Papers with structure-augmented modeling

1 papers
Bridging Local Details and Global Context in Text-Attributed Graphs (2024.emnlp-main)

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Challenge: Existing studies focus on combining different information levels but overlook interconnections, i.e., contextual textual information among nodes.
Approach: They propose a framework that bridges local and global perspectives by leveraging contextual textual information.
Outcome: The proposed framework achieves state-of-the-art performance while reducing tokens significantly.

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