Knowledge Graph Foundation Models

A research paper exploring generalization in knowledge graph foundation models.

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Half a Link can Be Enough to Predict a Whole Link: Understanding Generalization in Knowledge Graph Foundation Models

arXiv
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The authors investigate the ability of knowledge graph foundation models to generalize from partial links. They examine whether providing half a link is sufficient for accurate predictions.

The study aims to understand how these models can be improved for more efficient and effective knowledge retrieval.

Abstract

The authors investigate the ability of knowledge graph foundation models to generalize from partial links. They examine whether providing half a link is sufficient for accurate predictions. The study aims to understand how these models can be improved for more efficient and effective knowledge retrieval.

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knowledge graph foundation modelsgeneralization in knowledge graphspartial links predictionknowledge retrieval efficiencyKnowledge GraphsLarge Language ModelsSemantic InteroperabilityOntology & Taxonomy
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