Interview with Bo Li: A comprehensive assessment of trustworthiness in GPT models

Bo Li and colleagues won an outstanding datasets and benchmark track award at NeurIPS 2023 for their work DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models. In this interview, Bo tells us about the research, the team's methodology, and key findings. We focus on assessing the safety and risks of foundation models. In particular, we provide the first comprehensive trustworthiness evaluation platform for large language models (LLMs). Given the wide adoption of LLMs, it is critical to understand their safety and risks in different scenarios before large deployments in the real world.