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

By A Mystery Man Writer

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…

Steps In Evaluating Retrieval Augmented Generation (RAG) Pipelines, by Cobus Greyling

Retrieval augmented generation (RAG) explained [+ examples]

RAG Evaluation

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

Retrieval Augmented Generation (RAG) Safeguards Against LLM Hallucination

Evaluating RAG Metrics Across Different Retrieval Methods, by Harpreet Sahota, Feb, 2024

Cobus Greyling on LinkedIn: Retrieval Augmented Generation (RAG) Safeguards Against LLM Hallucination

Scale AI on X: Retrieval Augmented Generation (RAG) vs Fine-tuning is a false dichotomy. These two techniques are complementary not in competition. In fact, they're often needed together. For example, a tax lawyer needs both specialized training (fine

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

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

A New Study Compares RAG & Fine-Tuning For Knowledge Base Use-Cases