Compare: A Framework for Scientific Comparisons
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arXiv
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| Auteurs principaux: | , , , , , |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866914027430477824 |
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| author | Staudinger, Moritz Kusa, Wojciech Cancellieri, Matteo Pride, David Knoth, Petr Hanbury, Allan |
| author_facet | Staudinger, Moritz Kusa, Wojciech Cancellieri, Matteo Pride, David Knoth, Petr Hanbury, Allan |
| contents | Navigating the vast and rapidly increasing sea of academic publications to identify institutional synergies, benchmark research contributions and pinpoint key research contributions has become an increasingly daunting task, especially with the current exponential increase in new publications. Existing tools provide useful overviews or single-document insights, but none supports structured, qualitative comparisons across institutions or publications.
To address this, we demonstrate Compare, a novel framework that tackles this challenge by enabling sophisticated long-context comparisons of scientific contributions. Compare empowers users to explore and analyze research overlaps and differences at both the institutional and publication granularity, all driven by user-defined questions and automatic retrieval over online resources. For this we leverage on Retrieval-Augmented Generation over evolving data sources to foster long context knowledge synthesis. Unlike traditional scientometric tools, Compare goes beyond quantitative indicators by providing qualitative, citation-supported comparisons. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_06412 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Compare: A Framework for Scientific Comparisons Staudinger, Moritz Kusa, Wojciech Cancellieri, Matteo Pride, David Knoth, Petr Hanbury, Allan Digital Libraries Information Retrieval Navigating the vast and rapidly increasing sea of academic publications to identify institutional synergies, benchmark research contributions and pinpoint key research contributions has become an increasingly daunting task, especially with the current exponential increase in new publications. Existing tools provide useful overviews or single-document insights, but none supports structured, qualitative comparisons across institutions or publications. To address this, we demonstrate Compare, a novel framework that tackles this challenge by enabling sophisticated long-context comparisons of scientific contributions. Compare empowers users to explore and analyze research overlaps and differences at both the institutional and publication granularity, all driven by user-defined questions and automatic retrieval over online resources. For this we leverage on Retrieval-Augmented Generation over evolving data sources to foster long context knowledge synthesis. Unlike traditional scientometric tools, Compare goes beyond quantitative indicators by providing qualitative, citation-supported comparisons. |
| title | Compare: A Framework for Scientific Comparisons |
| topic | Digital Libraries Information Retrieval |
| url | https://arxiv.org/abs/2509.06412 |