2025
Resource-Efficient Anonymization of Textual Data via Knowledge Distillation from Large Language Models
COLING 2025industry
Protecting personal and sensitive information in textual data is increasingly crucial, especially when leveraging large language models (LLMs) that may pose privacy risks due to their API-based access. We introduce a novel approach and pipeline for anonymizing text across arbitrary domains without t…