🔗 Who cites «GraphGPT: Graph Instruction Tuning for Large Language Models»

69 papers of our library cite it (of the 149,439 whose bibliographies we read) · 17 with a page here, the most cited first · ← back to «GraphGPT: Graph Instruction Tuning for Large Language Models»

1. LightRAG: Simple and Fast Retrieval-Augmented GenerationarXiv:2410.05779Zirui Guo, Lianghao Xia, Yanhua Yu, et al.2024 · 316 citations
2. G-Retriever: Retrieval-Augmented Generation for Textual Graph Understanding and Question AnsweringConference on Neural Information Processing Systems (NeurIPS)Xiaoxin He, Yijun Tian, Yifei Sun, et al.2024 · 236 citations
3. InstructMol: Multi-Modal Integration for Building a Versatile and Reliable Molecular Assistant in Drug DiscoveryInternational Conference on Computational Linguistics (COLING)He Cao, Zijing Liu, Xingyu Lu, et al.2025 · 38 citations
4. BioKGBench: A Knowledge Graph Checking Benchmark of AI Agent for Biomedical SciencearXiv:2407.00466Xinna Lin, Siqi Ma, Junjie Shan, et al.2024 · 12 citations
5. Taming Language Models for Text-attributed Graph Learning with Decoupled AggregationAnnual Meeting of the Association for Computational Linguistics (ACL)Chuang Zhou, Zhu Wang, Shengyuan Chen, et al.2025 · 9 citations
6. AnyGraph: Graph Foundation Model in the WildFindings of the Association for Computational LinguisticsLianghao Xia, Chao Huang2026 · 3 citations
7. Exploring Graph Learning Tasks with Pure LLMs: A Comprehensive Benchmark and InvestigationFindings of the Association for Computational LinguisticsYuxiang Wang, Xinnan Dai, Wenqi Fan, et al.2026 · 1 citation
8. AgentGL: Towards Agentic Graph Learning with LLMs via Reinforcement LearningAnnual Meeting of the Association for Computational Linguistics (ACL)Yuanfu Sun, Kang Li, Dongzhe Fan, et al.2026
9. CITE: Benchmarking Heterogeneous Text-Attributed Graph ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Chenghao Zhang, Qingqing Long, Ludi Wang, et al.2026
10. Colorful Talks with Graphs: Human-Interpretable Graph Encodings for Large Language ModelsFindings of the Association for Computational LinguisticsAngelo Zangari, Peyman Baghershahi, Sourav Medya2026
11. Generalizable LLM Learning of Graph Synthetic Data with Post-training AlignmentFindings of the Association for Computational LinguisticsYizhuo Zhang, Heng Wang, Shangbin Feng, et al.2026
12. Generalization in Graph Reasoning: A Systematic Comparison of LLM Training ApproachesWorkshop on Structured Understanding, Retrieval, and Generation in the LLM EraSola Shirai, Kavitha Srinivas, Julian Dolby, et al.2026
13. GraphLoRA: Structure-Aware Low-Rank Adaptation for Large Language Model RecommendationFindings of the Association for Computational LinguisticsLin Mu, Guoji Wang, Li Ni, et al.2026
14. How to Make LMs Strong Node Classifiers?Findings of the Association for Computational LinguisticsZhe Xu, Kaveh Hassani, Si Zhang, et al.2026
15. MuSe: Multi-Stage Graph Reasoning via Vision-Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Guanyu Wang, Xu Chu, Zhijie Tan, et al.2026
16. 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
17. TRN-R1-Zero: Text-rich Network Reasoning via LLMs with Reinforcement Learning OnlyAnnual Meeting of the Association for Computational Linguistics (ACL)Yilun Liu, Ruihong Qiu, Zi Huang2026

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