Fine-Tuning LLMs With Retrieval Augmented Generation (RAG)

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…

RAG vs Finetuning — Which Is the Best Tool to Boost Your LLM Application?, by Heiko Hotz

Retrieval-augmented generation. A working example for adding private…, by Mike Shwe

Fine Tuning or Retrieval Augmented Generation (RAG), That Is the Question, by Peng Liu, Mar, 2024

List: Building using LLMs, Curated by Dhruvajyoti Sarma

High-Level Concepts - LlamaIndex

List: LLM, Curated by CP Lu, PhD

Knowledge Graphs & LLMs: Fine-Tuning vs. Retrieval-Augmented Generation - Graph Database & Analytics

The Power of Retrieval Augmented Generation (RAG) LLM-based Academic Search Engines

Retrieval Augmented Generation: Refine LLM Responses with RAG — Elastic Search Labs

Giovanni Lima on LinkedIn: Fine-Tuning LLMs With Retrieval Augmented Generation (RAG)

Bruno Vicente on LinkedIn: Customer: Garsa