CiteSum: Citation Text-guided Scientific Extreme Summarization and Low-resource Domain Adaptation

@article{Mao2022CiteSumCT,
  title={CiteSum: Citation Text-guided Scientific Extreme Summarization and Low-resource Domain Adaptation},
  author={Yuning Mao and Ming Zhong and Jiawei Han},
  journal={ArXiv},
  year={2022},
  volume={abs/2205.06207}
}
Scientific extreme summarization (TLDR) aims to form ultra-short summaries of scientific papers. Previous efforts on curating scientific TLDR datasets failed to scale up due to the heavy human annotation and domain ex-pertise required. In this paper, we propose a simple yet effective approach to automatically extracting TLDR summaries for scientific papers from their citation texts. Based on the proposed approach, we create a new benchmark CiteSum without human annotation, which is around 30 times… 

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