GLOW: hybrid GNN + LLM question answering over incomplete knowledge graphs
burkov · x · 2026-10-14
Burkov surveys GLOW, a hybrid QA system combining graph neural networks with LLMs to answer accurately over incomplete knowledge graphs. Standard QA assumes all facts exist in the KB, but operational databases and knowledge graphs are inherently incomplete and evolving — LLMs hallucinate on missing facts and graph-retrieval tools fail when factual paths don't exist. GLOW's stated goal is demonstrating that combining structural learning with LLM language ability solves multi-hop questions under incompleteness.
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