Papers by Marco Ferdinand Salchner

1 papers
A Survey of Automatic Text Summarization Using Graph Neural Networks (2022.coling-1)

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Challenge: Abstractive ATS involves generating factually correct and fluent sentences.
Approach: They provide an overview of the use of graph neural networks (GNNs) for automatic text summarization.
Outcome: The proposed model is based on a set of graph neural networks (GNNs) that are used to generate a concise, correct and fluent summary of a given text.

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