GitHub

GitHub - deepdoctor/MDT-LLM: Multi-agent LLM framework with RAG for lung cancer multidisciplinary decision support. LungMDT-Bench-100 benchmark. JKSUCIS 2026. · GitHub

Open-source framework and benchmark accompanying our paper "MDT-LLM: A Multi-Agent Large Language Model Framework with Retrieval-Augmented Generation for Lung Cancer Multidisciplinary Decision Support ...
IEEE

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

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

Alibaba’s Tongyi Lab Releases VimRAG: a Multimodal RAG Framework that Uses a Memory Graph to Navigate Massive Visual Contexts

Retrieval-Augmented Generation (RAG) has become a standard technique for grounding large language models in external knowledge — but the moment you move beyond plain text and start mixing in images ...
IEEE

Evaluating Handwritten and Multimodal, Free-Style Responses in Algorithms and Data Structures: A RAG-LLM-Based Feedback Framework

Abstract: This innovative practice full paper presents a retrieval-augmented large language model (RAG-LLM) framework for evaluating handwritten and multimodal, freeform student responses. In the age ...
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 ...