208 citations · 245 across the 11 of their papers we have counts for
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cs.CR2024★ 1 cited
Prompt Obfuscation for Large Language Models
David Pape, Sina Mavali, Thorsten Eisenhofer +1
System prompts that include detailed instructions to describe the task performed by the underlying LLM can easily transform foundation models into tools and services with minimal o…
cs.CR2024★ 4 cited
Whispers in the Machine: Confidentiality in Agentic Systems
Jonathan Evertz, Merlin Chlosta, Lea Schönherr +1
Large language model (LLM)-based agents combine LLMs with external tools to automate tasks such as scheduling meetings, managing documents, or booking travel. While these integrati…