8 papers
FINER-SQL: Boosting Small Language Models for Text-to-SQL
Thanh Dat Hoang, Thanh Trung Huynh, Matthias Weidlich +4
Large language models have driven major advances in Text-to-SQL generation. However, they suffer from high computational cost, long latency, and data privacy concerns, which make t…
AV-SQL: Decomposing Complex Text-to-SQL Queries with Agentic Views
Minh Tam Pham, Trinh Pham, Tong Chen +3
Text-to-SQL is the task of translating natural language queries into executable SQL for a given database, enabling non-expert users to access structured data without writing SQL ma…
An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data
Trinh Pham, Thanh Tam Nguyen, Viet Huynh +2
Recent advances in large language models have strengthened Text2SQL systems that translate natural language questions into database queries. A persistent deployment challenge is to…
Toward a Vision-Language Foundation Model for Medical Data: Multimodal Dataset and Benchmarks for Vietnamese PET/CT Report Generation
Huu Tien Nguyen, Dac Thai Nguyen, The Minh Duc Nguyen +11
Vision-Language Foundation Models (VLMs), trained on large-scale multimodal datasets, have driven significant advances in Artificial Intelligence (AI) by enabling rich cross-modal…
A Multi-agent Text2SQL Framework using Small Language Models and Execution Feedback
Thanh Dat Hoang, Thanh Trung Huynh, Matthias Weidlich +4
Text2SQL, the task of generating SQL queries from natural language text, is a critical challenge in data engineering. Recently, Large Language Models (LLMs) have demonstrated super…
Scaling Text2SQL via LLM-efficient Schema Filtering with Functional Dependency Graph Rerankers
Thanh Dat Hoang, Thanh Tam Nguyen, Thanh Trung Huynh +2
Most modern Text2SQL systems prompt large language models (LLMs) with entire schemas -- mostly column information -- alongside the user's question. While effective on small databas…