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

Nianlong Gu, Richard H. R. Hahnloser
6/6/2023
cs.CL

No official code found. Best implementation: nianlonggu/SciLit (10 stars, Apache-2.0, last commit 2025-01-29).

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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Code Implementations(1)

nianlonggu/SciLitCommunity100%
Apache-2.0

ACL23 Demo SciLit: A Platform for Joint Scientific Literature Discovery, Summarization and Citation Generation

101CSS, HTMLMay 26, 20231 years agoApache-2.0
acl2023demo

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Cite this paper

@article{gu2023scilit,
  title  = {SciLit: A Platform for Joint Scientific Literature Discovery, Summarization and Citation Generation},
  author = {Nianlong Gu and Richard H. R. Hahnloser},
  year   = {2023},
  eprint = {2306.03535},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2306.03535v2}
}

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