Task Definition and Integration For Scientific-Document Writing Support

Hiromi Narimatsu, Kohei Koyama, Kohji Dohsaka, Ryuichiro Higashinaka, Yasuhiro Minami, Hirotoshi Taira


Abstract
With the increase in the number of published academic papers, growing expectations have been placed on research related to supporting the writing process of scientific papers. Recently, research has been conducted on various tasks such as citation worthiness (judging whether a sentence requires citation), citation recommendation, and citation-text generation. However, since each task has been studied and evaluated using data that has been independently developed, it is currently impossible to verify whether such tasks can be successfully pipelined to effective use in scientific-document writing. In this paper, we first define a series of tasks related to scientific-document writing that can be pipelined. Then, we create a dataset of academic papers that can be used for the evaluation of each task as well as a series of these tasks. Finally, using the dataset, we evaluate the tasks of citation worthiness and citation recommendation as well as both of these tasks integrated. The results of our evaluations show that the proposed approach is promising.
Anthology ID:
2021.sdp-1.3
Volume:
Proceedings of the Second Workshop on Scholarly Document Processing
Month:
June
Year:
2021
Address:
Online
Venues:
NAACL | sdp
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
18–26
Language:
URL:
https://aclanthology.org/2021.sdp-1.3
DOI:
10.18653/v1/2021.sdp-1.3
Bibkey:
Cite (ACL):
Hiromi Narimatsu, Kohei Koyama, Kohji Dohsaka, Ryuichiro Higashinaka, Yasuhiro Minami, and Hirotoshi Taira. 2021. Task Definition and Integration For Scientific-Document Writing Support. In Proceedings of the Second Workshop on Scholarly Document Processing, pages 18–26, Online. Association for Computational Linguistics.
Cite (Informal):
Task Definition and Integration For Scientific-Document Writing Support (Narimatsu et al., sdp 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.sdp-1.3.pdf
Code
 citation-minami-lab/citation-dataset