TabularARGN: A Flexible and Efficient Auto-Regressive Framework for Generating High-Fidelity Synthetic Data. - Paul Tiwald; Ivona Krchova; Andrey Sidorenko 003; Mariana Vargas Vieyra; Mario Scriminaci; Michael Platzer (CoRR, 2025)

Benchmarking Synthetic Tabular Data: A Multi-Dimensional Evaluation Framework. - Andrey Sidorenko 003; Michael Platzer; Mario Scriminaci; Paul Tiwald (CoRR, 2025)

A Note on Statistically Accurate Tabular Data Generation Using Large Language Models. - Andrey Sidorenko 003 (CoRR, 2025)

Democratizing Tabular Data Access with an Open-Source Synthetic-Data SDK. - Ivona Krchova; Mariana Vargas Vieyra; Mario Scriminaci; Andrey Sidorenko 003 (CoRR, 2025)

Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN. - Andrey Sidorenko 003; Paul Tiwald (CoRR, 2025)