3 papers
cs.IR2026
Open Tabular Insight Extraction: Where Do We Stand, and Where Should We Go?
Daniel Gomm, Maarten de Rijke, Madelon Hulsebos
Democratizing access to the knowledge held in large corpora of tables such as data lakes is emerging as a central research challenge. Research in this space is advancing and broade…
cs.IR2026
SQaLe: A Large Text-to-SQL Corpus Grounded in Real Schemas
Cornelius Wolff, Daniel Gomm, Madelon Hulsebos
Advances in large language models have accelerated progress in text-to-SQL, methods for converting natural language queries into valid SQL queries. A key bottleneck for developing…
cs.AI2025
Are We Asking the Right Questions? On Ambiguity in Natural Language Queries for Tabular Data Analysis
Daniel Gomm, Cornelius Wolff, Madelon Hulsebos
Natural language interfaces to tabular data must handle ambiguities inherent to queries. Instead of treating ambiguity as a deficiency, we reframe it as a feature of cooperative in…