7 papers
Towards Contextual Sensitive Data Detection
Liang Telkamp, Madelon Hulsebos
The emergence of open data portals necessitates more attention to protecting sensitive data before datasets get published and exchanged. To do so effectively, we observe the need t…
Fine-Grained Table Retrieval Through the Lens of Complex Queries
Wojciech Kosiuk, Xingyu Ji, Yeounoh Chung +2
Enabling question answering over tables and databases in natural language has become a key capability in the democratization of insights from tabular data sources. These systems fi…
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…
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…
How well do LLMs reason over tabular data, really?
Cornelius Wolff, Madelon Hulsebos
Large Language Models (LLMs) excel in natural language tasks, but less is known about their reasoning capabilities over tabular data. Prior analyses devise evaluation strategies th…
Rethinking Dataset Discovery with DataScout
Rachel Lin, Bhavya Chopra, Wenjing Lin +3
Dataset Search -- the process of finding appropriate datasets for a given task -- remains a critical yet under-explored challenge in data science workflows. Assessing dataset suita…