Installing alignment values during pretraining from the beginning creates deeper, more robust alignment than adding it after training, and this advantage grows with more pretraining data.
This paper introduces Synthetic Persona Pretraining (SPP), a method that embeds desired values and assistant behavior directly into language models from the start of pretraining rather than adding them afterward.