AccurateRAG: A Framework for Building Accurate Retrieval-Augmented Question-Answering Applications

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Hauptverfasser: Nguyen, Linh The, Tran, Chi, Nguyen, Dung Ngoc, Pham, Van-Cuong, Ngo, Hoang, Nguyen, Dat Quoc
Format: Preprint
Veröffentlicht: 2025
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author Nguyen, Linh The
Tran, Chi
Nguyen, Dung Ngoc
Pham, Van-Cuong
Ngo, Hoang
Nguyen, Dat Quoc
author_facet Nguyen, Linh The
Tran, Chi
Nguyen, Dung Ngoc
Pham, Van-Cuong
Ngo, Hoang
Nguyen, Dat Quoc
contents We introduce AccurateRAG -- a novel framework for constructing high-performance question-answering applications based on retrieval-augmented generation (RAG). Our framework offers a pipeline for development efficiency with tools for raw dataset processing, fine-tuning data generation, text embedding & LLM fine-tuning, output evaluation, and building RAG systems locally. Experimental results show that our framework outperforms previous strong baselines and obtains new state-of-the-art question-answering performance on benchmark datasets.
format Preprint
id arxiv_https___arxiv_org_abs_2510_02243
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle AccurateRAG: A Framework for Building Accurate Retrieval-Augmented Question-Answering Applications
Nguyen, Linh The
Tran, Chi
Nguyen, Dung Ngoc
Pham, Van-Cuong
Ngo, Hoang
Nguyen, Dat Quoc
Computation and Language
We introduce AccurateRAG -- a novel framework for constructing high-performance question-answering applications based on retrieval-augmented generation (RAG). Our framework offers a pipeline for development efficiency with tools for raw dataset processing, fine-tuning data generation, text embedding & LLM fine-tuning, output evaluation, and building RAG systems locally. Experimental results show that our framework outperforms previous strong baselines and obtains new state-of-the-art question-answering performance on benchmark datasets.
title AccurateRAG: A Framework for Building Accurate Retrieval-Augmented Question-Answering Applications
topic Computation and Language
url https://arxiv.org/abs/2510.02243