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BABOONS: Black-Box Optimization of Data Summaries in Natural Language

Summary: BABOONS black-box-optimizes natural-language data summaries for arbitrary utilities, including LLM- or user-defined scorers, via reinforcement learning. Proactive query merging, scenario-specific sampling, and batching enable scalable search and higher human-rated summary quality. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
12968
Venue
VLDB
Year
2022
Pagerank
5.093636e-05
Overall Rank
11,582 | 20.54%
DOI
10.14778/3551793.3551846

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Authors

BibTeX Citation

@article{trummer_vldb22,
        title = {{BABOONS: Black-Box Optimization of Data Summaries in Natural Language}},
        author = {Trummer, Immanuel},
        journal = {PVLDB},
        series = {{VLDB} '22},
        volume = {15},
        number = {11},
        pages = {2980--2993},
        doi = {10.14778/3551793.3551846},
        url = {https://doi.org/10.14778/3551793.3551846},
        year = {2022}
}

Incoming Citations (Sorted by Pagerank)

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Rank Citing Paper Year Venue Pagerank
4,449 From BERT to GPT-3 Codex: Harnessing the Potential of Very Large Language Models for Data Management 2022 VLDB 6.697553e-05
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