Measuring Backdoor Persistence in Post-trained Large Language Models: The Cyber Resilience Scaling Coefficient

Data-poisoning backdoors implanted during supervised fine-tuning of large language models persist through subsequent clean training, yet the field lacks a bounded, scale-normalized metric for quantifying and comparing this persistence across architectures and training regimes. We propose the Cybe