Generating a synthetic dataset for fine-tuning LLMs with varied abstract reasoning tasks and formal solver verification

I've been thinking about building a pipeline to generate reasoning training data for LLMs, but I want to avoid the common failure mode of synthetic data where you just generate the same template with different...