@inproceedings{82360b7aa690481b88538203f69e28cc,
title = "Extractive Research Slide Generation Using Windowed Labeling Ranking",
abstract = "Presentation slides describing the content of scientific and technical papers are an efficient and effective way to present that work. However, manually generating presentation slides is labor intensive. We propose a method to automatically generate slides for scientific papers based on a corpus of 5000 paper-slide pairs compiled from conference proceedings websites. The sentence labeling module of our method is based on SummaRuNNer, a neural sequence model for extractive summarization. Instead of ranking sentences based on semantic similarities in the whole document, our algorithm measures importance and novelty of sentences by combining semantic and lexical features within a sentence window. Our method outperforms several baseline methods including SummaRuNNer by a significant margin in terms of ROUGE score.",
author = "Athar Sefid and Jian Wu and Prasenjit Mitra and Giles, {C. Lee}",
note = "Publisher Copyright: {\textcopyright} 2021 Workshop on Scholarly Document Processing; 2nd Workshop on Scholarly Document Processing, SDP 2021 ; Conference date: 10-06-2021",
year = "2021",
language = "English (US)",
series = "2nd Workshop on Scholarly Document Processing, SDP 2021 - Proceedings of the Workshop",
publisher = "Association for Computational Linguistics (ACL)",
pages = "91--96",
editor = "Iz Beltagy and Arman Cohan and Guy Feigenblat and Dayne Freitag and Tirthankar Ghosal and Keith Hall and Drahomira Herrmannova and Petr Knoth and Kyle Lo and Philipp Mayr and Patton, {Robert M.} and Michal Shmueli-Scheuer and {de Waard}, Anita and Kuansan Wang and Wang, {Lucy Lu}",
booktitle = "2nd Workshop on Scholarly Document Processing, SDP 2021 - Proceedings of the Workshop",
}