Fusion Training for Mathematical Generalization in Large Language Models
Training AI to think deeply and answer quickly at the same time
Summary
Teaching language models to both reason through hard problems and give quick answers creates a tension between the two skills—more training on fast answers actually weakens the model's ability to think carefully. The order and balance of training matter: the right schedule can reduce this damage, but the best approach depends on how much of each type of training data you use.
Why it matters
As AI assistants take on both simple customer-service tasks and complex problem-solving work, companies need both speed and accuracy. This research shows they can't maximize both equally in one model, and gives engineers concrete guidance on how to balance this trade-off depending on their actual needs.