The National Security Agency (NSA) Research Directorate recently selected “Decoding Trust: Comprehensive Assessment of Trustworthiness in GPT Models” as the winner of its 12th Annual Best Scientific Cybersecurity Paper Competition.
The winning paper, authored by 19 researchers, including professors Dawn Song, University of California at Berkeley; Bo Li, University of Illinois Urbana-Champaign; and Sanmi Koyejo, Stanford University, evaluated the framework for large language models (LLMs) and proposed a comprehensive trustworthiness evaluation for them, with a focus on generative pre-trained transformer (GPT) models.