Results 111 to 120 of about 9,267 (223)
Beyond Standard Losses: Redefining Text-to-SQL with Task-Specific Optimization
MathematicsIn recent years, large language models (LLMs) have shown an impressive ability in translating text to SQL queries. However, in real-world applications, standard loss functions frequently fail to capture the complexity of queries adequately. Therefore, in
Iker Azurmendi +4 more
doaj +1 more source
Extractive Schema Linking for Text-to-SQL
Text-to-SQL is emerging as a practical interface for real world databases. The dominant paradigm for Text-to-SQL is cross-database or schema-independent, supporting application schemas unseen during training. The schema of a database defines the tables, columns, column types and foreign key connections between tables.
Glass, Michael +5 more
openaire +2 more sources
Towards Understanding the Generalization of Medical Text-to-SQL Models and Datasets. [PDF]
AMIA Annu Symp Proc, 2023 Tarbell R, Choo KR, Dietrich G, Rios A.
europepmc +1 more source
Refining Zero-Shot Text-to-SQL Benchmarks via Prompt Strategies with Large Language Models
Applied SciencesText-to-SQL leverages large language models (LLMs) for natural language database queries, yet existing benchmarks like BIRD (12,751 question–SQL pairs, 95 databases) suffer from inconsistencies—e.g., 30% of queries misalign with SQL outputs—and ...
Ruikang Zhou, Fan Zhang
doaj +1 more source
SE-HCL: Schema Enhanced Hybrid Curriculum Learning for Multi-Turn Text-to-SQL
IEEE AccessExisting multi-turn Text-to-SQL approaches, mainly use data in a randomized order when training the model, ignoring the rich structural information contained in the dialog and schema.
Yiyun Zhang +2 more
doaj +1 more source
Automatic Metadata Extraction for Text-to-SQL
Large Language Models (LLMs) have recently become sophisticated enough to automate many tasks ranging from pattern finding to writing assistance to code generation. In this paper, we examine text-to-SQL generation. We have observed from decades of experience that the most difficult part of query development lies in understanding the database contents ...
Shkapenyuk, Vladislav +3 more
openaire +2 more sources
Combining computational linguistics with sentence embedding to create a zero-shot NLIDB
ArrayAccessing relational databases using natural language is a challenging task, with existing methods often suffering from poor domain generalization and high computational costs. In this study, we propose a novel approach that eliminates the training phase
Yuriy Perezhohin +2 more
doaj +1 more source
ACT-SQL: In-Context Learning for Text-to-SQL with Automatically-Generated Chain-of-Thought [PDF]
, 2023 Hanchong Zhang +4 more
openalex +1 more source
Text-to-SQL for Enterprise Data Analytics
The introduction of large language models has brought rapid progress on Text-to-SQL benchmarks, but it is not yet easy to build a working enterprise solution. In this paper, we present insights from building an internal chatbot that enables LinkedIn's product managers, engineers, and operations teams to self-serve data insights from a large, dynamic ...
Chen, Albert +17 more
openaire +2 more sources
FinSQL: Model-Agnostic LLMs-based Text-to-SQL Framework for Financial Analysis
Text-to-SQL, which provides zero-code interface for operating relational databases, has gained much attention in financial analysis; because, financial professionals may not well-skilled in SQL programming.
Chen, Lu +7 more
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