FinSQL: Model-Agnostic LLMs-based Text-to-SQL Framework for Financial Analysis

Summary: FinSQL: a model-agnostic LLM-based Text-to-SQL framework for finance, with prompt design, efficient fine-tuning, and output calibration. BULL, a financial T2S benchmark with wide tables across funds, stocks, and macro data, yields few-shot cross-database gains up to 36.64%. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 6783
Venue: SIGMOD
Year: 2024
Pagerank: 5.7486224e-05
Overall Rank: 5,033 | 64.99%
DOI: 10.1145/3626426.3653375

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 8 of 8 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
8,896	SQL-Factory: A Multi-Agent Framework for High-Quality and Large-Scale SQL Generation	2026	VLDB	4.427232e-05
9,151	The Power of Constraints in Natural Language to SQL Translation	2025	VLDB	4.3849295e-05
9,235	ThriftLLM: On Cost-Effective Selection of Large Language Models for Classification Queries	2025	VLDB	4.3690661e-05
10,051	Are Your LLM-based Text-to-SQL Models Secure? Exploring SQL Injection via Backdoor Attacks	2026	SIGMOD	4.1945683e-05
10,210	SchemaRAG: A Schema-aware Retrieval-Augmented Generation Framework for Text-to-SQL	2026	SIGMOD	4.1945683e-05
10,589	Birdie: Natural Language-Driven Table Discovery Using Differentiable Search Index	2025	VLDB	4.1945683e-05
10,693	Evoschema: Towards Text-To-Sql Robustness Against Schema Evolution	2025	VLDB	4.1945683e-05
10,784	Towards Automated Cross-domain Exploratory Data Analysis through Large Language Models	2025	VLDB	4.1945683e-05

Outgoing Citations (Sorted by Pagerank)

Showing 2 of 2 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank	Cited Paper	Year	Venue	Pagerank
369	Text-to-SQL Empowered by Large Language Models: A Benchmark Evaluation	2024	VLDB	0.0002547515
2,945	Few-shot Text-to-SQL Translation using Structure and Content Prompt Learning	2023	SIGMOD	7.8377395e-05

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