@inproceedings{8e71b09947934426aa6b595d8cd6a74c,
title = "Argument Mining for Scholarly Document Processing: Taking Stock and Looking Ahead",
abstract = "Argument mining targets structures in natural language related to interpretation and persuasion. Most scholarly discourse involves interpreting experimental evidence and attempting to persuade other scientists to adopt the same conclusions, which could benefit from argument mining techniques. However, While various argument mining studies have addressed student essays and news articles, those that target scientific discourse are still scarce. This paper surveys existing work in argument mining of scholarly discourse, and provides an overview of current models, data, tasks, and applications. We identify a number of key challenges confronting argument mining in the scientific domain, and suggest some possible solutions and future directions.",
author = "Khalid Al-Khatib and Tirthankar Ghosal and Yufang Hou and {De Waard}, Anita and Dayne Freitag",
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",
series = "2nd Workshop on Scholarly Document Processing, SDP 2021 - Proceedings of the Workshop",
publisher = "Association for Computational Linguistics (ACL)",
pages = "56--65",
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",
address = "United States",
}