APE: Selective Fine-tuning with Acceptance Criteria for Language Model Adaptation
APE is a method for adapting large language models by selectively exploring parameter changes. It works by testing many small updates to the model using tiny data subsets and only keeping those that significantly improve performance. This ensures stable, beneficial changes with low computational cost.