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…

RAG Vs Fine tuning Vs Both. Introduction, by Ramprasath S

Fine-Tuning GPT-3.5 RAG Pipeline with GPT-4 Training Data

NEFTune”: Discover How Noisy Embeddings Act as Catalyst to Improve Instruction Finetuning!, by AI TutorMaster

Cobus Greyling on LinkedIn: LLM Drift

Self-Reflective Retrieval-Augmented Generation (SELF-RAG), by Cobus Greyling, Mar, 2024

RAT — Retrieval Augmented Thoughts, by Cobus Greyling

Cobus Greyling on LinkedIn: Data Delivery can be best described as the process of imbuing one or more…

Fine-Tuning LLMs With Retrieval Augmented Generation (RAG)

Introduction To Retrieval Augmented Generation - Arize AI

RAG Vs Fine tuning Vs Both. Introduction, by Ramprasath S

Retrieval Augmented Generation (RAG) Safeguards Against LLM Hallucination

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