---
title: "Who cites Hengshu Zhu — 75 papers of our library"
description: "75 papers of the Elamur Research library cite the works of Hengshu Zhu, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/hengshu-zhu/cited-by/"
---
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# Who cites Hengshu Zhu

75 citations of their works from 75 papers of our library (of the 149,439 whose bibliographies we read) · 11 with a page here, the most cited first · [← Hengshu Zhu](https://md.research.elamur.ai/free/en/authors/hengshu-zhu/)

1. **[Graph Retrieval-Augmented Generation: A Survey](https://md.research.elamur.ai/free/en/papers/peng-2024-graph-retrieval-augmented-generation-survey/) [ACM Transactions on Information Systems](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-information-systems/)**Boci Peng, Yun Zhu, Yongchao Liu, et al.*2024 · 276 citations*
2. [**BioKGBench: A Knowledge Graph Checking Benchmark of AI Agent for Biomedical Science arXiv:2407.00466**Xinna Lin, Siqi Ma, Junjie Shan, et al.*2024 · 12 citations*](https://md.research.elamur.ai/free/en/papers/lin-2024-biokgbench-knowledge-graph-checking-benchmark/)
3. **[Stepwise Reasoning Disruption Attack of LLMs](https://md.research.elamur.ai/free/en/papers/peng-2025-stepwise-reasoning-disruption-attack-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jingyu Peng, Maolin Wang, Xiangyu Zhao, et al.*2025 · 10 citations*
4. **[COSMOS: Connectivity-Oriented Submodular Maximization for Optimal Subgraph Retrieval](https://md.research.elamur.ai/free/en/papers/peng-2026-cosmos-connectivity-oriented-submodular-maximization/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Boci Peng, Xiao Liu, Boren Hu, et al.*2026*
5. **[EA-Agent: A Structured Multi-Step Reasoning Agent for Entity Alignment](https://md.research.elamur.ai/free/en/papers/nan-2026-ea-agent-structured-multi-step/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yixuan Nan, Xixun Lin, Yanmin Shang, et al.*2026*
6. **[EvoMemKG: An Evolvable Memory Agent for Multi-hop Knowledge Graph Reasoning](https://md.research.elamur.ai/free/en/papers/tian-2026-evomemkg-evolvable-memory-agent-multi/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shiyu Tian, Shuyue Xing, Zhuoxin Han, et al.*2026*
7. **[Graph-Assisted Large Language Models: A Perspective on Mitigating Intrinsic Limitations](https://md.research.elamur.ai/free/en/papers/luo-2026-graph-assisted-large-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Haitong Luo, Fali Wang, Weiyao Zhang, et al.*2026*
8. **[Interactive Semantic Parsing with Reinforcement Learning for Knowledge Graph Reasoning](https://md.research.elamur.ai/free/en/papers/song-2026-interactive-semantic-parsing-reinforcement-learning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yurun Song, Xiangqing Shen, Jianfei Yu, et al.*2026*
9. **[NG-Router: Graph-Supervised Multi-Agent Collaboration for Nutrition Question Answering](https://md.research.elamur.ai/free/en/papers/shi-2026-ng-router-graph-supervised-multi/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Kaiwen Shi, Zheyuan Zhang, Zhengqing Yuan, et al.*2026*
10. **[Subgraph-Guided Executable Logical Form Generation for Knowledge Base Question Answering](https://md.research.elamur.ai/free/en/papers/tian-2026-subgraph-guided-executable-logical-form/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuhang Tian, Dandan Song, Zhijing Wu, et al.*2026*
11. **[Thought-Action Graph Reasoning: Faithful and Efficient Reasoning of Large Language Models via Reusing Past Experience](https://md.research.elamur.ai/free/en/papers/qi-2026-thought-action-graph-reasoning-faithful/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhixiao Qi, Feng Huang, Yunqi Zhang, et al.*2026*

64 more citing papers of our library have no page here yet.

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