Today, I’d like to discuss the evaluation methods for GraphRAG.Additionally, there are evaluation methods where LLMs serve as the evaluators, including single point, reference-based, and pairwise-based…Jul 31Jul 31
How do we measure if GraphRAG will help with the RAG pipeline?From Local to Global: A Graph RAG Approach to Query-Focused Summarization.Jun 121Jun 121
Really helpful to knowledge graph for reasoning and improving LLM performance?Evolving the industry of LLM, we had been faced the challenge for enhancing their performance aspect of hallucination , data privacy and…Apr 15Apr 15
Semantic search and its supplement ‘Graph based prompting’Graph Neural Prompting with Large Language ModelsMar 24Mar 24
From RAG to GraphRAG , What is the GraphRAG and why i use it?Before discussing RAG and GraphRAG,Mar 126Mar 126
GraphRAG, Let’s check the rationality with the paper and a few checklists to see if it’s time to…Email : jeongiitae6@gmail.comMar 3Mar 3
Neural Scaling Laws on Graphs, do you believe is there strong related between model , data size…Correlation between model , data size and model performance at grpah data.Feb 25Feb 25
GraNNDis / before you worried the large graph training , this architecture can help your worry…GraNNDis: Efficient Unified Distributed Training Framework for Deep GNNs on Large ClustersFeb 181Feb 181
Graph FDS | before we implement the model , we must know the trend of FDS paper — 04review _ Pick and Choose: A GNN-based Imbalanced Learning Approach for Fraud DetectionFeb 4Feb 4
