4 citations · 5 across the 6 of their papers we have counts for
4 papers · 1 filter
From Data Querying to Data Investigations: Rethinking Natural Language Interfaces for Databases
Fabian Wenz, Zixuan Chen, Carsten Binnig
Natural language (NL) interfaces to databases have been optimized for the wrong problem. The dominant Text-to-SQL paradigm assumes that users ask questions that can be answered by…
RUBICON: Agentic AI for Messy Enterprise Data
Fabian Wenz, Felix Treutwein, Çagatay Demiralp +1
Enterprise data exists in many forms, such as tables, text, maps, e-mail, and CAD models, that are access-controlled and hidden behind bespoke interfaces. Current agentic AI system…
Mind the Data Gap: Bridging LLMs to Enterprise Data Integration
Moe Kayali, Fabian Wenz, Nesime Tatbul +1
Leading large language models (LLMs) are trained on public data. However, most of the world's data is dark data that is not publicly accessible, mainly in the form of private organ…
Making LLMs Work for Enterprise Data Tasks
Çağatay Demiralp, Fabian Wenz, Peter Baile Chen +3
Large language models (LLMs) know little about enterprise database tables in the private data ecosystem, which substantially differ from web text in structure and content. As LLMs'…