论文标题
Dimsum @laysumm 20：基于BART的科学文档摘要方法
Dimsum @LaySumm 20: BART-based Approach for Scientific Document Summarization
论文作者
论文摘要
LIE摘要旨在自动生成科学论文的外行摘要。这是一项必不可少的任务，可以增加科学对整个社会的相关性。在本文中，我们基于BART模型构建了一个外行摘要生成系统。我们利用句子标签作为额外的监督信号，以提高外行摘要的性能。在CL-Laysumm 2020共享任务中，我们的模型达到46.00 \％rouge1-f1得分。
Lay summarization aims to generate lay summaries of scientific papers automatically. It is an essential task that can increase the relevance of science for all of society. In this paper, we build a lay summary generation system based on the BART model. We leverage sentence labels as extra supervision signals to improve the performance of lay summarization. In the CL-LaySumm 2020 shared task, our model achieves 46.00\% Rouge1-F1 score.
