Our work, "A Synthetic Data-Driven Conformity Scoring Framework for Robust Federated Learning" will soon be presented at WACV 2026. It introduces a novel technique for robust federated learning, using synthetic data to defend against adversaries in a privacy-preserving way. Results show improved performance against gradient manipulation and backdoors. Our paper is available (https://openaccess.thecvf.com/content/WACV2026/papers/Alharbi_SD-CSFL_A_Synthetic_Data-Driven_Conformity_Scoring_Framework_for_Robust_Federated_WACV_2026_paper.pdf), including our code. Thanks E. Alharbi, A. Kerim, and Q. Ni! :) #ai #federatedlearning #wacv