Unlocking Data with Generative AI and RAG — Free eBook worth $35.990 0

Design intelligent AI agents with retrieval-augmented generation, memory components, and graph-based context integration.
IEEE

SH-RAG: A Syntax-Based Hierarchical Retrieval-Augmented Generation Framework for Handling Syntactic Complexity in Literary Machine Translation

Abstract: With the rapid advancements in machine translation (MT), large language models (LLMs) have demonstrated the ability to generate high-quality translations with relatively low computational ...
GitHub

yashab-cyber/metasploit-ai

Metasploit-AI is a cutting-edge cybersecurity framework that combines the power of Metasploit with advanced artificial intelligence and machine learning capabilities. Designed for cybersecurity ...
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 ...
blockchain

NVIDIA Nemotron RAG Gets Production Pipeline Tutorial for Enterprise AI

NVIDIA releases step-by-step guide for building multimodal document processing pipelines with Nemotron RAG, targeting enterprise AI deployments requiring precise data extraction. NVIDIA has published ...
IEEE

ENWAR: A RAG-Empowered Multi-Modal LLM Framework for Wireless Environment Perception

Abstract: Large language models (LLMs) hold significant promise in advancing network management and orchestration in sixth-generation (6G) and beyond networks. However, existing LLMs are limited in ...