#rag
1 note or post, 10 links.
Notes and posts
RAG
RAG is an AI framework for retrieving facts from an external knowledge base to ground large language models (LLMs) on the most accurate, up-to-date information and to give users insight into LLMs' generative process…
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From zero to a RAG system: successes and failures | Andros Fenollosa
Data Modeling for RAG That Works - by Alexandru Vesa
[2312.10997] Retrieval-Augmented Generation for Large Language Models: A Survey
Learnings from ingesting millions of technical pages for RAG on Azure. | Jakob Serlier's Personal Site
Production RAG: what I learned from processing 5M+ documents
The World’s Smallest Vector Database: How LEANN Uses 97% Less Space Than Traditional Vector DB | by MKWriteshere | Sep, 2025 | Medium
StarTrail-org/LEANN
[MLsys2026 Best Paper]: https://arxiv.org/abs/2506.08276. RAG on Everything with LEANN. Enjoy 97% storage savings while running a fast, accurate, and 100%…
Generating a dataset of queries for training and fine-tuning ColPali models on a UFO dataset – Daniel van Strien
Exploring ColBERT with RAGatouille | Simon Willison’s TILs
good explanation of ColBERT
A Simple Guide to Retrieval Augmented Generation
Book outline: The components of a RAG system How to create a RAG knowledge base The indexing and generation pipeline Evaluating a RAG system Advanced RAG…