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EcoRAG: A Multi-hop Economic QA Benchmark for Retrieval Augmented Generation Using Knowledge Graphs

A multi-hop economic question answering benchmark for retrieval augmented generation using knowledge graphs.

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EcoRAG: A Multi-hop Economic QA Benchmark for Retrieval Augmented Generation Using Knowledge Graphs

By Hanieh Khorashadizadeh, Sanju Tiwari, Farah Benamara, Nandana Mihindukulasooriya, Jinghua Groppe, Soror Sahri, Morteza Ezzabady, Frédéric IengLecture notes in computer science
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EcoRAG is a benchmark designed to evaluate the performance of retrieval augmented generation models on multi-hop economic question answering tasks. It uses knowledge graphs and aims to improve the accuracy and efficiency of these models.

The benchmark provides a comprehensive evaluation framework for researchers and developers working in this area.

Abstract

EcoRAG is a benchmark designed to evaluate the performance of retrieval augmented generation models on multi-hop economic question answering tasks. It uses knowledge graphs and aims to improve the accuracy and efficiency of these models. The benchmark provides a comprehensive evaluation framework for researchers and developers working in this area.

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multi-hopeconomic qabenchmarkknowledge graphsretrieval augmented generationKnowledge GraphsRetrieval & RAGLarge Language ModelsSemantic Interoperability
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