In sequence transduction models, the process of transforming input sequences into output sequences is primarily achieved through _______ mechanisms, which allow the model to weigh the importance of different parts of the input when generating each part of the output.

In sequence transduction models, the transformation of input sequences into output sequences is primarily achieved through attention mechanisms, which let the model focus on different parts of the input when producing each output token. Attention works by assigning a weight to every input element for every output step, so the model can decide which input pieces matter most at that moment. This weighting is computed by comparing the current output state with all input states, producing a context vector that guides the next prediction. For example, when translating “I love you” into French, the model may give higher attention to “love” while generating “aime” in the output, ensuring accurate word alignment. Thus, attention mechanisms provide the flexibility needed for effective sequence transduction.