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Graph Retrieval Augmented Generation (GraphRAG) has garnered increasing recognition for its potential to enhance large language models (LLMs) by structurally organizing domain-specific corpora and facilitating complex reasoning.
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2023
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Y. Gao, Y. Xiong, X. Gao, K. Jia, J. Pan, Y. Bi, Y. Dai, J. Sun, M. Wang, and H. Wang, “Retrieval-augmented generation for large language models: A survey,” 2024
2024
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B. Peng, Y. Zhu, Y. Liu, X. Bo, H. Shi, C. Hong, Y. Zhang, and S. Tang, “Graph retrieval-augmented generation: A survey,” 2024
2024
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P. Sarthi, S. Abdullah, A. Tuli, S. Khanna, A. Goldie, and C. D. Manning, “RAPTOR: Recursive abstractive processing for tree-organized retrieval,” in
2024
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X. He, Y. Tian, Y. Sun, N. V. Chawla, T. Laurent, Y. LeCun, X. Bresson, and B. Hooi, “G-retriever: Retrieval-augmented generation for textual graph understanding and question answering,” in
2024
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D. Li, S. Yang, Z. Tan, J. Y. Baik, S. Yun, J. Lee, A. Chacko, B. Hou, D. Duong-Tran, Y. Ding, H. Liu, L. Shen, and T. Chen, “DALK: Dynamic co-augmentation of LLMs and KG to answer Alzheimer‘s disease questions with scientific literature,” in
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2024
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2024
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2024
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Q. Zhang, S. Chen, Y. Bei, Z. Yuan, H. Zhou, Z. Hong, J. Dong, H. Chen, Y. Chang, and X. Huang, “A survey of graph retrieval-augmented generation for customized large language models,” 2025
2025
Closest in time.
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2024
Cited alongside, same era.
J. Sun, C. Xu, L. Tang, S. Wang, C. Lin, Y. Gong, L. Ni, H.-Y. Shum, and J. Guo, “Think-on-graph: Deep and responsible reasoning of large language model on knowledge graph,” in
2024
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Z. Guo, L. Xia, Y. Yu, T. Ao, and C. Huang, “Lightrag: Simple and fast retrieval-augmented generation,” 2024
2024
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B. J. Gutiérrez, Y. Shu, Y. Gu, M. Yasunaga, and Y. Su, “Hipporag: Neurobiologically inspired long-term memory for large language models,” in
2024
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2025
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Y. Zhou, Y. Su, Y. Sun, S. Wang, T. Wang, R. He, Y. Zhang, S. Liang, X. Liu, Y. Ma, and Y. Fang, “In-depth analysis of graph-based rag in a unified framework,” 2025
2025
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L. Luo, Z. Zhao, G. Haffari, D. Phung, C. Gong, and S. Pan, “Gfm-rag: Graph foundation model for retrieval augmented generation,” 2025
2025
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