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Self-supervised Guided Hypergraph Feature Propagation for Semi-supervised Classification with Missing Node Features
Some recent methods have been proposed to reconstruct the missing node features by the information propagation among nodes with known and unknown attributes.
Modelling the semantics of text in complex document layouts using graph transformer networks
Representing structured text from complex documents typically calls for different machine learning techniques, such as language models for paragraphs and convolutional neural networks (CNNs) for table extraction, which prohibits drawing links between text spans from different content types.
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