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<p>The rapid expansion of scientific publications poses a significant challenge for researchers who need to stay updated on recent advancements and efficiently extract crucial information. Summarizing scientific documents can address this challenge by providing concise overviews that highlight the main contributions of the original texts. This study introduces a cutting-edge deep learning approach that employs the sBERT model to enhance the accuracy and relevance of document summaries. Our method treats extractive summarization as a classification task, implementing a dual BERT model configuration to effectively pinpoint and extract critical information. Tested on the CL-SciSumm dataset, our approach demonstrates marked improvements over existing techniques, achieving higher ROUGE scores. These results affirm the potential of our model to generate accurate and dependable summaries, assisting researchers in managing and interpreting the growing volume of scientific literature.</p>

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Deep Learning-Based Scientific Document Summarization Considering Citation

  • 期刊论文

  • 发表日期：

    2025年3月19日

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  • Divya Jyoti,
  • Dharmendra Prasad Mahato,
  • Jyoti Srivastava

摘要

The rapid expansion of scientific publications poses a significant challenge for researchers who need to stay updated on recent advancements and efficiently extract crucial information. Summarizing scientific documents can address this challenge by providing concise overviews that highlight the main contributions of the original texts. This study introduces a cutting-edge deep learning approach that employs the sBERT model to enhance the accuracy and relevance of document summaries. Our method treats extractive summarization as a classification task, implementing a dual BERT model configuration to effectively pinpoint and extract critical information. Tested on the CL-SciSumm dataset, our approach demonstrates marked improvements over existing techniques, achieving higher ROUGE scores. These results affirm the potential of our model to generate accurate and dependable summaries, assisting researchers in managing and interpreting the growing volume of scientific literature.