17 papers
EdgeLM: Edge Demonstrations for Language Models' Table Understanding
Soroush Omidvartehrani, Mohammadamin Habibollah, Mohammadreza Daviran +1
Large language models (LLMs) perform table-centric prediction through in-context learning, making demonstration selection critical to performance. Existing retrieval methods priori…
LDI: Localized Data Imputation for Text-Rich Tables
Soroush Omidvartehrani, Davood Rafiei
Missing values are pervasive in real-world tabular data and can significantly impair downstream analysis. Imputing them is especially challenging in text-rich tables, where depende…
FlexSQL: Flexible Exploration and Execution Make Better Text-to-SQL Agents
Quang Hieu Pham, Yang He, Ping Nie +5
Text-to-SQL over large analytical databases requires navigating complex schemas, resolving ambiguous queries, and grounding decisions in actual data. Most current systems follow a…
SynSQL: Synthesizing Relational Databases for Robust Evaluation of Text-to-SQL Systems
Mohammadamin Habibollah, Davood Rafiei
Evaluating text-to-SQL systems remains largely fragile: correctness is typically judged by executing predicted and gold SQL queries on a single static database, even though the sam…
Which English Do LLMs Prefer? Triangulating Structural Bias Towards American English in Foundation Models
Mir Tafseer Nayeem, Davood Rafiei
Large language models (LLMs) are increasingly deployed in high-stakes domains, yet they expose only limited language settings, most notably "English (US)," despite the global diver…
SQL-Exchange: Transforming SQL Queries Across Domains
Mohammadreza Daviran, Brian Lin, Davood Rafiei
We introduce SQL-Exchange, a framework for mapping SQL queries across different database schemas by preserving the source query structure while adapting domain-specific elements to…