The weak-to-strong generalization problem is the challenge of using smaller, less complex models to supervise and improve the training of larger, more powerful models. This issue is particularly significant as it mirrors a potential future scenario where humans or existing AI systems would need to supervise AI that is significantly more intelligent than themselves.