title: SurveySum: A Dataset for Summarizing Multiple Scientific Articles into a
    Survey Section
summary: Document summarization is a task to shorten texts into concise and
  informative summaries. This paper introduces a novel dataset designed for
  summarizing multiple scientific articles into a section of a survey. Our
  contributions are: (1) SurveySum, a new dataset addressing the gap in
  domain-specific summarization tools; (2) two specific pipelines to summarize
  scientific articles into a section of a survey; and (3) the evaluation of these
  pipelines using multiple metrics to compare their performance. Our results
  highlight the importance of high-quality retrieval stages and the impact of
  different configurations on the quality of generated summaries.
paper_authors._id: 66d58485150d732d6667b038
paper_authors.name: Leandro Carísio Fernandes
paper_authors.status: extracted_confirmed
paper_authors.statusLastChangedAt: 2024-09-02T13:34:14.060Z
paper_authors._id: 644a852eccc39135fb30a1f0
paper_authors.avatarUrl: /avatars/8406cc7927e522279b71c3ca5677f6bc.svg
paper_authors.fullname: Leandro Carísio Fernandes
paper_authors.type: user
paper_authors.user: carisio
paper_authors._id: 66d58485150d732d6667b039
paper_authors.name: Gustavo Bartz Guedes
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2024-09-02T09:37:18.544Z
paper_authors._id: 63d16ce42036e44c44f98446
paper_authors.avatarUrl: /avatars/295e63d8dc90cac8d94d487900ba7aa5.svg
paper_authors.fullname: Gustavo Bartz Guedes
paper_authors.type: user
paper_authors.user: gubartz
paper_authors._id: 66d58485150d732d6667b03a
paper_authors.name: Thiago Soares Laitz
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2024-09-02T09:37:28.013Z
paper_authors._id: 6374f2cbb93cbdf656756c0d
paper_authors.avatarUrl: https://cdn-avatars.huggingface.co/v1/production/uploads/6374f2cbb93cbdf656756c0d/06HKXGWnAWgfgL559EgaN.jpeg
paper_authors.fullname: Thiago Laitz
paper_authors.type: user
paper_authors.user: thiagolaitz
paper_authors._id: 66d58485150d732d6667b03b
paper_authors.name: Thales Sales Almeida
paper_authors._id: 66d58485150d732d6667b03c
paper_authors.name: Rodrigo Nogueira
paper_authors._id: 66d58485150d732d6667b03d
paper_authors.name: Roberto Lotufo
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2024-09-03T07:48:35.532Z
paper_authors._id: 637760cafc2207aa11e25933
paper_authors.avatarUrl: /avatars/ff8a9929e7d3f1b5561dc1359edc8a0b.svg
paper_authors.fullname: Roberto A Lotufo
paper_authors.type: user
paper_authors.user: robertoalotufo
paper_authors._id: 66d58485150d732d6667b03e
paper_authors.name: Jayr Pereira
paper_title: SurveySum: A Dataset for Summarizing Multiple Scientific Articles into a
    Survey Section
paper_summary: Document summarization is a task to shorten texts into concise and
  informative summaries. This paper introduces a novel dataset designed for
  summarizing multiple scientific articles into a section of a survey. Our
  contributions are: (1) SurveySum, a new dataset addressing the gap in
  domain-specific summarization tools; (2) two specific pipelines to summarize
  scientific articles into a section of a survey; and (3) the evaluation of these
  pipelines using multiple metrics to compare their performance. Our results
  highlight the importance of high-quality retrieval stages and the impact of
  different configurations on the quality of generated summaries.
paper_ai_summary: A new dataset and two pipelines for summarizing scientific articles into survey sections are introduced and evaluated, emphasizing the impact of retrieval quality and configuration.
paper_ai_keywords: document summarization domain-specific summarization dataset pipeline evaluation retrieval stages generated summaries