Abstract
This paper describes our system (IREL) for 3C-Citation Context Classification shared task of the Scholarly Document Processing Workshop at NAACL 2021. We participated in both subtask A and subtask B. Our best system achieved a Macro F1 score of 0.26973 on the private leaderboard for subtask A and was ranked one. For subtask B our best system achieved a Macro F1 score of 0.59071 on the private leaderboard and was ranked two. We used similar models for both the subtasks with some minor changes, as discussed in this paper. Our best performing model for both the subtask was a finetuned SciBert model followed by a linear layer. This paper provides a detailed description of all the approaches we tried and their results.- Anthology ID:
- 2021.sdp-1.17
- Volume:
- Proceedings of the Second Workshop on Scholarly Document Processing
- Month:
- June
- Year:
- 2021
- Address:
- Online
- Editors:
- Iz Beltagy, Arman Cohan, Guy Feigenblat, Dayne Freitag, Tirthankar Ghosal, Keith Hall, Drahomira Herrmannova, Petr Knoth, Kyle Lo, Philipp Mayr, Robert M. Patton, Michal Shmueli-Scheuer, Anita de Waard, Kuansan Wang, Lucy Lu Wang
- Venue:
- sdp
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 130–133
- Language:
- URL:
- https://aclanthology.org/2021.sdp-1.17
- DOI:
- Cite (ACL):
- Himanshu Maheshwari, Bhavyajeet Singh, and Vasudeva Varma. 2021. SciBERT Sentence Representation for Citation Context Classification. In Proceedings of the Second Workshop on Scholarly Document Processing, pages 130–133, Online. Association for Computational Linguistics.
- Cite (Informal):
- SciBERT Sentence Representation for Citation Context Classification (Maheshwari et al., sdp 2021)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-3/2021.sdp-1.17.pdf