The authors evaluated the cross-dialect performance of 13 LLMs (3B to frontier scale) on the BIRD and Spider benchmarks across SQLite, PostgreSQL, MySQL, and ClickHouse.
Query plans make text-to-SQL portable across database dialects
By having LLMs emit dialect-agnostic relational algebra plans instead of SQL, the authors achieve near-uniform cross-dialect accuracy across 13 models.
Big Tech
Corentin Royer (IBM Research, Zurich, Switzerland) · Robin Oester (IBM Research, Zurich, Switzerland) · Yotam Perlitz (IBM Research, Zurich, Switzerland) · Yannick Metz (ETH Zurich, Zurich, Switzerland) · Andrea Giovannini (IBM Research, Zurich, Switzerland) · Mennatallah El-Assady (ETH Zurich, Zurich, Switzerland)
Research Digest··2 min read
, SQLite) suffer substantial accuracy drops when deployed on others.
Why this paper
From IBM Research and ETH Zurich
In one line
Switching text-to-SQL generation from dialect-specific SQL to dialect-agnostic relational algebra query plans restores cross-dialect portability with little or no accuracy cost.
What we could check
- ·No code link found
- ·No weights link found
- ·No dataset link found
- ·No compute details found
- ·No stated limitations found
- ✓Reports numbers on named benchmarks (2 benchmarks)
Observed from the paper text and links we have. Absence here means we did not find it, not that it does not exist.
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