AccurateRAG: A Framework for Building Accurate Retrieval-Augmented Question-Answering Applications
Linh The Nguyen, Chi Tran, Dung Ngoc Nguyen, Van-Cuong Pham, Hoang Ngo, Dat Quoc Nguyen
公開日: 2025/10/2
Abstract
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.