InfoQ

Graph RAG: Building Smarter Retrieval Workflows with Knowledge Graphs

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...
Hacker

Building a Graph-Vector Hybrid Memory Layer for AI Agents

I build things that shouldn't exist yet.Systems that learn from their own failures. Here's a problem I kept running into, over and over, while working with autonomous agents. I'd give an agent a task ...
marktechpost

PyGraphistry Implementation Workflow for Interactive Graph Intelligence Pipelines in Security Analytics and Risk Investigation

In this tutorial, we build an advanced, Colab-ready workflow around PyGraphistry for interactive graph analytics and visualization. We start by creating a realistic enterprise-style access dataset, ...
IEEE

ExGAT: Build Explicit Dependencies for Incomplete Multi-Modal Learning via Graph Attention Network

Abstract: Recent research in multi-modal applications has highlighted the challenge of handling missing modalities. Most existing methods either overlook the dependencies between modalities or rely on ...
Journal of Medical Internet Research

Large Language Model–Driven Knowledge Graph Construction in Sepsis Care Using Multicenter Clinical Databases: Development and Usability Study

Building upon this, we compiled a comprehensive sepsis knowledge graph, comprising of 1894 nodes and 2021 distinct relationships. Conclusions: This study represents a pioneering effort in using LLMs, ...
GitHub

STM-Graph: A Python Framework for Spatio-Temporal Mapping and Graph Neural Network Predictions

STM-Graph is a Python framework for analyzing spatial-temporal urban data and doing predictions using Graph Neural Networks. It provides a complete end-to-end pipeline from raw event data to trained ...