Ex-GraphRAG replaces GNN encoders with M-GNAN for exact node-level decomposition in graph-augmented LLMs, matching black-box performance on STaRK-Prime while exposing semantic-structural mismatches that degrade multi-hop QA when low-attribution intermediaries are removed.
Advances in Neural Information Processing Systems , pages=
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Ex-GraphRAG: Interpretable Evidence Routing for Graph-Augmented LLMs
Ex-GraphRAG replaces GNN encoders with M-GNAN for exact node-level decomposition in graph-augmented LLMs, matching black-box performance on STaRK-Prime while exposing semantic-structural mismatches that degrade multi-hop QA when low-attribution intermediaries are removed.