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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…
Amit Sharma on LinkedIn: #generativeai #rag #finetuning
Chain-Of-Note (CoN) Retrieval For LLMs
Evaluating RAG Applications with Trulens, by zhaozhiming
Harder, Better, Faster, Stronger: 🤖 LLM Hallucination Detection for Real-World RAG, Part I, by Jonathan, Mar, 2024
Fine-Tuning LLMs With Retrieval Augmented Generation (RAG)
Cobus Greyling on LinkedIn: Recently, On LinkedIn I asked what are
RAG Vs Fine-Tuning Vs Both: A Guide For Optimizing LLM Performance - Galileo
Cobus Greyling on LinkedIn: Data Delivery To Large Language Models
Retrieval Augmented Generation at Planet Scale
12 RAG Pain Points and Proposed Solutions, by Wenqi Glantz
Fine-tuning an LLM vs. RAG: What's Best for Your Corporate Chatbot?
Building LLM Applications: Introduction (Part 1), by Abhay Raj Singh
Build Industry-Specific LLMs Using Retrieval Augmented Generation
Cobus Greyling on LinkedIn: Retrieval-Augmented Generation (RAG
12 RAG Pain Points and Proposed Solutions, by Wenqi Glantz