all InfoSec news
DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models. (arXiv:2306.11698v4 [cs.CL] UPDATED)
cs.CR updates on arXiv.org arxiv.org
Generative Pre-trained Transformer (GPT) models have exhibited exciting
progress in their capabilities, capturing the interest of practitioners and the
public alike. Yet, while the literature on the trustworthiness of GPT models
remains limited, practitioners have proposed employing capable GPT models for
sensitive applications such as healthcare and finance -- where mistakes can be
costly. To this end, this work proposes a comprehensive trustworthiness
evaluation for large language models with a focus on GPT-4 and GPT-3.5,
considering diverse perspectives -- including …
applications assessment capabilities exciting finance generative gpt healthcare interest literature progress public sensitive trustworthiness