@inproceedings{umapathy-etal-2020-citeqa,
title = "{C}ite{QA}@{CLS}ci{S}umm 2020",
author = "Umapathy, Anjana and
Radhakrishnan, Karthik and
Jain, Kinjal and
Singh, Rahul",
editor = "Chandrasekaran, Muthu Kumar and
de Waard, Anita and
Feigenblat, Guy and
Freitag, Dayne and
Ghosal, Tirthankar and
Hovy, Eduard and
Knoth, Petr and
Konopnicki, David and
Mayr, Philipp and
Patton, Robert M. and
Shmueli-Scheuer, Michal",
booktitle = "Proceedings of the First Workshop on Scholarly Document Processing",
month = nov,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.sdp-1.34",
doi = "10.18653/v1/2020.sdp-1.34",
pages = "297--302",
abstract = "In academic publications, citations are used to build context for a concept by highlighting relevant aspects from reference papers. Automatically identifying referenced snippets can help researchers swiftly isolate principal contributions of scientific works. In this paper, we exploit the underlying structure of scientific articles to predict reference paper spans and facets corresponding to a citation. We propose two methods to detect citation spans - keyphrase overlap, BERT along with structural priors. We fine-tune FastText embeddings and leverage textual, positional features to predict citation facets.",
}
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<abstract>In academic publications, citations are used to build context for a concept by highlighting relevant aspects from reference papers. Automatically identifying referenced snippets can help researchers swiftly isolate principal contributions of scientific works. In this paper, we exploit the underlying structure of scientific articles to predict reference paper spans and facets corresponding to a citation. We propose two methods to detect citation spans - keyphrase overlap, BERT along with structural priors. We fine-tune FastText embeddings and leverage textual, positional features to predict citation facets.</abstract>
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%0 Conference Proceedings
%T CiteQA@CLSciSumm 2020
%A Umapathy, Anjana
%A Radhakrishnan, Karthik
%A Jain, Kinjal
%A Singh, Rahul
%Y Chandrasekaran, Muthu Kumar
%Y de Waard, Anita
%Y Feigenblat, Guy
%Y Freitag, Dayne
%Y Ghosal, Tirthankar
%Y Hovy, Eduard
%Y Knoth, Petr
%Y Konopnicki, David
%Y Mayr, Philipp
%Y Patton, Robert M.
%Y Shmueli-Scheuer, Michal
%S Proceedings of the First Workshop on Scholarly Document Processing
%D 2020
%8 November
%I Association for Computational Linguistics
%C Online
%F umapathy-etal-2020-citeqa
%X In academic publications, citations are used to build context for a concept by highlighting relevant aspects from reference papers. Automatically identifying referenced snippets can help researchers swiftly isolate principal contributions of scientific works. In this paper, we exploit the underlying structure of scientific articles to predict reference paper spans and facets corresponding to a citation. We propose two methods to detect citation spans - keyphrase overlap, BERT along with structural priors. We fine-tune FastText embeddings and leverage textual, positional features to predict citation facets.
%R 10.18653/v1/2020.sdp-1.34
%U https://aclanthology.org/2020.sdp-1.34
%U https://doi.org/10.18653/v1/2020.sdp-1.34
%P 297-302
Markdown (Informal)
[CiteQA@CLSciSumm 2020](https://aclanthology.org/2020.sdp-1.34) (Umapathy et al., sdp 2020)
ACL
- Anjana Umapathy, Karthik Radhakrishnan, Kinjal Jain, and Rahul Singh. 2020. CiteQA@CLSciSumm 2020. In Proceedings of the First Workshop on Scholarly Document Processing, pages 297–302, Online. Association for Computational Linguistics.