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.- Anthology ID:
- 2020.sdp-1.34
- Volume:
- Proceedings of the First Workshop on Scholarly Document Processing
- Month:
- November
- Year:
- 2020
- Address:
- Online
- Venue:
- sdp
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 297–302
- Language:
- URL:
- https://aclanthology.org/2020.sdp-1.34
- DOI:
- 10.18653/v1/2020.sdp-1.34
- Cite (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.
- Cite (Informal):
- CiteQA@CLSciSumm 2020 (Umapathy et al., sdp 2020)
- PDF:
- https://preview.aclanthology.org/ingestion-script-update/2020.sdp-1.34.pdf
- Data
- ScisummNet