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20202024
most citedIGB: Addressing The Gaps In Labeling, Features, Heterogeneity, and Size of Public Graph Datasets for Deep Learning Research

37 citations · 169 across the 20 of their papers we have counts for

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2 papers · 1 filter

cs.CL2024

Parameter-Efficient Tuning Large Language Models for Graph Representation Learning

Qi Zhu, Da Zheng, Xiang Song +4

Text-rich graphs, which exhibit rich textual information on nodes and edges, are prevalent across a wide range of real-world business applications. Large Language Models (LLMs) hav…

cs.CL2023★ 1 cited

Graph-Aware Language Model Pre-Training on a Large Graph Corpus Can Help Multiple Graph Applications

Han Xie, Da Zheng, Jun Ma +9

Model pre-training on large text corpora has been demonstrated effective for various downstream applications in the NLP domain. In the graph mining domain, a similar analogy can be…