Limited Stereotype Control Through Routing Reweighting in MoE Language Models
The study used a framework called FARE to test if changing which experts an AI model uses (routing) could reliably control stereotypes. It found that while routing sensitivity exists in all MoE models, it often fails to change the actual text output. This means simply adjusting router preferences is not enough to guarantee fair generation.