4 papers
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…
CALE : Concept-Aligned Embeddings for Both Within-Lemma and Inter-Lemma Sense Differentiation
Bastien Liétard, Gabriel Loiseau
Lexical semantics is concerned with both the multiple senses a word can adopt in different contexts, and the semantic relations that exist between meanings of different words. To i…
Tau-Eval: A Unified Evaluation Framework for Useful and Private Text Anonymization
Gabriel Loiseau, Damien Sileo, Damien Riquet +2
Text anonymization is the process of removing or obfuscating information from textual data to protect the privacy of individuals. This process inherently involves a complex trade-o…