---
title: "Who cites Talk like a Graph: Encoding — 69 citing papers"
description: "69 papers of the Elamur Research library cite «Talk like a Graph: Encoding Graphs for Large Language Models», found in their bibliographies…"
canonical: "https://research.elamur.ai/free/en/papers/fatemi-2023-talk-like-graph-encoding-graphs/cited-by/"
---
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[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Talk like a Graph: Encoding Graphs for Large…](https://md.research.elamur.ai/free/en/papers/fatemi-2023-talk-like-graph-encoding-graphs/) / cited by

# Who cites «Talk like a Graph: Encoding Graphs for Large Language Models»

69 papers of our library cite it (of the 149,439 whose bibliographies we read) · 21 with a page here, the most cited first · [← back to «Talk like a Graph: Encoding Graphs for Large Language Models»](https://md.research.elamur.ai/free/en/papers/fatemi-2023-talk-like-graph-encoding-graphs/)

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. **[G-Retriever: Retrieval-Augmented Generation for Textual Graph Understanding and Question Answering](https://md.research.elamur.ai/free/en/papers/he-2024-g-retriever-retrieval-augmented-generation/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Xiaoxin He, Yijun Tian, Yifei Sun, et al.*2024 · 236 citations*
3. [**Retrieval-Augmented Generation with Graphs (GraphRAG) arXiv:2501.00309**Haoyu Han, Yu Wang, Harry Shomer, et al.*2025 · 87 citations*](https://md.research.elamur.ai/free/en/papers/han-2025-retrieval-augmented-generation-graphs-graphrag/)
4. **[Knowledge Graph Retrieval-Augmented Generation for LLM-based Recommendation](https://md.research.elamur.ai/free/en/papers/wang-2025-knowledge-graph-retrieval-augmented-generation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shijie Wang, Wenqi Fan, Yue Feng, et al.*2025 · 77 citations*
5. **[LocAgent: Graph-Guided LLM Agents for Code Localization](https://md.research.elamur.ai/free/en/papers/chen-2025-locagent-graph-guided-llm-agents/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhaoling Chen, Robert Tang, Gangda Deng, et al.*2025 · 27 citations*
6. **[Can Graph Descriptive Order Affect Solving Graph Problems with LLMs?](https://md.research.elamur.ai/free/en/papers/ge-2025-can-graph-descriptive-order-affect/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuyao Ge, Shenghua Liu, Baolong Bi, et al.*2025 · 10 citations*
7. **[Agent-based Substructure Counting under Local Differential Privacy](https://md.research.elamur.ai/free/en/papers/zhang-2026-agent-based-substructure-counting-under/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuting Zhang, Kai Wang, Wei Ni, et al.*2026 · 1 citation*
8. **[Exploring Graph Learning Tasks with Pure LLMs: A Comprehensive Benchmark and Investigation](https://md.research.elamur.ai/free/en/papers/wang-2026-exploring-graph-learning-tasks-pure/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuxiang Wang, Xinnan Dai, Wenqi Fan, et al.*2026 · 1 citation*
9. **[Asking language models how to represent data for fine-tuning](https://md.research.elamur.ai/free/en/papers/singh-2026-asking-language-models-how-represent/) [Workshop on Structured Understanding, Retrieval, and Generation in the LLM Era](https://md.research.elamur.ai/free/en/venues/surgellm/)**Usneek Singh, Ananya Singha, Abhijeet Awasthi, et al.*2026*
10. **[BiMol-Diff: A Unified Diffusion Framework for Molecular Generation and Captioning](https://md.research.elamur.ai/free/en/papers/shahane-2026-bimol-diff-unified-diffusion-framework/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Aditya Hemant Shahane, Anuj Kumar Sirohi, Devansh Arora, et al.*2026*
11. **[Colorful Talks with Graphs: Human-Interpretable Graph Encodings for Large Language Models](https://md.research.elamur.ai/free/en/papers/zangari-2026-colorful-talks-graphs-human-interpretable/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Angelo Zangari, Peyman Baghershahi, Sourav Medya*2026*
12. **[Generalizable LLM Learning of Graph Synthetic Data with Post-training Alignment](https://md.research.elamur.ai/free/en/papers/zhang-2026-generalizable-llm-learning-graph-synthetic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yizhuo Zhang, Heng Wang, Shangbin Feng, et al.*2026*
13. **[Generalization in Graph Reasoning: A Systematic Comparison of LLM Training Approaches](https://md.research.elamur.ai/free/en/papers/shirai-2026-generalization-graph-reasoning-systematic-comparison/) [Workshop on Structured Understanding, Retrieval, and Generation in the LLM Era](https://md.research.elamur.ai/free/en/venues/surgellm/)**Sola Shirai, Kavitha Srinivas, Julian Dolby, et al.*2026*
14. **[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*
15. **[GROKE: Vision-Free Navigation Instruction Evaluation via Graph Reasoning on OpenStreetMap](https://md.research.elamur.ai/free/en/papers/shami-2026-groke-vision-free-navigation-instruction/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Farzad Shami, Subhrasankha Dey, Nico Van de Weghe, et al.*2026*
16. **[How to Make LMs Strong Node Classifiers?](https://md.research.elamur.ai/free/en/papers/xu-2026-how-make-lms-strong-node/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhe Xu, Kaveh Hassani, Si Zhang, et al.*2026*
17. **[Linguistic Initialization for Inductive Reasoning in Heterogeneous Knowledge Graphs](https://md.research.elamur.ai/free/en/papers/pasquini-2026-linguistic-initialization-inductive-reasoning-heterogeneous/) [Knowledge Graphs and Large Language Models Workshop (KG-LLM) @ LREC26](https://md.research.elamur.ai/free/en/venues/kallm/)**Daniele Pasquini, Danilo Croce, Roberto Basili*2026*
18. **[MuSe: Multi-Stage Graph Reasoning via Vision-Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-muse-multi-stage-graph-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Guanyu Wang, Xu Chu, Zhijie Tan, et al.*2026*
19. **[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*
20. [**Recent Advances in Text-attributed Graph Learning via Large Models (大模型驱动的文本属性图学习研究进展) Acta Automatica Sinica (自动化学报)**Yanping Zheng (郑艳萍), Jiarui Ji (季嘉蕊), Yuwei Hu (胡雨韦), et al.*2026*](https://md.research.elamur.ai/free/en/papers/zheng-2026-recent-advances-text/)
21. **[Toward Consistent World Models with Multi-Token Prediction and Latent Semantic Enhancement](https://md.research.elamur.ai/free/en/papers/zhong-2026-consistent-world-models-multi-token/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qimin Zhong, Hao Liao, Haiming Qin, et al.*2026*

48 more papers of our library cite it; they have no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/papers/fatemi-2023-talk-like-graph-encoding-graphs/) — Talk like a Graph: Encoding Graphs for Large Language Models