SAG: SQL-Retrieval Augmented Generation with Query-Time Dynamic Hyperedges
While retrieval-augmented generation (RAG) has proven effective at giving LLMs access to external knowledge, mainstream dense-retrieval implementations remain inherently limited in handling structured constraints and multi-hop reasoning. Graph-based methods address this by constructing knowledge graphs offline, but they often fragment semantics, incur high maintenance, and complicate incremental updates. We propose SAG (SQL-Retrieval Augmented Generation), a structured retrieval architecture that organizes documents into an event-entity index without building a global knowledge graph. SAG represents each chunk as a semantically complete event paired with its entities, forming a latent hyp...
| Authors | Yuchao Wu, Junqin Li, Xingcheng Liang et al. |
|---|---|
| Primary category | cs.CL |
| Published | 14 June 2026 |
| Last updated at source | 25 August 2026 |
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