Translations:Attention Mechanisms/31/en: Difference between revisions

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    '''Cross-attention''' is used when queries come from one sequence and keys/values come from another. In encoder-decoder {{Term|transformer|Transformers}}, the decoder attends to encoder outputs via cross-attention, enabling the model to condition its generation on the full input context.
    '''Cross-attention''' is used when queries come from one sequence and keys/values come from another. In encoder-decoder Transformers, the decoder attends to encoder outputs via cross-attention, enabling the model to condition its generation on the full input context.

    Revision as of 21:57, 27 April 2026

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    Message definition (Attention Mechanisms)
    '''Cross-attention''' is used when queries come from one sequence and keys/values come from another. In encoder-decoder {{Term|transformer|Transformers}}, the decoder attends to encoder outputs via cross-attention, enabling the model to condition its generation on the full input context.

    Cross-attention is used when queries come from one sequence and keys/values come from another. In encoder-decoder Transformers, the decoder attends to encoder outputs via cross-attention, enabling the model to condition its generation on the full input context.

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