Synthetic Curriculum

Generate training data with progressive difficulty, enabling models to learn complex capabilities by starting with easy examples and gradually increasing challenge. Instead of training on a static dataset, synthetic curriculum dynamically generates examples at increasing difficulty levels. Early examples teach basic patterns (format, simple reasoning), while later examples require composition of multiple skills. The difficulty can be controlled by prompt complexity, required reasoning steps, or the number of concepts that must be combined. This mirrors how human learning progresses from simple to complex.