1 citations · 2 across the 6 of their papers we have counts for
6 papers
Tytan: Interactive Neurosymbolic Construction of Analytic Semantic Schemas from Relational Data
Donna Hooshmand, Shubham Shahi, Cameron Barrie +4
From natural-language query interfaces to automated report generation, data analysis tools need a description of the data: the real-world entities it contains, which columns functi…
RingSQL: Schema-Independent Synthetic Data Generation for Text-to-SQL Reinforcement Learning
Marko Sterbentz, Kevin Cushing, Cameron Barrie +1
Recent advances in text-to-SQL have been driven by larger models, better datasets, and new training methods like RLVR. However, progress remains limited by scarce high-quality trai…
Satyrn: A Platform for Analytics Augmented Generation
Marko Sterbentz, Cameron Barrie, Shubham Shahi +4
Large language models (LLMs) are capable of producing documents, and retrieval augmented generation (RAG) has shown itself to be a powerful method for improving accuracy without sa…
Lightweight Knowledge Representations for Automating Data Analysis
Marko Sterbentz, Cameron Barrie, Donna Hooshmand +7
The principal goal of data science is to derive meaningful information from data. To do this, data scientists develop a space of analytic possibilities and from it reach their info…
Summarization from Leaderboards to Practice: Choosing A Representation Backbone and Ensuring Robustness
David Demeter, Oshin Agarwal, Simon Ben Igeri +4
Academic literature does not give much guidance on how to build the best possible customer-facing summarization system from existing research components. Here we present analyses t…
Requirements for Open Political Information: Transparency Beyond Open Data
Andong Luis Li Zhao, Andrew Paley, Rachel Adler +6
A politically informed citizenry is imperative for a welldeveloped democracy. While the US government has pursued policies for open data, these efforts have been insufficient in ac…