그래프 튜토리얼 1화 : Main Concept of Graph Neural Network
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26년 2월 3주차 그래프 오마카세
RAG-ANYTHING: ALL-IN-ONE RAG FRAMEWORK RAG-Anything: All-in-One RAG FrameworkRetrieval-Augmented Generation (RAG) has emerged as a fundamental paradigm for expanding Large Language Models beyond their static training limitations. However, a critical misalignment exists between current RAG capabilities and real-world information environments. Modern knowledge repositories are inherently multimodal, containing rich combinations of textual
26년 2월 2주차 그래프 오마카세
Graph Talks LLM,GNN integration 행사 참여 신청 링크 안녕하세요, GUG 정이태입니다. 1.입춘이 다가오고 있지만 여전히 바람이 매섭네요. 다행히 지난 주말은 바람이 잦아들어 잠시나마 숨을 돌릴 수 있는 휴일이었는데, 다들 건강하게 잘 지내고 계신가요? 2.요즘 AI 업계는 NVIDIA GTC 2025에서 화두가 되었던 GraphRAG(Softprompt, KGE)를 넘어, 다가올
26년 2월 1주차 그래프 오마카세
Learning Topology and Physical Laws Beyond Nodes and Edges : E(n)-Equivariant Topological Neural Networks E(n) Equivariant Topological Neural NetworksGraph neural networks excel at modeling pairwise interactions, but they cannot flexibly accommodate higher-order interactions and features. Topological deep learning (TDL) has emerged recently as a promising tool for addressing
26년 1월 4주차 그래프 오마카
The Synergy Created By MCP, and Knowledge Graph of Agentic AI Memgraph blogStay up-to-date with the latest trends and insights in graph database technology with Memgraph’s blog.GraphRAG & Knowledge Graphs: Making Your Data AI-Ready for 2026 - FlureeDiscover why 78% of companies aren’t AI-ready and how GraphRAG