RAGPerf: An End-to-End Benchmarking Framework for Retrieval-Augmented Generation Systems
Summary: RAGPerf is an end-to-end, modular benchmark that isolates embedding, indexing, retrieval, reranking, and generation in configurable RAG pipelines. It combines realistic multimodal/update workloads with vector DB/LLM support and automated systems-quality metrics at negligible overhead. (summarized by gpt-5.6-luna on Aug 28 2026)
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Authors
- 1. Shaobo Li (University of Illinois Urbana-Champaign)
- 2. Yirui Zhou (University of Illinois Urbana-Champaign)
- 3. Yuan Xu (University of Illinois Urbana-Champaign)
- 4. Kevin Chen (University of Illinois Urbana-Champaign)
- 5. Daniel Waddington (IBM)
- 6. Swaminathan Sundararaman (IBM)
- 7. Hubertus Franke (IBM)
- 8. Jian Huang (University of Illinois Urbana-Champaign)
BibTeX Citation
@article{li_vldb26,
title = {{RAGPerf: An End-to-End Benchmarking Framework for Retrieval-Augmented Generation Systems}},
author = {Li, Shaobo and Zhou, Yirui and Xu, Yuan and Chen, Kevin and Waddington, Daniel and Sundararaman, Swaminathan and Franke, Hubertus and Huang, Jian},
journal = {PVLDB},
series = {{VLDB} '26},
volume = {19},
number = {11},
pages = {3689--3703},
doi = {10.14778/3836663.3836718},
url = {https://doi.org/10.14778/3836663.3836718},
year = {2026}
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| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 194 | Milvus: A Purpose-Built Vector Data Management System | 2021 | SIGMOD | 0.00025636725 |
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