Papers by Arvindh Arun

1 papers
SEMMA: A Semantic Aware Knowledge Graph Foundation Model (2025.emnlp-main)

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Challenge: Existing Knowledge Graph Foundation Models (KGFMs) rely on graph structure, overlooking the rich semantic signals encoded in textual attributes.
Approach: They propose a dual-module KGFM that integrates transferable textual semantics alongside structure to generate relation identifiers.
Outcome: The proposed model outperforms ULTRA and ULtra in fully inductive link prediction in more challenging generalization settings.

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