Anthropic researchers detail “model spec midtraining”, which adds a stage between pretraining and fine-tuning to improve generalization from alignment training

Anthropic researchers have introduced "model spec midtraining," a discrete training stage inserted between pretraining and fine-tuning designed to improve how alignment objectives generalize across diverse downstream tasks. Unlike standard RLHF or constitutional AI fine-tuning applied post-pretraining, this intermediate stage targets deeper internalization of behavioral specifications before task-specific adaptation begins. Alignment practitioners and safety researchers should pay close attention, as this approach directly addresses the persistent problem of alignment tax and specification generalization failures seen in conventional pipelines.