SciBERT Sentence Representation for Citation Context Classification

Himanshu Maheshwari; Bhavyajeet Singh; Vasudeva Varma

SciBERT Sentence Representation for Citation Context Classification

Himanshu Maheshwari, Bhavyajeet Singh, Vasudeva Varma

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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:
Bibkey:
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)
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PDF:: https://aclanthology.org/2021.sdp-1.17.pdf

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@inproceedings{maheshwari-etal-2021-scibert,
    title = "{S}ci{BERT} Sentence Representation for Citation Context Classification",
    author = "Maheshwari, Himanshu  and
      Singh, Bhavyajeet  and
      Varma, Vasudeva",
    editor = "Beltagy, Iz  and
      Cohan, Arman  and
      Feigenblat, Guy  and
      Freitag, Dayne  and
      Ghosal, Tirthankar  and
      Hall, Keith  and
      Herrmannova, Drahomira  and
      Knoth, Petr  and
      Lo, Kyle  and
      Mayr, Philipp  and
      Patton, Robert M.  and
      Shmueli-Scheuer, Michal  and
      de Waard, Anita  and
      Wang, Kuansan  and
      Wang, Lucy Lu",
    booktitle = "Proceedings of the Second Workshop on Scholarly Document Processing",
    month = jun,
    year = "2021",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2021.sdp-1.17/",
    pages = "130--133",
    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."
}

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%0 Conference Proceedings
%T SciBERT Sentence Representation for Citation Context Classification
%A Maheshwari, Himanshu
%A Singh, Bhavyajeet
%A Varma, Vasudeva
%Y Beltagy, Iz
%Y Cohan, Arman
%Y Feigenblat, Guy
%Y Freitag, Dayne
%Y Ghosal, Tirthankar
%Y Hall, Keith
%Y Herrmannova, Drahomira
%Y Knoth, Petr
%Y Lo, Kyle
%Y Mayr, Philipp
%Y Patton, Robert M.
%Y Shmueli-Scheuer, Michal
%Y de Waard, Anita
%Y Wang, Kuansan
%Y Wang, Lucy Lu
%S Proceedings of the Second Workshop on Scholarly Document Processing
%D 2021
%8 June
%I Association for Computational Linguistics
%C Online
%F maheshwari-etal-2021-scibert
%X 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.
%U https://aclanthology.org/2021.sdp-1.17/
%P 130-133

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Markdown (Informal)

[SciBERT Sentence Representation for Citation Context Classification](https://aclanthology.org/2021.sdp-1.17/) (Maheshwari et al., sdp 2021)

SciBERT Sentence Representation for Citation Context Classification (Maheshwari et al., sdp 2021)

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.