GitHub

This is a mini AI QA project that answers one simple question:

An LLM can sound confident even when it is guessing. RAG is supposed to reduce that problem by giving the model relevant content before it answers. But as a QA engineer, you should not just assume RAG ...
TDWI

Driving Breakthrough AI Innovation in Financial Services with a RAG Playground and Agentic AI

In enterprise environments, traditional generative AI models often fall short due to their limited context, inability to effectively and securely access proprietary data, and a lack of traceability.
IEEE

A Unified Evaluation Framework for Grounded LLM Architectures: Comparative Analysis of RAG, Self-RAG, and Agentic RAG

Retrieval-Augmented Generation (RAG) grounds large language models with external knowledge, while two recent variants—Self-RAG (self-reflective retrieval refinement) and Agentic RAG (multi-step ...
GitHub

Suggestion: add WFGY (LLM robustness + RAG debugging framework)

Hi, thanks for maintaining this collection of machine learning lists. I would like to suggest one project that might fit under the LLM / RAG / evaluation or debugging related resources: Name: WFGY ...
IEEE

Permission-Aware RAG: Identity and Access Management (IAM)-Based Access Filtering in Multi-Resource Environments

Abstract: Retrieval-Augmented Generation (RAG) enhances large language models (LLMs) by integrating external knowledge sources, which significantly improves response accuracy and contextual relevance.
Hacker

Kendi RAG Uygulamanızı Oluşturun: Ollama, Python ve ChromaDB'yi kullanarak LLM'yi yerel olarak kurmak için Adım Adım Kılavuz

As a professional in the tech industry, I enjoy delving into complex problems and sharing solutions that help others on ...