Abacus: A Novel Self-Supervised Approach to Sequential User Modeling

This research introduces a novel self-supervised learning technique for sequential user modeling, potentially improving the accuracy of predictions based on user behavior. The paper's focus on distributional pretraining and event counting alignment suggests a sophisticated approach to capturing user patterns.