SurveySum: A Dataset for Summarizing Multiple Scientific Articles into a Survey Section
Fuente:
arXiv
Saved in:
| Main Authors: | , , , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866910876334817280 |
|---|---|
| author | Fernandes, Leandro Carísio Guedes, Gustavo Bartz Laitz, Thiago Soares Almeida, Thales Sales Nogueira, Rodrigo Lotufo, Roberto Pereira, Jayr |
| author_facet | Fernandes, Leandro Carísio Guedes, Gustavo Bartz Laitz, Thiago Soares Almeida, Thales Sales Nogueira, Rodrigo Lotufo, Roberto Pereira, Jayr |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2408_16444 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | SurveySum: A Dataset for Summarizing Multiple Scientific Articles into a Survey Section Fernandes, Leandro Carísio Guedes, Gustavo Bartz Laitz, Thiago Soares Almeida, Thales Sales Nogueira, Rodrigo Lotufo, Roberto Pereira, Jayr Computation and Language 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. |
| title | SurveySum: A Dataset for Summarizing Multiple Scientific Articles into a Survey Section |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2408.16444 |