Ex-GraphRAG: Interpretable Evidence Routing for Graph-Augmented LLMs

ArXi:2605.21994v1 Announce Type: cross GraphRAG conditions language models on subgraphs retrieved from knowledge graphs, encoded via message-passing GNNs. Because these encoders entangle node contributions through iterated neighborhood aggregation, there is no closed-form way to determine how much each retrieved entity influenced the encoder's output, and. therefore. no way to faithfully audit what structural evidence actually reached the model. We