Improving Large Language Model Safety Transparency And Calibration
Large language models may overstate safety & reliability. Researchers propose training LLMs to better recognize & communicate limitations & uncertainties, improving transparency & calibration.
This is a Plain English Papers summary of a research paper called Improving Large Language Model Safety Transparency and Calibration. If you like these kinds of analysis, you should join AImodels.fyi or follow me on Twitter. Overview This paper examines the issue of "exaggerated safety" in large language models (LLMs), where the models may overestimate the safety or reliability of their outputs. The authors propose an approach to mitigate this issue by training LLMs to better recognize and communicate the limitations and uncertainties of their responses. The research aims to improve...