论文标题
抽象性和提取方法的结合，用于总结长科学文本
Combination of abstractive and extractive approaches for summarization of long scientific texts
论文作者
论文摘要
在这项研究工作中，我们提出了一种生成长期科学文档摘要的方法，该文档使用了提取性和抽象方法的优势。在以抽象的方式产生摘要之前，我们执行提取步骤，然后将其用于调节抽象模块。我们为提取器和抽象器都使用了预训练的基于变压器的语言模型。我们的实验表明，使用提取性和抽象模型共同显着改善了汇总结果和胭脂评分。
In this research work, we present a method to generate summaries of long scientific documents that uses the advantages of both extractive and abstractive approaches. Before producing a summary in an abstractive manner, we perform the extractive step, which then is used for conditioning the abstractor module. We used pre-trained transformer-based language models, for both extractor and abstractor. Our experiments showed that using extractive and abstractive models jointly significantly improves summarization results and ROUGE scores.
