English

Dimsum @LaySumm 20: BART-based Approach for Scientific Document Summarization

Computation and Language 2020-10-20 v1

Abstract

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.

Keywords

Cite

@article{arxiv.2010.09252,
  title  = {Dimsum @LaySumm 20: BART-based Approach for Scientific Document Summarization},
  author = {Tiezheng Yu and Dan Su and Wenliang Dai and Pascale Fung},
  journal= {arXiv preprint arXiv:2010.09252},
  year   = {2020}
}

Comments

4 pages

R2 v1 2026-06-23T19:26:30.228Z