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Bridging Semantics and Structure: A Theoretically Grounded Framework for Link Prediction on TAGs
Link prediction on text-attributed graphs (TAGs) is a fundamental problem with applications in knowledge discovery, recommendation and beyond. Recent progress has highlighted the promise of combining Graph Neural Networks (GNNs) with Language Models (LMs) in order to leverage the complementary struc
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