AIBullisharXiv – CS AI · 3h ago7/10
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RAGe: A Retrieval-Augmented Generation Evaluation Framework
Researchers introduce RAGe, a benchmarking framework designed to optimize Retrieval-Augmented Generation (RAG) applications by evaluating trade-offs between accuracy, efficiency, and scalability. The framework enables developers to identify optimal pipeline components for domain-specific datasets while accounting for hardware constraints, making RAG development more accessible on consumer-grade hardware.