AirGapAgent: Protecting Privacy-Conscious Conversational Agents
The growing use of large language model (LLM)-based conversational agents to manage
sensitive user data raises significant privacy concerns. While these agents excel at …
sensitive user data raises significant privacy concerns. While these agents excel at …
CASE-Bench: Context-Aware Safety Evaluation Benchmark for Large Language Models
Aligning large language models (LLMs) with human values is essential for their safe
deployment and widespread adoption. Current LLM safety benchmarks often focus solely on …
deployment and widespread adoption. Current LLM safety benchmarks often focus solely on …
Permissive Information-Flow Analysis for Large Language Models
Large Language Models (LLMs) are rapidly becoming commodity components of larger
software systems. This poses natural security and privacy problems: poisoned data retrieved …
software systems. This poses natural security and privacy problems: poisoned data retrieved …
AI Delegates with a Dual Focus: Ensuring Privacy and Strategic Self-Disclosure
Large language model (LLM)-based AI delegates are increasingly utilized to act on behalf of
users, assisting them with a wide range of tasks through conversational interfaces. Despite …
users, assisting them with a wide range of tasks through conversational interfaces. Despite …
Protecting Users From Themselves: Safeguarding Contextual Privacy in Interactions with Conversational Agents
Conversational agents are increasingly woven into individuals' personal lives, yet users
often underestimate the privacy risks involved. In this paper, based on the principles of …
often underestimate the privacy risks involved. In this paper, based on the principles of …