Adapting the Facebook Reels RecSys AI Model Based on User Feedback

This post details the development and integration of the User True Interest Survey (UTIS) model into Facebook Reels' recommendation system. The UTIS model leverages direct user feedback from surveys to improve interest matching beyond traditional engagement signals like likes and watch time. It introduces a lightweight alignment model layer trained on binarized survey responses and existing model predictions. The UTIS score is integrated into both late-stage ranking (LSR) and early-stage ranking (retrieval) to boost relevant content and reconstruct user interest profiles. Offline metrics show significant improvements in accuracy, precision, and recall, while online A/B tests with over 10 million users confirm increased engagement and retention.