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Elasticsearch-Enhanced RAG for QA Systems by lilkangbose is a document available to read on EtoBox.

This study explores the integration of Elasticsearch into the Retrieval-Augmented Generation (RAG) framework to enhance the accuracy and quality of question-answering systems. The proposed ES-RAG method demonstrates significant improvements in retrieval efficiency and accuracy compared to traditional methods like TF-IDF-RAG and BM25-RAG, particularly in handling complex queries. Future research will focus on optimizing the interaction between Elasticsearch and large language models to further enhance the qu

Author

lilkangbose

Language

EN