--- title: "Who cites Empowering GraphRAG with — 5 citing papers" description: "5 papers of the Elamur Research library cite «Empowering GraphRAG with Knowledge Filtering and Integration», found in their bibliographies…" canonical: "https://research.elamur.ai/free/en/papers/guo-2025-empowering-graphrag-knowledge-filtering-integration/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/guo-2025-empowering-graphrag-knowledge-filtering-integration/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Empowering GraphRAG with Knowledge Filtering and…](https://md.research.elamur.ai/free/en/papers/guo-2025-empowering-graphrag-knowledge-filtering-integration/) / cited by # Who cites «Empowering GraphRAG with Knowledge Filtering and Integration» 5 papers of our library cite it (of the 149,439 whose bibliographies we read) · 2 with a page here, the most cited first · [← back to «Empowering GraphRAG with Knowledge Filtering and Integration»](https://md.research.elamur.ai/free/en/papers/guo-2025-empowering-graphrag-knowledge-filtering-integration/) 1. [**You Don't Need Pre-built Graphs for RAG: Retrieval Augmented Generation with Adaptive Reasoning Structures arXiv:2508.06105**Shengyuan Chen, Chuang Zhou, Zheng Yuan, et al.*2025 · 9 citations*](https://md.research.elamur.ai/free/en/papers/chen-2025-don-t-need-pre-built/) 2. **[Think Parallax: Solving Multi-Hop Problems via Multi-View Knowledge-Graph-Based Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/liu-2026-think-parallax-solving-multi-hop/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jinliang Liu, Jiale Bai, Shaoning Zeng*2026* 3 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/guo-2025-empowering-graphrag-knowledge-filtering-integration/) — Empowering GraphRAG with Knowledge Filtering and Integration