DBScholar

Back to papers

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
hde38e594f65c1f96
Venue
SIGMOD
Year
2025
Pagerank
6.9214086e-05
Overall Rank
3,925 | 73.62%
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}
}

Incoming Citations (Sorted by Pagerank)

Showing 7 of 7 citing papers.

Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 8 of 8 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Previous Page 1 / 1 Next

Semantically Similar Papers