Structured Summarization of Academic Publications
This work addresses the need for structured summarization in academic publications, offering an incremental improvement over existing methods.
The authors tackled the problem of generating structured summaries for academic articles by proposing SUSIE, a method that enhances existing summarization models, and created a new dataset PMC-SA, achieving performance improvements of up to 4 ROUGE points.
We propose SUSIE, a novel summarization method that can work with state-of-the-art summarization models in order to produce structured scientific summaries for academic articles. We also created PMC-SA, a new dataset of academic publications, suitable for the task of structured summarization with neural networks. We apply SUSIE combined with three different summarization models on the new PMC-SA dataset and we show that the proposed method improves the performance of all models by as much as 4 ROUGE points.