Debiasing Sequential Recommenders through Distributionally Robust Optimization over System Exposure

Abstract

Sequential recommendation (SR) models are typically trained on user-item interactions which are affected by the system exposure bias, leading to the user preference learned from the biased SR model not being fully consistent with the true user preference. Exposure