collaborators

6 papers

cs.LG2025

Robust Detection of Synthetic Tabular Data under Schema Variability

G. Charbel N. Kindji, Elisa Fromont, Lina Maria Rojas-Barahona +1

The rise of powerful generative models has sparked concerns over data authenticity. While detection methods have been extensively developed for images and text, the case of tabular…

cs.LG2025

Tabular Data Generation Models: An In-Depth Survey and Performance Benchmarks with Extensive Tuning

G. Charbel N. Kindji, Lina Maria Rojas-Barahona, Elisa Fromont +1

The ability to train generative models that produce realistic, safe and useful tabular data is essential for data privacy, imputation, oversampling, explainability or simulation. H…

cs.LG2025

Datum-wise Transformer for Synthetic Tabular Data Detection in the Wild

G. Charbel N. Kindji, Elisa Fromont, Lina Maria Rojas-Barahona +1

The growing power of generative models raises major concerns about the authenticity of published content. To address this problem, several synthetic content detection methods have…

cs.LG2025

Synthetic Tabular Data Detection In the Wild

G. Charbel N. Kindji, Elisa Fromont, Lina Maria Rojas-Barahona +1

Detecting synthetic tabular data is essential to prevent the distribution of false or manipulated datasets that could compromise data-driven decision-making. This study explores wh…

cs.LG2024

Cross-table Synthetic Tabular Data Detection

G. Charbel N. Kindji, Lina Maria Rojas-Barahona, Elisa Fromont +1

Detecting synthetic tabular data is essential to prevent the distribution of false or manipulated datasets that could compromise data-driven decision-making. This study explores wh…

cs.CL2024

Navigating the Shadows: Unveiling Effective Disturbances for Modern AI Content Detectors

Ying Zhou, Ben He, Le Sun

With the launch of ChatGPT, large language models (LLMs) have attracted global attention. In the realm of article writing, LLMs have witnessed extensive utilization, giving rise to…