Search Results for author:
Found 4 papers, 0 papers with code
Human-Centered Privacy Research in the Age of Large Language Models
The emergence of large language models (LLMs), and their increased use in user-facing systems, has led to substantial privacy concerns.
Reducing Privacy Risks in Online Self-Disclosures with Language Models
Motivated by the user feedback, we introduce the task of self-disclosure abstraction, which is paraphrasing disclosures into less specific terms while preserving their utility, e. g., "Im 16F" to "I'm a teenage girl".
Can Language Models be Instructed to Protect Personal Information?
While data leaks should be prevented, it is also crucial to examine the trade-off between the privacy protection and model utility of proposed approaches.
"It's a Fair Game", or Is It? Examining How Users Navigate Disclosure Risks and Benefits When Using LLM-Based Conversational Agents
To bridge this gap, we analyzed sensitive disclosures in real-world ChatGPT conversations and conducted semi-structured interviews with 19 LLM-based CA users.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
