Automatically generated, adaptive training scaffolds can significantly improve RL-trained language models by turning failure information into targeted guidance, with gains persisting even after scaffolds are removed at evaluation.
AutoScaffold is an AI system that automatically creates and adapts training guidance (scaffolds) for language models learning through reinforcement learning. A frozen teacher analyzes the student model's failures during training, diagnoses problems, and generates helpful strategies or hints that are removed at test time.