Conceptual framework for analyzing RAG techniques
In brief
- A conceptual framework to classify RAG techniques is proposed.
- It enables filtering suitable methods before expensive empirical tests.
- The goal is to reduce hallucinations and improve LLM performance.
A conceptual framework is introduced to characterize and evaluate Retrieval-Augmented Generation (RAG) techniques. It aims to help researchers and practitioners select the most suitable methods before costly empirical testing.
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