A Design Space for the Critical Validation of LLM-Generated Tabular Data
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Date
2025
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
LLM-generated tabular data is creating new opportunities for data-driven applications in academia, business, and society. To leverage benefits like missing value imputation, labeling, and enrichment with context-aware attributes, LLM-generated data needs a critical validation process. The number of pioneering approaches is increasing fast, opening a promising validation space that, so far, remains unstructured. We present a design space for the critical validation of LLM-generated tabular data with two dimensions: First, the Analysis Granularity dimension-from within-attribute (single-item and multi-item) to acrossattribute perspectives (1×1, 1×m, and n×n). Second, the Data Source dimension-differentiating between LLM-generated values, ground truth values, explanations, and their combinations. We discuss analysis tasks for each dimension cross-cut, map 19 existing validation approaches, and discuss the characteristics of two approaches in detail, demonstrating descriptive power.
Description
@inproceedings{10.2312:eurova.20251101,
booktitle = {EuroVis Workshop on Visual Analytics (EuroVA)},
editor = {Schulz, Hans-Jörg and Villanova, Anna},
title = {{A Design Space for the Critical Validation of LLM-Generated Tabular Data}},
author = {Sachdeva, Madhav and Narayanan, Christopher and Wiedenkeller, Marvin and Sedlakova, Jana and Bernard, Jürgen},
year = {2025},
publisher = {The Eurographics Association},
ISSN = {2664-4487},
ISBN = {978-3-03868-283-7},
DOI = {10.2312/eurova.20251101}
}