RAG Methodology Guide

Design and implement Retrieval-Augmented Generation (RAG) systems for academic research, including document chunking, embedding strategies, retrieval pipelines, and evaluation.

What Is RAG?

Retrieval-Augmented Generation (RAG) augments a language model's generation with relevant information retrieved from an external knowledge base. For academic research, this enables:

• Question answering over a personal paper library
• Literature synthesis across hundreds of papers
• Fact-checking claims against source documents
• Generating citations with provenance

RAG Pipeline Architecture