A Comparative Study of Light-weight Language Models for PII Masking and their Deployment for Real Conversational Texts

This article describes a research paper focusing on the application of lightweight language models for Personally Identifiable Information (PII) masking in conversational texts. The study likely compares different models in terms of their performance and efficiency for this specific task, and also explores the practical aspects of deploying these models in real-world scenarios.

• •Focuses on PII masking in conversational texts.
• •Investigates the use of lightweight language models.
• •Likely involves a comparative analysis of different models.
• •Explores deployment in real-world scenarios.