LEGO-GraphRAG: Modularizing Graph-based Retrieval-Augmented Generation for Design Space Exploration
Summary: LEGO-GraphRAG decomposes GraphRAG into fine-grained, composable modules, classifying existing techniques and enabling systematic instance construction. Large-scale experiments expose trade-offs among reasoning quality, latency, and token/GPU cost. (summarized by gpt-5.6-luna on Jul 24 2026)
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Authors
- 1. Yukun Cao (University of Science and Technology Beijing)
- 2. Zengyi Gao (University of Science and Technology Beijing)
- 3. Zhiyang Li (University of Science and Technology Beijing)
- 4. Xike Xie (University of Science and Technology Beijing)
- 5. S. Kevin Zhou (University of Science and Technology Beijing)
- 6. Jianliang Xu (Hong Kong Baptist University)
BibTeX Citation
@article{cao_vldb25,
title = {{LEGO-GraphRAG: Modularizing Graph-based Retrieval-Augmented Generation for Design Space Exploration}},
author = {Cao, Yukun and Gao, Zengyi and Li, Zhiyang and Xie, Xike and Zhou, S. Kevin and Xu, Jianliang},
journal = {PVLDB},
series = {{VLDB} '25},
volume = {18},
number = {10},
pages = {3269--3283},
doi = {10.14778/3748191.3748194},
url = {https://doi.org/10.14778/3748191.3748194},
year = {2025}
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Outgoing Citations (Sorted by Pagerank)
Showing 9 of 9 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 65 | Freebase: A Collaboratively Created Graph Database For Structuring Human Knowledge | 2008 | SIGMOD | 0.00038697603 |
| 1,414 | Fast and Exact Top-k Search for Random Walk with Restart | 2012 | VLDB | 0.00010848387 |
| 3,315 | Distributed Algorithms on Exact Personalized PageRank | 2017 | SIGMOD | 7.5274958e-05 |
| 4,289 | Graph Indexing for Shortest-Path Finding over Dynamic Sub-Graphs | 2016 | SIGMOD | 6.779194e-05 |
| 4,714 | Personalized PageRank on Evolving Graphs with an Incremental Index-Update Scheme | 2023 | SIGMOD | 6.5497309e-05 |
| 5,608 | Big Graphs: Challenges and Opportunities | 2022 | VLDB | 6.1514145e-05 |
| 5,751 | Summarizing Static and Dynamic Big Graphs | 2017 | VLDB | 6.0994565e-05 |
| 7,798 | A Survey and Experimental Comparison of Distributed SPARQL Engines for Very Large RDF Data | 2017 | VLDB | 5.542286e-05 |
| 9,059 | PrismX: A Single-Machine System for Querying Big Graphs | 2024 | VLDB | 5.3251649e-05 |
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