BIRD benchmark
PulseAugur coverage of BIRD benchmark — every cluster mentioning BIRD benchmark across labs, papers, and developer communities, ranked by signal.
2 day(s) with sentiment data
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Text-to-SQL accuracy boosted by schema modeling and LLM context handling · 2 sources tracked
Researchers have demonstrated that advanced language models can achieve high accuracy in Text-to-SQL tasks without traditional schema linking, by directly processing relevant schema elements within their context window.…
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Reflect-SQL framework boosts Text-to-SQL accuracy with self-reflection
Researchers have developed Reflect-SQL, a new framework designed to improve the accuracy and reliability of Text-to-SQL systems. This framework utilizes a multi-stage self-reflection process, incorporating an LLM-as-a-j…
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Google's Gemini-SQL2 Tops Text-to-SQL Benchmarks with 80.04% Accuracy
Google Research has unveiled Gemini-SQL2, a new text-to-SQL capability built on Gemini 3.1 Pro. This system achieves 80.04% execution accuracy on the BIRD benchmark, surpassing previous entries and narrowing the gap to …
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New CA-SQL system boosts LLM Text-to-SQL accuracy on complex queries
Researchers have developed CA-SQL, a new Text-to-SQL system designed to improve the accuracy of large language models on complex database queries. CA-SQL dynamically adjusts its search for potential solutions based on t…