GIO: Generating Efficient Matrix and Frame Readers for Custom Data Formats by Example
Summary: GIO learns mapping from raw text to matrix/frame layouts from a sample and auto-generates a fast multi-threaded reader. Supports CSV/LibSVM/MatrixMarket and nested formats; mappings and readers editable; competitive with hand-written parsers. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Saeed Fathollahzadeh (Graz University of Technology; Know-Center GmbH)
- 2. Matthias Boehm (Technical University of Berlin)
BibTeX Citation
@inproceedings{fathollahzadeh_sigmod23,
title = {{GIO: Generating Efficient Matrix and Frame Readers for Custom Data Formats by Example}},
author = {Fathollahzadeh, Saeed and Boehm, Matthias},
series = {{SIGMOD} '23},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3589265},
url = {https://dl.acm.org/doi/10.1145/3589265},
year = {2023}
}
Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 6,118 | ELEET: Efficient Learned Query Execution over Text and Tables | 2024 | VLDB | 5.9698795e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 45 of 45 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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