Demonstrating CatDB: LLM-based Generation of Data-centric ML Pipelines
Summary: CatDB enables LLM-based data-centric ML pipelines using dataset-specific instructions from profiling metadata and a refined data catalog. Instruction-splitting (clean, transform, train) yields massive speedups over state-of-the-art LLM/AutoML on large datasets. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Saeed Fathollahzadeh (Concordia University)
- 2. Essam Mansour (Concordia University)
- 3. Matthias Boehm (Technical University of Berlin)
BibTeX Citation
@inproceedings{fathollahzadeh_sigmod25,
title = {{Demonstrating CatDB: LLM-based Generation of Data-centric ML Pipelines}},
author = {Fathollahzadeh, Saeed and Mansour, Essam and Boehm, Matthias},
series = {{SIGMOD} '25},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3722212.3725097},
url = {https://dl.acm.org/doi/10.1145/3722212.3725097},
year = {2025}
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