In this paper, the Citizen Lab’s Mohamed Amed and Jeffrey Knockel examine Chinese censorship bias in LLMs with a censorship detector they designed as part of the research. They warn that when LLMs are trained on state-censored texts, their output is more likely to align with the state. An Analysis of Chinese Censorship Bias in… Read more »