self-attention

[美]/ˌself.əˈten.ʃən/
[英]/ˌself.əˈten.ʃən/

释义

n.神经网络中一种机制,使模型在处理序列时能够权衡输入数据不同部分的重要性。

短语搭配

self-attention mechanism

自注意力机制

using self-attention

使用自注意力

self-attention layer

自注意力层

apply self-attention

应用自注意力

self-attention weights

自注意力权重

with self-attention

带有自注意力

self-attention scores

自注意力分数

self-attention model

自注意力模型

self-attention network

自注意网络

self-attention improved

自注意力提升

例句

the model utilizes self-attention to weigh the importance of different words in the input sequence.

该模型使用自注意力机制来衡量输入序列中不同词语的重要性。

self-attention allows the transformer to capture long-range dependencies effectively.

自注意力机制使转换器能够有效地捕捉长距离依赖关系。

we fine-tuned the pre-trained model with self-attention on a new dataset.

我们在新的数据集上使用自注意力机制微调了预训练模型。

the self-attention mechanism significantly improved the model's performance on the task.

自注意力机制显著提高了模型在任务上的表现。

visualizing self-attention weights provides insights into the model's reasoning process.

可视化自注意力权重可以深入了解模型的推理过程。

multi-head self-attention enables the model to attend to different aspects of the input.

多头自注意力机制使模型能够关注输入的不同方面。

self-attention layers are crucial for understanding context in natural language processing.

自注意力层对于理解自然语言处理中的上下文至关重要。

the self-attention mechanism helps the model resolve ambiguity in the sentence.

自注意力机制帮助模型解决句子中的歧义。

we compared self-attention with traditional recurrent neural networks.

我们将自注意力机制与传统的循环神经网络进行了比较。

the effectiveness of self-attention is well-established in the field of nlp.

自注意力机制在自然语言处理领域中的有效性已经得到充分证实。

self-attention contributes to better machine translation quality.

自注意力机制有助于提高机器翻译的质量。

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