arXiv AI September 10, 2026 By Daniel Gomm, Maarten de Rijke, Madelon Hulsebos

Open Tabular Insight Extraction: Where Do We Stand, and Where Should We Go?

The paper introduces Open Tabular Insight Extraction (OpenTI), a unified framework aimed at democratizing access to insights from large table corpora. It highlights how current research is fragmented across domains like table QA, text‑to‑SQL, and data analysis agents, and shows that existing systems and benchmarks fall short of covering the full end‑to‑end scope of OpenTI. The authors propose a consolidated terminology, conduct a systematic review, and outline a research agenda for developing comprehensive OpenTI systems, evaluation methods, and interaction paradigms.

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