Beyond PII: How Users Attempt to Estimate and Mitigate Implicit LLM Inference

This publication has 46 references indexed in Scilit:

• Privacy disclosure to large language models: A large-scale study on awareness, benefits, and concerns in health contexts across three countries
  Computers in Human Behavior Reports, 2025
• The benefits and dangers of anthropomorphic conversational agents
  Proceedings of the National Academy of Sciences, 2025
• Understanding privacy concerns in ChatGPT: A data-driven approach with LDA topic modeling
  Heliyon, 2024
• Enhancing privacy policy comprehension through Privacify: A user-centric approach using advanced language models
  Computers & Security, 2024
• Security and Privacy Perceptions of Mental Health Chatbots
  2023
• Machine-Generated Text: A Comprehensive Survey of Threat Models and Detection Methods
  IEEE Access, 2023
• Tell Me, What Are You Most Afraid Of? Exploring the Effects of Agent Representation on Information Disclosure in Human-Chatbot Interaction
  2023
• Privacy Concerns in Chatbot Interactions: When to Trust and When to Worry
  2021
• Membership Inference Attacks Against Machine Learning Models
  2017
• Private traits and attributes are predictable from digital records of human behavior
  Proceedings of the National Academy of Sciences, 2013