DSABench: Benchmarking Source Discovery, Coordination, and Execution for Multi-Database Agents
We present DSABench to evaluate these capabilities jointly.
ProofPaper ↗
Key points
- Most text-to-SQL benchmarks provide the target database.
- In a large data catalog, however, choosing the sources is part of the problem: an agent must find every database needed for a request, determine how their results fit together, and execute the resulting workflow.
- Executable contracts define source participation, cross-source dependencies, and source-local execution, while RouteEnv lets agents inspect public catalog evidence without revealing the gold annotations.
- On ambiguous tasks, clarification improves exact branch-source recovery by 39.8-43.2 percentage points.
Sources (1)
- [1]DSABench: Benchmarking Source Discovery, Coordination, and Execution for Multi-Database AgentsarXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 10, 08:17 AM
We present DSABench to evaluate these capabilities jointly.
Most text-to-SQL benchmarks provide the target database.
Extractive summary: sentences quoted from the sources.
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