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Machine learning has made significant advancements in generative models, but there is still a need to fine-tune these models to better align with human preferences. Researchers have introduced a new method, called Maximizing Alignment Preference Optimization (MaPO), which integrates preference data into the training process to improve alignment and handle diverse stylistic discrepancies.