InPars Toolkit: A Unified and Reproducible Synthetic Data Generation Pipeline for Neural Information Retrieval

Recent work has explored Large Language Models (LLMs) to overcome the lack of training data for Information Retrieval (IR) tasks. The generalization abilities of these models have enabled the creation of synthetic in-domain data by providing instructions and a few examples on a prompt. InPars and Pr...

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Bibliographische Detailangaben

Hauptverfasser:	Abonizio, Hugo, Bonifacio, Luiz, Jeronymo, Vitor, Lotufo, Roberto, Zavrel, Jakub, Nogueira, Rodrigo
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Information Retrieval
Online-Zugang:	Volltext bestellen
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