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Raw generative models do not generally produce globally accurate outputs given input prompts.

This is due to the manner of training and next-word-prediction (or more arbitrary masked-word prediction) is probabilistically 'greedy'. Namely, within a sampling of outputs, the next-prediction will be sampled based on their immediate likelihood. To improve the outputs, the models are further refined using various approaches. These approaches 'align' the output to accurately considered

Global alignment