| Challenge: | Existing GraphRAGs expose a new attack surface: corpus-level knowledge poisoning can corrupt query-specific subgraphs and steer the generator toward incorrect answers. |
| Approach: | They propose a defense layer between retriever and generator that decomposes multi-hop questions into ordered subqueries and monitors hop-wise execution for poisoning-induced inconsistencies. |
| Outcome: | The proposed defense layer decomposes multi-hop questions into ordered subqueries and monitors hop-wise execution for poisoning-induced inconsistencies. |
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| Challenge: | Existing methods for enhancing LLM reliability suffer from inefficient information aggregation and rigid reasoning schemes. |
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