SciLit: A Platform for Joint Scientific Literature Discovery, Summarization and Citation Generation

• URL: http://arxiv.org/abs/2306.03535v2
• Date: Mon, 6 Nov 2023 15:53:23 GMT
• Title: SciLit: A Platform for Joint Scientific Literature Discovery, Summarization and Citation Generation
• Authors: Nianlong Gu, Richard H.R. Hahnloser
• Abstract summary: We propose SciLit, a pipeline that automatically recommends relevant papers, extracts highlights, and suggests a reference sentence as a citation of a paper. 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.
• Score: 11.186252009101077
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Scientific writing involves retrieving, summarizing, and citing relevant papers, which can be time-consuming processes in large and rapidly evolving fields. By making these processes inter-operable, natural language processing (NLP) provides opportunities for creating end-to-end assistive writing 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

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