An Adaptive Benchmark for Modeling User Exploration of Large Datasets
Summary: Proposes SIMBA, an adaptive benchmark that simulates data exploration by generating SQL-based interaction sequences to encode goals. It measures progress by equating user queries with goals, enabling goal-driven benchmarking and exposing IDEBench misses. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Joanna Purich (University of Maryland)
- 2. Anthony Wise (University of Washington)
- 3. Leilani Battle (University of Washington)
BibTeX Citation
@inproceedings{purich_sigmod25,
title = {{An Adaptive Benchmark for Modeling User Exploration of Large Datasets}},
author = {Purich, Joanna and Wise, Anthony and Battle, Leilani},
series = {{SIGMOD} '25},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3709658},
url = {https://dl.acm.org/doi/10.1145/3709658},
year = {2025}
}
Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,199 | Automated Discovery of Test Oracles for Database Management Systems Using LLMs | 2026 | SIGMOD | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 12 of 12 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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