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.appComment: Accepted at ACL 2023 System Demonstratio