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ExpeSQL: An Efficient, Experience-Guided Decompositional Search Framework for Text-to-SQL

This work introduces ExpeSQL, a zero-shot, open-source–compatible, and efficient framework that combines divide-and-conquer reasoning, Best-of-N candidate selection, and self-critique with experience-guided refinement that establishes a new paradigm for deployable, self-improving Text-to-SQL systems in dynamic, real-wo...

Unknown authors · 0 citations
Conference Aug 2026

"Question→SQL→Wiki" Dynamic Wiki Graph for NL2SQL

To bridge the semantic gap in NL2SQL (Natural Language to SQL) tasks, this study proposes a "Question→SQL→Wiki" framework that leverages a dynamic Wiki Graph as an intermediate reasoning layer. Departing from conventional NL2SQL approaches that rely solely on end-to-end mapping, our method utilizes Large Language Model...

Jia-Xuan Liu, Shi-Yu Fang, Ji-Bing Wu et al. · 0 citations
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Text-to-SQL Evaluation Toolkit

Text-to-SQL systems translate natural language questions into executable SQL queries, enabling intuitive access to structured data. While recent large language models have substantially improved generation quality, evaluating these systems remains a complex challenge: SQL semantics are subtle, multiple valid query form...

Oktie Hassanzadeh, Yotam Perlitz, Nhan H. Pham et al. · 0 citations
#artificial intelligence Preprint Aug 2026

BIRD-History: A Benchmark for History-Driven Text-to-SQL with Fine-Grained Knowledge Annotations

BIRD-History is introduced, a benchmark consisting of 1,393 tasks across 11 databases, designed to evaluate text-to-SQL systems'ability to ground underspecified natural language questions using historical SQL scripts, and a plug-in retriever that extracts five types of external knowledge from historical SQL scripts, th...

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Guided Table Retrieval for Structured Data Search

guided table retrieval is presented, a four-phase pipeline that combines deterministic grounding via hash-based predictors, structural exploration of join-graph reachability, LLM-powered disambiguation of sources and targets, and algorithmic merging into minimal, topologically ordered join trees.

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#artificial intelligence Preprint Sep 2026

A Cost-Aware Agentic Architecture for NL-to-SQL over Nested Enterprise Schemas, with a New Benchmark

Natural-language-to-SQL systems have ad- vanced rapidly on academic benchmarks, yet production enterprise schemas exhibit graph- like, semi-structured, deeply nested structure that current benchmarks do not measure. We make two complementary contributions. First, we introduce the DevRev NL2SQL bench- mark: 900 executio...

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