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)
Incoming Non-self Citations Over Time
No non-self incoming citations found for this paper in this database.
Authors
- 1. Gaurav Tarlok Kakkar
- 2. Yeounoh Chung
- 3. Fatma Özcan
- 4. Steve Mussmann
- 5. Joy Arulraj
Incoming Citations (Sorted by Pagerank)
Showing 0 of 0 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|
Previous
Page 1 / 1
Next
Outgoing Citations (Sorted by Pagerank)
Showing 7 of 7 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 369 | Text-to-SQL Empowered by Large Language Models: A Benchmark Evaluation | 2024 | VLDB | 0.0002547515 |
| 998 | CodeS: Towards Building Open-source Language Models for Text-to-SQL | 2024 | SIGMOD | 0.00014729379 |
| 1,963 | DocETL: Agentic Query Rewriting and Evaluation for Complex Document Processing | 2025 | VLDB | 9.929429e-05 |
| 2,106 | Palimpzest: Optimizing AI-Powered Analytics with Declarative Query Processing | 2025 | CIDR | 9.5342543e-05 |
| 3,978 | OmniSQL: Synthesizing High-quality Text-to-SQL Data at Scale | 2025 | VLDB | 6.5725884e-05 |
| 7,339 | SpareLLM: Automatically Selecting Task-Specific Minimum-Cost Large Language Models under Equivalence Constraint | 2025 | SIGMOD | 4.7579469e-05 |
| 9,234 | Is Long Context All You Need? Leveraging LLM's Extended Context for NL2SQL | 2025 | VLDB | 4.3690661e-05 |
Previous
Page 1 / 1
Next
Semantically Similar Papers
| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,837 | Natural Language to SQL: State of the Art and Open Problems | 2025 | VLDB | 4.1945683e-05 |
| 1,732 | CatSQL: Towards Real World Natural Language to SQL Applications | 2023 | VLDB | 0.00010732004 |
| 369 | Text-to-SQL Empowered by Large Language Models: A Benchmark Evaluation | 2024 | VLDB | 0.0002547515 |
| 7,354 | Reliable Text-to-SQL with Adaptive Abstention | 2025 | SIGMOD | 4.7529612e-05 |
| 5,437 | SNAILS: Schema Naming Assessments for Improved LLM-Based SQL Inference | 2025 | SIGMOD | 5.5033018e-05 |
| 3,662 | The Dawn of Natural Language to SQL: Are We Fully Ready? | 2024 | VLDB | 6.8672143e-05 |
| 2,988 | NL2SQL is a solved problem... Not! | 2024 | CIDR | 7.7761714e-05 |
| 9,151 | The Power of Constraints in Natural Language to SQL Translation | 2025 | VLDB | 4.3849295e-05 |
| 4,908 | Combining Small Language Models and Large Language Models for Zero-Shot NL2SQL | 2024 | VLDB | 5.8339245e-05 |
| 10,221 | NL2SQLBench: A Modular Benchmarking Framework for LLM-Enabled NL2SQL Solutions | 2026 | VLDB | 4.1945683e-05 |