Retrieval-Augmented Generation (RAG) vs LLM Fine-Tuning, by Cobus Greyling

RAG is known for improving accuracy via in-context learning and is very affective where context is important. RAG is easier to implement and often serves as a first foray into implementing LLMs due…

12 Retrieval Augmented Generation (RAG) Tools / Software in '23

Cobus Greyling on LinkedIn: Retrieval-Augmented Generation (RAG) vs LLM Fine -Tuning The two most…

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

Tuning the RAG Symphony: A guide to evaluating LLMs, by Sebastian Wehkamp, Feb, 2024

A Practitioners Guide to Retrieval Augmented Generation (RAG), by Cameron R. Wolfe, Ph.D., Mar, 2024

Revolutionizing AI with Multimodal Large Language Models: Introducing OneLLM, by Saleh Alkhalifa, Jan, 2024

T-RAG = RAG + Fine-Tuning + Entity Detection

Retrieval Augmented Generation (RAG) versus Fine Tuning in LLM Workflows

Enhancing LLMs with Retrieval-Augmented Generation

Which is better, retrieval augmentation (RAG) or fine-tuning? Both.

Retrieval-Augmented Generation (RAG) vs LLM Fine-Tuning, by Cobus Greyling

Harnessing Retrieval Augmented Generation With Langchain, by Amogh Agastya

Retrieval-Augmented Generation (RAG) vs LLM Fine-Tuning, by Cobus Greyling

Evaluating RAG Applications with Trulens, by zhaozhiming, Feb, 2024