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20242026
most citedGraph Machine Learning in the Era of Large Language Models (LLMs)

5 citations · 6 across the 8 of their papers we have counts for

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cs.LG2026

Learning the Latent Structure: A Feature-Centric Approach to Graph Data Augmentation

Yu Song, Zhigang Hua, Yan Xie +5

Graph-structured data plays a pivotal role in modeling complex relationships. However, real-world graphs are often incomplete due to data collection and observational constraints,…

cs.LG2026

Plain Transformers are Surprisingly Powerful Link Predictors

Quang Truong, Yu Song, Donald Loveland +4

Link prediction is a core challenge in graph machine learning, demanding models that capture rich and complex topological dependencies. While Graph Neural Networks (GNNs) are the s…