GraphRAG methods to create optimized LLM context windows for Retrieval — Jonathan Larson, Microsoft
This talk introduces GraphRAG, a method for optimizing Large Language Model (LLM) context windows using graph structures for retrieval. The core thesis is that LLM memory with structure is a key enabler for building effective AI applications, and when paired with agents, this combination offers even greater power. The presentation demonstrates GraphRAG's application in code understanding and feature development, alongside the announcement of Benchmark QED, an open-source tool for evaluating LLM systems.
World's Fair 2025 15 min