Fine-Tuning LLMs With Retrieval Augmented Generation (RAG), by Cobus Greyling

This approach is a novel implementation of RAG called RA-DIT (Retrieval Augmented Dual Instruction Tuning) where the RAG dataset (query, context retrieved and response) is used to to fine-tune a LLM…

Specializing LLMs for Domains: RAG 🧵vs. Fine-Tuning ⚡

RAG — Retrieval Augmented Generation, by Cobus Greyling

Retrieval-Augmented Generation: How to Use Your Data to Guide LLMs

Knowledge Graphs & LLMs: Fine-Tuning vs. Retrieval-Augmented

Advanced RAG 01: Problems of Naive RAG

How to improve RAG results in your LLM apps: from basics to advanced, by Guodong (Troy) Zhao

Retrieval Augmented Generation (RAG) Safeguards Against LLM Hallucination

Chain-Of-Note (CoN) Retrieval For LLMs

RAG vs. Fine-tuning: Here's the Detailed Comparison

A Gentle Introduction to Retrieval Augmented Generation (RAG)

How ChatGPT really works, explained for non-technical people, by Guodong (Troy) Zhao

Hopsworks Solution - Fine-Tuning LLMs & RAG for GenAI

Retrieval augmented generation: Keeping LLMs relevant and current