SurveySum: A Dataset for Summarizing Multiple Scientific Articles into a Survey Section

Gustavo Bartz Guedes; Jayr Pereira; Leandro Car\'isio Fernandes; Roberto Lotufo; Rodrigo Nogueira; Thales Sales Almeida; Thiago Soares Laitz

SurveySum: A Dataset for Summarizing Multiple Scientific Articles into a Survey Section

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arxiv 2408.16444 v1 pith:QKLEP2WJ submitted 2024-08-29 cs.CL

Leandro Carísio Fernandes , Gustavo Bartz Guedes , Thiago Soares Laitz , Thales Sales Almeida , Rodrigo Nogueira , Roberto Lotufo , Jayr Pereira This is my paper · ORCID

classification cs.CL

keywords articlesdatasetmultiplescientificsectionsurveypipelinessummaries

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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.

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Ask, Retrieve, Summarize: A Modular Pipeline for Scientific Literature Summarization
cs.CL 2025-05 conditional novelty 4.0 of 10

XSum, a question-generation plus editor RAG pipeline, produces survey-style summaries from multiple scientific papers and reports improved scores on the SurveySum benchmark.

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