Our paper titled ‘A Unified Detection Framework for Inference-Stage Backdoor Defenses’ has been accepted at NeurIPS 2023. In this paper, we developed a unified framework for defending against backdoor attacks in both computer vision (CV) and natural language processing (NLP) applications, achieving up to a 300% improvement in terms of detection performance.