Papers with heterogeneous graph transformers

1 papers
Beyond Text: Incorporating Metadata and Label Structure for Multi-Label Document Classification using Heterogeneous Graphs (2021.emnlp-main)

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Challenge: Existing methods for multi-label document classification ignore the heterogeneous graphical structures of metadata and labels.
Approach: They propose a neural network based approach to multi-label document classification that uses two heterogeneous graphs to model metadata and labels.
Outcome: The proposed approach outperforms state-of-the-art models on two benchmark datasets.

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