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arXiv Computation and Language By Yuchao Wu, Junqin Li, Xingcheng Liang, Yongjie Chen, Yinghao Liang, Linyuan Mo, Guanxian Li

SAG: SQL-Retrieval Augmented Generation with Query-Time Dynamic Hyperedges

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SAG (SQL‑Retrieval Augmented Generation) is a structured retrieval framework that indexes documents as event‑entity pairs, forming latent hyperedges that preserve n‑ary relations without building a global knowledge graph. At query time, shared entities act as join keys, dynamically creating a query‑scoped neighborhood of related events while keeping each evidence chunk intact. Experiments on HotpotQA, 2WikiMultiHopQA, and MuSiQue demonstrate that SAG outperforms existing dense‑retrieval baselines, achieving the highest recall and end‑to‑end QA performance, especially as reasoning‑chain complexity grows.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computation and Language.

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