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Cutting Through the Clutter: The Potential of LLMs for Efficient Filtration in Systematic Literature Reviews

Fuente: arXiv

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Dettagli Bibliografici
Autori principali:	Joos, Lucas, Keim, Daniel A., Fischer, Maximilian T.
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning Digital Libraries Human-Computer Interaction H.5.2
Accesso online:	Acceder al recurso
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