25 citations · 28 across the 6 of their papers we have counts for
6 papers
How Many Different Outputs Can a Transformer Generate?
Maxime Meyer, Mario Michelessa, Caroline Chaux +1
We study how we can leverage only a handful of characteristics of a transformer's architecture to closely predict the number of different sequences it can output, both qualitativel…
Distilling Human-Aligned Privacy Sensitivity Assessment from Large Language Models
Gabriel Loiseau, Damien Sileo, Damien Riquet +2
Accurate privacy evaluation of textual data remains a critical challenge in privacy-preserving natural language processing. Recent work has shown that large language models (LLMs)…
Adaptive Text Anonymization: Learning Privacy-Utility Trade-offs via Prompt Optimization
Gabriel Loiseau, Damien Sileo, Damien Riquet +2
Anonymizing textual documents is a highly context-sensitive problem: the appropriate balance between privacy protection and utility preservation varies with the data domain, privac…
Targeted Attacks: Redefining Spear Phishing and Business Email Compromise
Sarah Wassermann, Maxime Meyer, Sébastien Goutal +1
In today's digital world, cybercrime is responsible for significant damage to organizations, including financial losses, operational disruptions, or intellectual property theft. Cy…
NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation
Kaustubh D. Dhole, Varun Gangal, Sebastian Gehrmann +122
Data augmentation is an important component in the robustness evaluation of models in natural language processing (NLP) and in enhancing the diversity of the data they are trained…
Text Data Augmentation: Towards better detection of spear-phishing emails
Mehdi Regina, Maxime Meyer, Sébastien Goutal
Text data augmentation, i.e., the creation of new textual data from an existing text, is challenging. Indeed, augmentation transformations should take into account language complex…