Abstract
Scientific writing involves retrieving, summarizing, and citing relevant papers, which can be time-consuming processes. Although in many workflows these processes are serially linked, there are opportunities for natural language processing (NLP) to provide end-to-end assistive tools. We propose SciLit, a pipeline that automatically recommends relevant papers, extracts highlights, and suggests a reference sentence as a citation of a paper, taking into consideration the user-provided context and keywords. SciLit efficiently recommends papers from large databases of hundreds of millions of papers using a two-stage pre-fetching and re-ranking literature search system that flexibly deals with addition and removal of a paper database. We provide a convenient user interface that displays the recommended papers as extractive summaries and that offers abstractively-generated citing sentences which are aligned with the provided context and which mention the chosen keyword(s). Our assistive tool for literature discovery and scientific writing is available at https://scilit.vercel.app- Anthology ID:
- 2023.acl-demo.22
- Volume:
- Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations)
- Month:
- July
- Year:
- 2023
- Address:
- Toronto, Canada
- Editors:
- Danushka Bollegala, Ruihong Huang, Alan Ritter
- Venue:
- ACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 235–246
- Language:
- URL:
- https://aclanthology.org/2023.acl-demo.22
- DOI:
- 10.18653/v1/2023.acl-demo.22
- Cite (ACL):
- Nianlong Gu and Richard H.R. Hahnloser. 2023. SciLit: A Platform for Joint Scientific Literature Discovery, Summarization and Citation Generation. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations), pages 235–246, Toronto, Canada. Association for Computational Linguistics.
- Cite (Informal):
- SciLit: A Platform for Joint Scientific Literature Discovery, Summarization and Citation Generation (Gu & Hahnloser, ACL 2023)
- PDF:
- https://preview.aclanthology.org/naacl24-info/2023.acl-demo.22.pdf