10 citations · 10 across the 4 of their papers we have counts for
3 papers · 1 filter
Pneuma-Seeker: A Relational Reification Mechanism to Align AI Agents with Human Work over Relational Data
Muhammad Imam Luthfi Balaka, John Hillesland, Kemal Badur +1
When faced with data problems, many data workers cannot articulate their information need precisely enough for software to help. Although LLMs interpret natural-language requests,…
The Pneuma Project: Reifying Information Needs as Relational Schemas to Automate Discovery, Guide Preparation, and Align Data with Intent
Muhammad Imam Luthfi Balaka, Raul Castro Fernandez
Data discovery and preparation remain persistent bottlenecks in the data management lifecycle, especially when user intent is vague, evolving, or difficult to operationalize. The P…
Pneuma: Leveraging LLMs for Tabular Data Representation and Retrieval in an End-to-End System
Muhammad Imam Luthfi Balaka, David Alexander, Qiming Wang +3
Finding relevant tables among databases, lakes, and repositories is the first step in extracting value from data. Such a task remains difficult because assessing whether a table is…