PRISM: Navigating Cost–Accuracy Trade-offs for NL2SQL
Summary: PRISM targets NL2SQL deployment as a schema-aware cost–accuracy optimization problem, rather than pure accuracy maximization. Uses cost-aware Bayesian optimization offline to curate high-performing pipelines, then deploys a single candidate or ensemble for strong accuracy at dramatically lower inference cost. (summarized by gpt-5-mini on Apr 11 2026)
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Authors
- 1. Gaurav Tarlok Kakkar
- 2. Yeounoh Chung
- 3. Fatma Özcan
- 4. Steve Mussmann
- 5. Joy Arulraj
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 366 | Text-to-SQL Empowered by Large Language Models: A Benchmark Evaluation | 2024 | VLDB | 0.00025580097 |
| 998 | CodeS: Towards Building Open-source Language Models for Text-to-SQL | 2024 | SIGMOD | 0.00014726344 |
| 1,839 | DocETL: Agentic Query Rewriting and Evaluation for Complex Document Processing | 2025 | VLDB | 0.00010351287 |
| 2,013 | Palimpzest: Optimizing AI-Powered Analytics with Declarative Query Processing | 2025 | CIDR | 9.7986166e-05 |
| 3,978 | OmniSQL: Synthesizing High-quality Text-to-SQL Data at Scale | 2025 | VLDB | 6.5662694e-05 |
| 7,335 | SpareLLM: Automatically Selecting Task-Specific Minimum-Cost Large Language Models under Equivalence Constraint | 2025 | SIGMOD | 4.7533835e-05 |
| 9,239 | Is Long Context All You Need? Leveraging LLM's Extended Context for NL2SQL | 2025 | VLDB | 4.3648789e-05 |
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