EviLink: Multi-Path Schema Linking with Uncertainty-Guided Evidence Acquisition for Large-Scale Text-to-SQL
arXiv:2605.29670v1 Announce Type: cross Abstract: Schema linking is a difficult and important step in large-scale Text-to-SQL, where systems must identify a compact yet sufficient schema context from large and ambiguous databases. Existing methods often treat schema linking as deterministic selection around a single SQL path, but complex questions may admit multiple valid realizations with different schema needs. We reframe schema linking as uncertainty-aware schema-need inference over multiple plausible SQL paths, where the system distinguishes required schema items from path-dependent uncert
The proliferation of large language models and the increasing sophistication of AI necessitate more robust and nuanced methods for complex data interaction, making advanced text-to-SQL solutions a critical need for enterprise data accessibility.
This development improves how AI systems can query and understand large, ambiguous databases, leading to more accurate and reliable automated data extraction and analysis, which is crucial for decision-making across industries.
Current deterministic text-to-SQL methods are evolving towards uncertainty-aware, multi-path reasoning, allowing for more flexible and intelligent schema linking that better handles complex user queries and database structures.
- · AI developers
- · Data analytics companies
- · Large enterprises with complex databases
- · Database interaction platforms
- · Manual data scientists (for routine tasks)
- · Legacy text-to-SQL solutions
- · Companies with inefficient data access
- · Simple query interfaces
Enterprise AI applications will become significantly more capable in querying and interpreting complex, real-world data.
This improved data accessibility could accelerate automation of reporting and analytical functions, reducing the need for human intermediaries in data extraction.
The enhanced ability of AI to interact with large databases could lead to novel AI-driven applications and services, fundamentally changing how businesses interact with their own information assets.
This signal links to a primary source. Continuum Brief monitors and indexes it as part of the live intelligence stream — we do not republish source content.
Read at arXiv cs.AI