Papers with Graph-based Supervised Summarizationmodel

1 papers
Scientific Paper Extractive Summarization Enhanced by Citation Graphs (2022.emnlp-main)

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Challenge: citation graphs can be used to extract scientific papers under different conditions.
Approach: They propose a multi-granularity unsupervised summarization model that fine tunes a pre-trained encoder model on the citation graph by link prediction tasks.
Outcome: The proposed model outperforms baseline models on a public benchmark dataset.

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