Gustavo Escobedo

Users can tell the difference in popularity composition of music recommendations, but they don’t necessarily prefer the calibrated options.

Autoguidance—using a model to guide itself—can effectively reduce popularity bias in diffusion recommenders, leading to fairer item exposure without significantly sacrificing accuracy.