Web: http://arxiv.org/abs/2206.10781

June 23, 2022, 1:10 a.m. | Vassilis N. Ioannidis, Xiang Song, Da Zheng, Houyu Zhang, Jun Ma, Yi Xu, Belinda Zeng, Trishul Chilimbi, George Karypis

cs.LG updates on arXiv.org arxiv.org

Can we combine heterogenous graph structure with text to learn high-quality
semantic and behavioural representations? Graph neural networks (GNN)s encode
numerical node attributes and graph structure to achieve impressive performance
in a variety of supervised learning tasks. Current GNN approaches are
challenged by textual features, which typically need to be encoded to a
numerical vector before provided to the GNN that may incur some information
loss. In this paper, we put forth an efficient and effective framework termed
language model …

arxiv graph language lg models network neural neural network training

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