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Pneuma: Leveraging LLMs for Tabular Data Representation and Retrieval in an End-to-End System

Summary: Pneuma is an end-to-end RAG system using LLMs to represent and retrieve tabular data, preserving schema and row context for accurate discovery. Evaluated on six real-world datasets, it outperforms full-text search and state-of-the-art RAG in accuracy and efficiency. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
7318
Venue
SIGMOD
Year
2025
Pagerank
6.2013279e-05
Overall Rank
5,485 | 62.37%
DOI
10.1145/3725337

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{balaka_sigmod25,
        title = {{Pneuma: Leveraging LLMs for Tabular Data Representation and Retrieval in an End-to-End System}},
        author = {Balaka, Muhammad Imam Luthfi and Alexander, David and Wang, Qiming and Gong, Yue and Krisnadhi, Adila and Fernandez, Raul Castro},
        series = {{SIGMOD} '25},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3725337},
        url = {https://dl.acm.org/doi/10.1145/3725337},
        year = {2025}
}

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